Archives For scientific communication

Author Information: Mirko Farina, King’s College London, mirko.farina@kcl.ac.uk.

Farina, Mirko. “Exploring the Concepts of Science in 166 Pages: Reviewing Nigel Sanitt.” Social Epistemology Review and Reply Collective 8, no. 4 (2019): 28-33.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-48g

A wax statue of Isaac Newton, deceased.
Image by Nadia via Flickr / Creative Commons

 

In Culture, Curiosity and Communication in Scientific Discovery, scientist Nigel Sanitt develops an empirically-informed, highly interdisciplinary, and richly holistic account of scientific progress and discovery. By drawing upon a vast range of historical and contemporary sources, Sanitt provides important, original insights to understand the nature of scientific reasoning and how it is practised.

The book contains a useful introduction in which Sanitt highlights the focal points of his project and 15 short chapters in which he further develops his positive proposal (the idea that the foundations of science are built on sand and that scientific theories are frameworks we use to model nature). The book also considers how meaning is created in science and argues that science is deeply grounded in questions.

In the first part of this critical notice I briefly summarise the book’s content. I then turn my attention to one of the most important theoretical tensions underlying it: the relationship between science and philosophy. I investigate this tension,  critically assess the claim that philosophy is dead (Hawking, 2010), and in agreement with Sanitt conclude that a synergetic relationship between science and philosophy is not only desirable but also mutually beneficial.

A Fast Walk Through Vast Territory

In chapters 1 and 2, Sanitt sets up the scene and looks at the role of truth in science (pp.2-6). He then goes on to discuss the function (prediction) of scientific theories (pp. 18-22) and their search for invariance (pp. 25-26). Sanitt also aptly reviews recent progresses in philosophy of science (pp.7-14) and convincingly argues that the foundations of science are built on sand. Let me notice here that the philosophical grounding of this latter set of ideas could have been enriched by discussing the work of Poincaré, Duhem, Lakatos and Feyerabend.

In chapters 3 and 4, Sanitt discusses two theories [the integrationist theory of meaning defended by Harris (1981); and the theory of problematology pioneered by Meyer 2014)] that play a pivotal role in the development of his book. In particular, the former (pp. 41-43) provides Sanitt with the conceptual palette for the latter, which he uses to argue that science is an answer-generating dynamic enterprise (p.53).

Chapters 5 and 6 focus on the idea that scientific theories are frameworks, networks with links and nodes (p.70), that we use to model nature. Here Sanitt gives the mathematical background to describe these networks using graph theory (pp.72-79).

Chapter 7 focuses on scientific communication and looks, in particular, at how scientists interact with the media, the public, the politicians, with scientific organisations, and with each other (pp.82-84). While the need for more public engagement is stressed, the picture that emerges is one where scientists are often forced, by lack of research funding, ‘to actively engage with all these actors in outreach, lobbying, publicity, and policy briefing’ (p.85). This highlights the political, economical and socio-cultural dimension of contemporary scientific practice, which – it is argued- may threaten the independence of science.

The central chapters of the book focus on the relation between science and literature (ch. 8), science and religion (ch. 9), science and art (ch. 10), and science and history (ch.11). Particularly interesting is chapter 10 where Sanitt looks at whether beauty (understood as Pythagorean harmony) can play a role in science (pp.105-107) and points out that many scientists were also successful artists (e.g. Feynman), musicians (e.g. Einstein, Plack, Heisenberg), or writers (e.g. Hoyle, Oppenheimer, Snow).

Chapters 12 looks at the relation between science and culture. Here Sanitt demonstrates that science -as an intellectual and practical pursuit- is deeply rooted and inexorably tied in with our culture (p.121). He also cogently argues for the crucial importance of science in our society (p.122).

Chapter 13 focuses on artificial intelligence and on consciousness (p.131).  Sanitt claims that in explaining these phenomena, ‘separating out meaning, thinking, embodiment, perception and decision making from each other does not work’ (p.135). He thus seems to endorse, albeit not stated, a view (Clark 1998) that involves mind, body and environment as direct and equal partners in the making of human cognitive behaviour.

In chapter 14 Sanitt looks at the relation between science and ethics. He reviews philosophical works on moral and ethical behaviour (pp.137-139), discusses examples of misconduct and professional malpractice in science (pp.141-142), and calls for the development of more rigorous enforcement measures to fight them (p.143).

Chapter 15 focuses on the relation between science and education, discusses gender anomalies in science (p.151) and calls for innovations (adoption of ebooks, contextualisation of textbooks) in educational practices (pp.152-153).

In chapter 16 Sanitt summarises what he has achieved in the book (pp.155-160) and concludes by condemning the idea that philosophy and science should be separated. He writes: ‘a lack of critical thinking skills leads to intellectual impoverishment and in the end, to poor science. There are many universities that include philosophy courses in their undergraduate science curriculum – this is to be encouraged’ (p.162).

Having described the contents of the monograph, I now briefly turn to what I believe is the most interesting theoretical tension underlying it; the relation between science and philosophy.

Philosophy and Science: A Sometimes Sublime Dynamic

The relation between science and philosophy is intricate and highly complicated, and is one that I can only start touching upon here. Roughly speaking we can say that until perhaps the 19th century, there was no real distinction between scientists and philosophers, and many of the greatest scientists were also great philosophers. Newton’s masterpiece, Philosophiae Naturalis Principia Mathematica (Newton, 1687/1999) is imbued with philosophical assumptions and is a paradigmatic example of this deep relation.

The gap between science and philosophy started to widen at the beginning of the last century when scientific specialisation drove a wedge between the two disciplines (Philipp, 1957). The gap became even more prominent over the last 50 years or so with the advent of the age of hyper-specialisation.

On the one hand, with the development of new technological breakthroughs, many scientists started to amass enormous amounts of empirical data (especially in disciplines like neuroscience, physics, and psychology) often forgetting (sometimes deliberately ignoring) the theoretical interpretation of such data; on the other hand, many philosophers failed to understand such developments and retreated to their ivory towers into the study of human affairs, leaving the study of nature to natural scientists and often deliberately refusing any interaction with them (this process is brilliantly summarised by Snow 1959/2012).

There were remarkable exceptions on both sides, of course. Einstein’s work (1935) demonstrated that there is a genuine interaction between science and philosophy. Heisenberg once said ‘my mind was formed by studying philosophy, Plato and that sort of thing’ (Buckley and Peat, 1996, p.6).

Russell (1914) argued that the difference between philosophy and science is of the degree not of kind.  Dewey (1938/1991) asserted that the roots of philosophy and science are the same. Poincaré (1905) and Duhem (1908/1991) spent their whole lives developing a ‘scientific philosophy’.

There are also numerous examples in the history of science that shows this deep mutual dependence and profound interaction. For example, Kepler and Sommerfeld were both inspired by Pythagorean ideas in developing their models of the harmonies of the solar system and of the atom (de Haro, 2013).

Non-Locality: Philosophy as a Guide for Quantum Physics

Next, however, I focus on the development of quantum mechanics and discuss a key moment in its history that shows how physical progress crucially depended on asking the right philosophical questions. The discussion of this case study demonstrates that the philosophical debate that took place during those years acted as a positive, driving force that pushed the development of science further.

In 1927, conflicting views on quantum physics started to crystallize. At the 5th Solvay conference in Brussels, Heisenberg declared quantum mechanics to be a ‘closed theory, whose fundamental physical and mathematical assumptions are no longer susceptible of any modification’ (Bacciagaluppi and Valentini, 2009, p. 437). With that assertion, Heisenberg voiced the feelings and the convinctions of many of his colleagues (among them Bohr, Pauli, and Dirac) also present at the conference.

Einstein, however, did not agree with Heisenberg. He believed that the so-called Copenhagen interpretation of quantum mechanics – the view that Heisenberg was indirectly defending —had philosophical implications (such as the lack of determinacy in physical quantities and events) that seemed undesirable.

Thus in 1935, with some of his colleagues (Podolsky, and Rosen), Einstein developed a famous thought experiment (known as EPR), which demonstrated the entanglement of two particles located at long distances and implied faster-than-light interactions. Since this explicitly contradicted Einstein’s theory of relativity, quantum mechanics had to be an incomplete theory and the Copenhagen interpretation had to be wrong.

With this thought experiment Einstein wanted to arrive at a theory that fullfilled some ontological desiderata. More precisely, he wanted the theory to accurately describe the real world while incorporating the requirement that physics should be independent of the observer.

While the study of paradoxes has always played an important role in physics, the formulation of the EPR paradox required the development of a neat philosophical stance about the principles and methods that were deemed to be appropriate and valuable for the development of the theory. Thus, this example paradigmatically shows that Einstein’s quest was philosophical in character and therefore that philosophical ideas indeed can play a major role in the development of scientific theories.

Contemporary Alienation

Recently, however, Stephen Hawking declared (2010) the official ‘death’ of philosophy (for similar arguments see also Weinberg, 1992 , for a review of similar arguments see Kerr, 2018). Commenting on the nature of reality, Hawking wrote: ‘traditionally these are questions for philosophy, but philosophy is dead. Philosophy has not kept up with modern developments in science, particularly physics. Scientists have become the bearers of the torch of discovery in our quest for knowledge’ (Hawking 2010, p. 5).

To be fair to Hawking, his remark seems to be about the current status of philosophy. It does not seem to be a claim about philosophy as a discipline and including all its history (as some critics of Hawking have recently argued). Also, when Hawking made that provocative claim, he probably referred to just metaphysics, the branch of philosophy that aspires to the most general understanding of nature – not to all philosophy.

Now, I don’t want to enter here the discussion of whether all metaphysics should be naturalised (Ladyman et al., 2007). But having given Hawking the fairest possible understanding, I would still like to point out that his view of contemporary philosophy is partial, misleading, and ill-informed.

This is because Hawking, when making that claim, ignored that nowadays there is lots of philosophy born out of metaphysics (philosophy of mind and cognitive science, philosophy of psychology, philosophy of neuroscience) that is deeply grounded in the sciences. He also ignored that there are many areas of research in philosophy (e.g. embodied cognition) that are inspired by scientific findings and that, in turn, guide scientific research. More importantly, he ignored that there are large groups of empirically-informed philosophers (I am one of them, for what that matters), who are increasing leaving their armchairs and ivory towers to work in close contact with scientists.

Here Sanitt, who is himself a scientist but one that is not crusading against philosophy, does (unlike Hawking) a good job in recognising the fundamental importance of philosophical thinking to scientific reasoning. He writes: ‘I believe that science research at the highest level is adversely affected by the lack of philosophical awareness and training for scientists’ (p.59).

Sanitt also recognises that ‘there are limits to the denial of philosophical import to science, which results in paralysis’ (p. 14) and goes on to condemn the process that has led to the fragmentation and alienation of science from philosophy: ‘science has been separated horizontally…from within by too much specialisation…..This separation … is also vertical in the sense that science is seen as a completely different kind of entity from areas dubbed the arts or literature. This kind of separation is just as damaging and just as specious’ (p.14).

The picture that Sanitt draws is therefore one where philosophy directly interacts with science on a number of different levels. In particular, Sanitt believes: i).that the way science is taught and practised should not be immune from philosophical speculations (p.12); ii).that philosophical theorising should play an instrumental role in raising the right questions (pp.52-55) that science aims to answer (pp.64-70); and iii).that philosophy should help scientists interfacing with the wider, non-academic, world (pp. 80-86). Sanitt sees in this collaboration the roots of scientific success and thus argues, pace Hawking, that a synergetic partnership between science and philosophy is highly desirable.

Conclusion

Culture, Curiosity and Communication in Scientific Discovery shines a light through the mist of scientific research. It convincingly makes the case that science is driven by questions that often have a philosophical nature. The book also demonstrates that the foundations of science are built on sand and that the search for truth is always elusive.

The volume is thorough and does not at all shy away from conceptual complexity – quite the opposite.  The impressive sheer wealth and breadth of information presented makes the volume worthwhile. The prose is engaging, the style is captivating, the argument is coherently presented.

Structurally, however, I question the author’s decision of having 16 short chapters, each containing a lot of different subsections (often trying to summarise complex debates in a page or two). Occasionally, this results in having half-backed subsections (e.g. ‘free will’, p.99), which do not fully capture the nuances and the complexities of the issues debated. This sometimes interrupts the flow of the argumentation and prevents the reader from understanding the main point being made.

Nevertheless, this is a much needed (and welcomed) contribution to the field. A must read for scientists and philosophers, and more generally, for all those who are interested in understanding how scientific theories are constructed and verified.

Contact details: mirko.farina@kcl.ac.uk 

References

Bacciagaluppi, Guido, and Antony Valentini. Quantum theory at the crossroads: reconsidering the 1927 Solvay conference. Cambridge, UK: Cambridge University Press, 2009.

Buckley, Paul, and F. David Peat. Glimpsing reality: Ideas in physics and the link to biology. Toronto, ON: University of Toronto Press, 1996.

Clark, Andy. Being there: Putting brain, body, and world together again. Cambridge, MA: MIT Press, 1998.

de Haro, Sebastian. “Science and Philosophy: A Love-Hate Relationship.” arXiv preprint arXiv:1307.1244 (2013).

Dewey, John. Logic, the theory of inquiry. Carbondale: IL, Southern University Press, 1938/1991.

Duhem, Pierre Maurice Marie. The aim and structure of physical theory. Vol. 13. Princeton, NJ: Princeton University Press, 1908/1991.

Einstein, Albert, Boris Podolsky, and Nathan Rosen. “Can quantum-mechanical description of physical reality be considered complete?.” Physical review 47, no. 10 (1935): 777.

Hawking, Stephen. The grand design. London, UK: Random House Digital, Inc., 2010.

Kerr, Eric. “A Hermeneutic of Non-Western Philosophy.” Social Epistemology Review and Reply Collective 7: 1-6, 2018

Ladyman, James, Don Ross, David Spurrett, and John Collier. Every thing must go: Metaphysics naturalized. Oxford, UK: Oxford University Press, 2007.

Newton, Isaac. The Principia: mathematical principles of natural philosophy. Berkeley: CA: University of California Press, 1687/1999.

Philipp, Frank. Philosophy of science: The link between science and philosophy. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1957

Poincaré, Henri. Science and hypothesis. Science Press, 1905.

Russell, Bertrand. Our Knowledge of the External World as a Field for Scientific Method in Philosophy. Chicago, IL and London, UK: Open Court Publishing, 1914.

Snow, Charles Percy. The two cultures. Cambridge, UK: Cambridge University Press, 1959/2012.

Weinberg, Steven. Dream of a final theory, the scientist’s search for the ultimate laws of nature. New York, NYC: Vintage Books, (1992).

Author Information: Gregory Sandstrom, Arena Blockchain, gregory.sandstrom@gmail.com.

Sandstrom, Gregory. “Is Blockchain an ‘Evolutionary’ or ‘Revolutionary’ Technology, and So What If It Is?: Digitally Extending Satoshi Nakamoto’s Distributed Ledger Innovation.” Social Epistemology Review and Reply Collective 8, no. 3 (2019): 17-49.

The pdf of the article gives specific page references, and includes the full text of the article. Shortlink, Part One: https://wp.me/p1Bfg0-47f. Shortlink: Part Two: https://wp.me/p1Bfg0-47m

Image by Tiger Pixel via Flickr / Creative Commons

 

Ideological Blockchain Evolutionism

There is also a position held that promotes what I call ‘ideological evolutionism’ in insisting that blockchain must be called a particularly ‘evolutionary’ phenomenon. This appears to be due largely to a broader ideological framework to which the authors are already committed.

This view requires either that blockchain should not be seen as a ‘revolutionary’ technology or use ideas available in literature produced by academics that promote something akin to the ‘evolution of everything,’ i.e. that ‘everything evolves’ based on the logic that ‘everything changes.’ This ideology is professed in the works of Matt Ridley and David Sloan Wilson among others.

Patrick T. Harker, President and Chief Executive Officer for the Federal Reserve Bank of Philadelphia, tells us that, “banking evolved its products and appendages just like the first single-cell organisms evolved fins and gills and eventually feet and legs.” (2017: 4) Here an analogy with the origins of life and animals implies that blockchain is an innovation of almost mythical proportion. Though it may surprise the people who use ‘evolution’ colloquially to hear this, not a few people actually do link the rise of blockchain to a broader understanding of life, human existence and their general worldview.

One of the most well-known ideological blockchain evolutionists is Naval Ravikant, co-founder of Angel List. “The Evolution of Everything by Matt Ridley, one of my favorite authors,” tells Ravikant. “If I can’t verify it on my own or if I cannot get there through science, then it may be true, it may be false, but it’s not falsifiable so I cannot view it as a fundamental truth. On the other side, I do know that evolution is true. I do know that we are evolved as survival and replication machines. I do know that we have an ego so that we get up off the ground and worms don’t eat us and we actually take action.” Ravikant also appeared on a podcast with Tim Ferris using a title “The Evolutionary Angel[1].” In short, Ravikant says, “I think almost everything about humans and human civilization is explained better by evolution than anything else[2].” To clarify what he means, he says,

“I use evolution as my binding principle in that it can explain a lot about how we behave towards each other and why we do certain things. / Ignoring that your genes want you to live in a certain way is a delusion that is going to hurt you. / I think a lot of modern society can be explained through evolution. One theory is that civilization exists to answer the question of who gets to mate. If you look around, from a purely sexual selection perspective, sperm is abundant and eggs are scarce. It’s an allocation problem. How do you choose which sperm gets the egg? / Literally all of the works of mankind and womankind can be traced down to people trying to solve that problem.”[3]

In short, we see an attempt at the ‘naturalisation’ of blockchain technology based on ideology or worldview, rather than ‘science.’

Similarly, but with a more academic focus, Chris Berg et al. (2018) are promoting an institutional evolutionary approach that mixes together ‘development’ with ‘evolution’. They ask: “How do blockchain protocols develop? How do they evolve? It is useful to see the development of blockchain innovation through the entrepreneurial innovation literature. Each sequential adaptation of a blockchain represents a new economic organisation, such as a firm.” (Ibid: 3)

For them, “Blockchain protocols offer us an evolutionary window into institutional change. The protocols are evolving under variation, replication and selection conditions, and researchers have a near complete and comprehensive window into those changes.” (Ibid: 10) This choice of terms follows on the work of Donald T. Campbell who attempted to apply Darwinian principles regarding biology to the human world, using the controversial notion of ‘blind variation and selective retention’ (cf. the Darwinian notion of ‘random mutation and natural selection’), which at the same time dislocates humanity’s power of choice by removing the teleological impulse[4] that is present in non-evolutionary and trans-evolutionary (Sandstrom 2016) viewpoints.

Nick Szabo is a major figure in blockchain space, perhaps most known for his coinage of the term ‘smart contract.’ Szabo is also somewhat prolific in his use of the term ‘evolution’ when it comes to cultural artefacts. He writes, “Common law is a highly evolved system of security for persons and property.” This draws on his general belief that, “Over many centuries of cultural evolution has emerged both the concept of contract and principles related to it, encoded into common law. Algorithmic information theory suggests that such evolved structures are often prohibitively costly to recompute. If we started from scratch, using reason and experience, it could take many centuries to redevelop sophisticated ideas like property rights that make the modern free market work.”

Szabo, however, notes that, “the digital revolution is radically changing the kinds of relationships we can have. … New institutions, and new ways to formalize the relationships that make up these institutions, are now made possible by the digital revolution. I call these new contracts ‘smart,’ because they are far more functional than their inanimate paper-based ancestors.” (1996) At the same time, he reminds us that, “Societies have evolved institutions such as firms and competitive markets to set prices, legal precedents and judicial proceedings to make judgments, and so forth.” (2002) Thus, we are proposed with a digital revolution happening inside of a broadly evolutionary version of human history.

Kartik Hegadekatti (2017) believes that, “Man has not only evolved biologically and culturally but also economically. Human economy has grown over many centuries through continuous addition of value. This value addition has been an evolutionary factor as it has influenced the formation of the main economic sectors-namely Primary, Secondary and Tertiary. Recently after the advent of Blockchain technology, Bitcoin achieved Gold parity. This paper analyses whether such an event will have any impact on the evolution of our economies.”

He suggests that,

“Man first settled down for agriculture, and started the process of economic and social development. In fact, this event led to conditions where mankind could experiment and evolve new economic and social systems. Earlier, during the hunter-gatherer phase, there were very few niche specialties. A hunter had to sharpen his [sic] own spear and go to hunt with the group. Once man settled down, distribution and differentiation of labor started. Villages sprang up where there were blacksmiths, cattle herders, and traders etc. who became part of the then-nascent human society.” (2017: 3)

Further, he writes that, “Consequently we may witness an explosion in technology entities, akin to the industrial revolution; A Technology Revolution. This may culminate in the creation of a truly Artificial Intelligence (as investment and research into Data analytics and automation technology will increase, thanks to investment in Blockchain Technology) leading to Technological Singularity.” (Ibid: 6)

In this final example of ideological blockchain evolutionism, we notice the author predicting a ‘Technological Singularity’ (cf. Ray Kurzweil’s dystopian scenario for humanity), which presents a kind of teleological goal and aim for human-machine interaction. Proponents of blockchain development who share this view may thus somehow still believe in technological revolutions that happen within a broader worldview in which everything, inevitably, is always and everywhere evolving.

Digitally Extending Blockchain

“The idea of cultural evolution strikes me as nothing but a dodge to put off the work of doing th[e] thinking, a piece of displacement activity brought in to dodge the conflict. It is not the right way to grasp the continuity between human and non-human nature. We need to drop it and find a better path[5].” – Mary Midgley (1984)

“Practitioners should be skeptical of claims of revolutionary technology.”

– Arvind Naryanan and Jeremy Clark (2017)

After having considered the ways various people write about blockchain as a constantly changing and ‘evolving’ technology, potentially a ‘revolutionary’ one, in this section I will offer an additional approach to blockchain development. My view is that blockchain technology is an example of a ‘social machine[6]‘ (Berners-Lee 1999) that most closely resembles the educational and agricultural extension movements from the late 19th and 20th centuries, which continue around the world today.

It is not necessary and can even be harmful or at least restrictive to use ‘evolutionary’ language to describe this alternative approach. In the current 21st century, we can thus consider the emergence and development of blockchain as a form of ‘digital extension services,’ which I will briefly elaborate on below and further in a forthcoming book chapter (Bailetti IGI, 2019).

The first thing to realise in order to make a simple yet crucial shift in language is that ‘change’ is the master category, not ‘evolution’ or ‘revolution’. That is to say that both evolution and revolution require change to happen, but change need not be either evolutionary or revolutionary. That is what makes change the master category over both evolution and revolution.

This basic semantic point serves an aim to help curb the rampant over-use and exaggeration of the ‘biological theory of evolution’ into the field of technology development that at the same time largely avoids identifying non-evolutionary or trans-evolutionary (Sandstrom 2017c) types of change. Instead, properly identifying the master category reveals that the intended new directions of social and cultural change due to blockchains are happening less rapidly and possibly also less disruptively compared to what many ‘blockchain revolution’ proponents enthusiastically claim.

Here it is worth noting that blockchain technology is based on not a few prior innovations, which when taken into account make it appear less revolutionary and more step-wise logically sequential. Such is the case that Naryanan and Clark make in their impressive paper “Bitcoin’s Academic Pedigree (2017). In it they state that, “many proposed applications of blockchains, especially in banking, don’t use Nakamoto consensus. Rather, they use the ledger data structure and Byzantine agreement, which, as shown, date to the ’90s. This belies the claim that blockchains are a new and revolutionary technology.” (Ibid)

They continue, concluding that, “most of the ideas in bitcoin that have generated excitement in the enterprise, such as distributed ledgers and Byzantine agreement, actually date back 20 years or more. Recognize that your problem may not require any breakthroughs—there may be long-forgotten solutions in research papers.” (Ibid) While nevertheless celebrating the significant achievement that Satoshi Nakamoto made in bringing multiple previous innovations together into Bitcoin, Naryanan and Clark reveal how the ‘revolutionary’ language of some proponents of blockchain can be considered as an exaggeration that avoids its historical precursors and likewise neglects the ‘shoulders of giants’ on which Nakamoto stood.

Junking the Blockchain Hype

Instead of either ‘evolution’ or ‘revolution,’ the alternative term ‘extension’ identifies inherently teleological, intentional and goal-oriented change-over-time. This term also adds considerable untapped value in connecting directly with the history of educational extension and agricultural extension mentioned in the introduction.

In both cases, the extension of knowledge, training and scientific innovations from centres to margins and from people in cities and at research institutes to people in rural areas around the world without convenient access to educational institutions has opened new opportunities for social learning and overall human development[7].

Thus, blockchain framed as an example of ‘digital extension services’ provides an analogy with applications for business, finance, governance[8], military[9], education, agriculture[10], cultural heritage[11], and any and all other institutions in society that may make use of peer-to-peer transaction-based systems that can be measured with data collection.

Burton Swanson et al. define ‘extension’ as “the organized exchange of information and the purposive transfer of skills.” (1997) It was such intentional diffusion of creative innovation and knowledge sharing that led to a worldwide movement of ‘extensionsists’ and ‘extension agents,’ that has arguably become the greatest social impact force, both personally and institutionally, perhaps alongside of universities, football (soccer) and major religions, that the world has ever known and experienced.

This is why I believe a discussion now of blockchain as ‘digital extension services’ is particularly ripe for exploration and why the regularly repeated question of whether or not blockchain is an ‘evolution or revolution’ is not currently as important. If blockchain is going to become a ‘revolutionary’ technology in the digital era, an ‘internet of trust,’ then it will require require some kind of individual and social ‘extension’ motif with goals, aims and purposes in mind in order to achieve this.

At the same time it appears crucial, however, to openly reject ‘evolutionary’ approaches to blockchain as if believing that the origin of Bitcoin did not happen as the result of a random and undirected process that was simply a result of external ‘environmental pressures’ (cf. blind variation and selective retention). Rather, Bitcoin and the technology now known as ‘blockchain’ were created intentionally by a pseudonymous programmer and cryptographer in 2008, with the first Bitcoin mined on January 3, 2009.

If Satoshi Nakamoto’s intentional creation is not credited as such, then an invitation to future blockchain chaos without planning or purpose will be the likely result. In short, an ‘evolutionary’ origins story for blockchain falls short of validity and simply makes no logical sense. Instead, more goal-oriented and teleological discussion is needed about where we are now heading through the use of distributed ledgers, which indeed may bring highly transformative social change to people around the world through digital peer-to-peer interactions.

Investment in Revolution

The question of whether or not blockchain is potentially a ‘revolutionary’ technology and what impact it will have on society raises many difficult questions to answer. To some degree it must involve speculative futuristics. The promises of ‘decentralisation’ and the removal of intermediaries (disintermediation) from digital social transactions that happen across borders and nations using the internet has led to what can be called ‘centre-phobia,’ or the fear of centralised institutions of social, economic and political power. Some proponents of blockchain are even calling for ‘leaderless democracy[12],’ which sounds more utopian and radical than what mainstream blockchain builders are aiming for.

The blockchain feature of having a timestamped, immutable record has many implications, including for deterrence of online criminal activity and financial fraud detection[13]. While much of the zeal for Bitcoin in the early years involved illicit use through the Silk Road website involving weapons, drugs, human trafficking and various nefarious schemes, other non-criminal uses of distributed ledger for ‘social impact[14]‘ soon started to arise that pushed the boundaries of what peer-to-peer networking and transacting around the world could enable.

All of these changes require the intentional and ‘signed’ (cf. key signatures) use of blockchain systems, where users must agree to accept the rules and regulations of the ledger community’s ‘Genesis Block’ in order to participate. Again, the language of ‘extension’ based on individual and social choices seems more suitable than outsourcing the conversation to biological or even environmental language.

To enable easily distinguishing ‘non-evolutionary’ change and ‘development’ from ‘evolutionary’ change, we may simply consider the effects of intentionality, purpose and aim[15]. When we explore the directions and trajectories that blockchain DLT is headed, we mean that people are consciously developing and building it and/or purchasing crypto-assets and digital currencies, i.e. they are ‘extending’ the innovation made by Satoshi Nakamoto with new applications.

Rest assured, however, with this new terminology in hand this does not necessarily mean that any one person knows, or even that it can be known exactly for certain, in which direction(s) blockchain is headed, such that a single person, group or institution can ‘control’ it, as Carter rightly identified above. Yet, while most people cautiously say they do not now know and cannot predict where blockchain is headed in the future, those who are actually building blockchains now should properly be given credit for their work and not left out of the conversation as if their plans are irrelevant to the eventual outcome of the technology’s growth.

Indeed, the goals, aims, visions and plans of many blockchain builders and investors will determine the trajectory of blockchain development; they are the ones who are now ‘in control’ of where the technology is headed since Satoshi Nakamoto has disappeared from public[16].

Similarly, the perspective which holds that all change that is gradual, rather than rapid, therefore, according to biological precedent, automatically counts as ‘evolutionary,’ turns out to be both false and unnecessary upon closer investigation. French Nobel prize winner in Medicine, François Jacob suggested that, “Natural selection does not work as an engineer works. It works like a tinkerer — a tinkerer who does not know exactly what he is going to produce but uses whatever he finds around him… to produce some kind of workable object[17].”

Yet with blockchain the ‘human selection[18]‘ or ‘human extension’ of technology is being done by software developers, legal experts and innovation leaders with particular practical goals and business solutions in mind, even if ‘tinkering’ is the method by which the development occurs. The key is that people are actively involved in plotting the trajectory of blockchain growth and application, in contra-distinction with the mere anthropomorphic appearance (design) of biological change over time.

It simply does not make sense, therefore, when speaking about blockchain technology to use the language of a biologist like Dawkins, who suggested based largely upon a reactionary view, that ‘natural selection,’ “has no purpose in mind. It has no mind and no mind’s eye. It does not plan for the future. It has no vision, no foresight, no sight at all. If it can be said to play the role of watchmaker in nature, it is the blind watchmaker.” (1986: 5) Instead, with blockchain, it is our deep sense of purpose, vision, foresight, and planning that will result in new opportunities to apply the technology in potentially beneficial and effective social and cultural, economic and political configurations.

Indeed, the all-too-human sense of vision and deliberate drive, even if the direction was not always entirely clear and involved a kind of groping for solutions towards an unknown future; this is what enabled Satoshi Nakamoto to bring together past innovations, to ideate, code and eventually build a technological, legal framework and community for Bitcoin users in the first place.

To write this off according to a non-inventive theory of biological evolution that has no foresight or personal agency is to unnecessarily reduce and even dangerously dehumanise the conversation about blockchain in a disparaging way. Instead, I believe that aiming to uplift the conversation involving blockchain for humanity’s individual and collective extension and benefit is what the situation now most urgently requires.

What was the problem to which blockchain presented a solution? Was Nakamoto mainly aiming to undermine the power of financial institutions following the USA’s Emergency Economic Stabilization Act of 2008, i.e. the great bailout for banking elites at massive cost to millions of citizens? What purposes need there be other than financial ones to inspire the invention of an immutable public ledger that may serve as the basis for a ‘blockchain revolution’?

A public ledger (cf. triple entry accounting) that eliminates the double spending problem for digital transactions involving money is a massively transformative technology in and of itself. Regardless of what purposes Nakamoto had in mind when designing, creating and developing Bitcoin, we now are faced with what to do with this invention in ways that not only disrupt older systems, but that rather may at the same time creatively uplift human development of people around the world. What seems most urgently needed nowadays is a globally-oriented, socially-responsible digital extension services built upon distributed ledger technologies, using a combination of human, informational and material resources to produce it.

Conclusion

“The extensions of man with their ensuing environments, it’s now fairly clear, are the principal area of manifestation of the evolutionary process[19].” – McLuhan (1968)

“Building is the only truth path. Creation.” … “Bitcoin started because of my ideas. It was my design, and it is my creation.” – Craig Steven Wright (2019)

Given the above survey of uses of both terms ‘evolution’ and ‘revolution’ with respect to blockchain in the available literature, it is clear at least that there is on-going debate between which term is more suitable. My preference is to drop the term ‘evolution’ as unnecessarily ambiguous and imprecise when applied to technology, while cautioning that ateleological language is not particularly helpful or constructive in the conversation about blockchain development.

Likewise, at this early stage of historical growth, we still don’t know what kind of ‘revolution’ blockchain may cause in combination with other emerging digital technologies (IoTs, UAVs, VR/AR, virtual assistants, neural nets, quantum computing, etc.). We may thus look with either some trepidation or tempered optimism at the potential for revolutionary changes with the coming of distributed ledgers, particularly in the way blockchain will impact society, economics, politics, and culture.

In this paper, a brief comparison towards blockchain’s ‘revolutionary’ impact was proposed in the educational extension movement and agricultural extension and advisory services. The worldwide extension movement in agriculture contributed to the so-called ‘Green Revolution[20]‘ of the 1950s and 60s through knowledge sharing and information transfer to farmers who otherwise would not have had access to new seeds, knowledge and farming techniques.

With blockchain as a globally-oriented technology built upon the internet, we are starting to see new opportunities for digital identity provision that opens access to vital resources for those who are currently identity-less, for money transfer across borders (remissions), and for opportunities to bring ‘banking to the unbanked.’ This transformation has the potential to unlock many available human resources that will be able to further develop societies and cultures through savings and investment in peoples’ futures, something now impossible via institutional gridlock, exclusion and information capture.

On the strictly academic level, distributed ledgers may turn out to be the greatest technology created since the ‘social survey’ (or questionnaire) itself with the prospect of gathering big data for multivariate analysis. Now with a partially anonymous (cf. pseudonymous) user platform to protect personal identities from recrimination and ‘outing,’ social scientific research may be able to provide greater safety and security for ethical studies of humanity via digital devices that was simply not available in the past.

Nevertheless, we are still largely in the theoretical stage of blockchain’s coming impact and no mass platform for collecting such linked social data has yet been created where peer-to-peer interactions can produce a cascading global network effect. The question of whether a ‘revolution’ is coming or not due to blockchain DLT is thus for many people one still of sheer fantasy or hopeful speculation waiting for a major consensus-building breakthrough.

The Origins and the Future

Whether or not a person believes Craig Steven Wright was ‘Satoshi Nakamoto’ (perhaps with helpers alongside) or not is beside the point that someone must have been the inventive creator of Bitcoin. It simply didn’t arise on its own without an inventor and creator or without a purpose, aim and plan for its roll-out. To posit an ‘evolutionary origin’ for blockchain DLT thus profoundly misses out on the crucial elements of intentional, planned, purposeful technological change. Instead, looking at blockchain as an ‘extension’ of peoples’ choices places priorities on human values and desires, which are not to be ignored, but rather individually and collectively celebrated.

That said, in closing it is worth noting that a ‘revolution’ would only happen involving blockchains if the technology is not limited in usage to banks, multi-national corporations, and intermediary holders of financial power that collect fees without adding actual value to communities and users. Rent-seeking behaviour and currency speculation indeed has levied a massive cost on human civilisation in terms of widening the inequality gap within and between nations.

Similarly, writes Lawrie, “the Extension Movement … had to battle against the prejudice of those who would prefer university education to remain a privilege for the few.” (2014: 79) An overall struggle for power can and therefore must be expected in attempts to control distributed ledgers via ‘super users’ and centralised databases that sell user information. If the champions of blockchain DLTs are also champions of human freedom and dignity of person, the result may turn out better for a majority, rather than a minority few.

The dangers also adds caution and concern to those who focus on blockchain’s supposed ‘revolutionary’ impact as something necessarily disruptive and even destructive. The rhetoric heats up especially when blockchain is framed as a kind of deterministic, unavoidable and inevitable change driven by forces outside of human control.

Does technology have a ‘mind of its own?’ If not, then who is in control? Who is innovating? Who is guiding, choosing and directing the development of blockchain technology? And are they creating it for their own selfish gains or for the broader aims of society and culture? These questions animate the underlying concerns in this paper that mainly attempted to distinguish between random, unguided and guided, responsible technological change.

While it is true that in some sense the identity of Satoshi Nakamoto does not matter anymore, as the so-called “genie is out of the bottle[21]” now with blockchain. I believe it is nevertheless wrong to suggest that no one is or even should be in control of blockchain development, even though Satoshi Nakamoto disappeared. The growing number of people now building blockchain technologies will create a new horizon in which this technology will impact humanity in the coming years in a profound way. We may therefore watch with interest at the various ways P2P and E2E digital interactions on a global scale will change the course of human history in the near future to come.

In short, blockchain technology is a non-evolutionary or trans-evolutionary phenomenon that is potentially revolutionary for how it will restructure human society and culture based on immutable, timestamped distributed public ledgers. Blockchain as a ‘social machine’ heralds digital extension services and a new era of social change-over-time. Let us be ready and unafraid to face the challenges that this technology brings as it both disrupts, re-creates and unites people in a way that was unimaginable until Satoshi’s blockchain was invented to change the world.

Contact details: gregory.sandstrom@gmail.com

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Videos

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“Are Blockchains Alive? Co-evolving with Technology” – Amanda Gutterman (ConsenSys) – https://www.youtube.com/watch?v=X7GkkGTnVwA

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“Blockchain Evolution” – https://www.youtube.com/watch?v=CULUqgfVteg

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“Blockchain Evolution” – https://www.youtube.com/watch?v=tGcuJoFZLOY

“Chandler Guo on The Bitcoin & Blockchain Revolution” – https://www.youtube.com/watch?v=J7g2JFn68LU

“Cryptos Are The EVOLUTION of Money and Blockchain is the REVOLUTION of Trust! Vlog#18” – Siam Kidd – https://www.youtube.com/watch?v=-nu2F6_K0S0

“DigiByte Blockchain – The evolution of the Internet & the revolution in the financial systems” – https://www.youtube.com/watch?v=w8h10ckU0sE “The revolution has already begun.”

“Don Tapscott – The Blockchain Revolution – https://www.youtube.com/watch?v=gZEmaSbqfYQ

“Evolution of Bitcoin” – Documentary Film – https://www.youtube.com/watch?v=HUpGHOLkoXs

“Evolution of Blockchain And Its Future Moving Forward In 2018!” – https://www.youtube.com/watch?v=YWlMoxMTbDQ

“Evolution of Blockchain in India:The value of Ownership.” – Mr.Akash Gaurav – TEDxKIITUniversity – https://www.youtube.com/watch?v=BtTJmb0jYzE

“Evolution of the Blockchain Economy” – Jeremy Gardner – Startup Grind – https://www.youtube.com/watch?v=Q7cPy6ITUm4

“Future Evolution of Blockchain” – Silicon Valley TV – https://www.youtube.com/watch?v=5_6m7LYIEo4

“Future Thinkers Podcast – a podcast about evolving technology, society and consciousness. https://futurethinkers.org/

“Genetics of Blockchain Evolution” – Reese Jones – https://www.youtube.com/watch?v=8fFsmuvyXeE

“Keynote: Blockchain’s Evolution: Digital Assets are getting Physical” – FinTech Worldwide” – https://www.youtube.com/watch?v=1p5PUn4z_Gs

“How the Blockchain revolution will change our lives? | Eddy Travia | TEDxIEMadrid” https://www.youtube.com/watch?v=ErxKm0b0DIU

“How the Blockchain Revolution Will Decentralize Power and End Corruption | Brian Behlendorf” https://www.youtube.com/watch?v=Tv-XR6gXfLI

“Interview for Bitcoin And Blockchain Evolution Podcast – Sarah Herring – “Evolution – There is a Revolution coming!” https://www.youtube.com/watch?v=tIZJsFotDdg

“John McAfee on Infowars: Nothing Can Stop The Blockchain Revolution” – https://www.youtube.com/watch?v=CssU9WBHx6k

“Make the blockchain business case: Evolution, not revolution” (only title, not in video) – PWC – https://www.youtube.com/watch?v=sjr_Wqwk1SI

“The blockchain evolution, from services…to smartphones.” – Mingis on Tech – https://www.youtube.com/watch?v=jvn5zZj5IR8

“The Blockchain Evolution” – Hewlett Packard – https://www.hpe.com/us/en/insights/videos/the-evolution-of-blockchain-1712.html

“The Blockchain Evolution” – https://www.youtube.com/watch?v=TeyeKXmqQn8

“The Blockchain Evolution” – Cambridge House International” – https://www.youtube.com/watch?v=nELBTdqeKuQ

“The Evolution of Bitcoin – Bill Barhydt – Global Summit 2018 | Singularity” Universityhttps://www.youtube.com/watch?v=CZjK1i9CE6U

“The Evolution of Blockchain and Global Vision (Shanghai)” https://www.youtube.com/watch?v=56rOLarCttA

“The Evolution Of Blockchain Over The Decades” – With David Birch” https://www.youtube.com/watch?v=yC8oBJSQ6vc

“The Evolution of Blockchain technology” – Amir Assif. Microsoft Israel” – https://www.youtube.com/watch?v=f_eKp1z5hj0

“The Evolution of Blockchain: How EOS is reinventing blockchain” – https://www.youtube.com/watch?v=R8aDGf8WpKs

“The Evolution of Blockchain” – Nicola Morris – https://www.youtube.com/watch?v=aSy-UJn1G1I

“The Evolution of Blockchain” – The State of Digital Money 18′ conference” – https://www.youtube.com/watch?v=RWfNVTgbqjc

“The Blockchain Revolution – Graham Richter, Accenture” – https://www.youtube.com/watch?v=AYTmjZmsUm4

“The Blockchain Revolution | Rajesh Dhuddu | TEDxHyderabad” – https://www.youtube.com/watch?v=OrnvX92vlu8

“The Blockchain Revolution by Talal Tabaa – ECOH 2018” – https://www.youtube.com/watch?v=AvRJ1kEQ2so

“The Blockchain Revolution Changing the Rules https://www.youtube.com/watch?v=GTgG8XzcVC0

“The Blockchain Revolution in Business and Finance” – https://www.youtube.com/watch?v=3SUfz6p0a7Y

“The blockchain revolution, the ultimate industry disruptor” – https://www.youtube.com/watch?v=7hEiHR-K_KY

“The Blockchain Revolution: From Organisations to Organism | Matan Field | TEDxBreda” – https://www.youtube.com/watch?v=2OSbseTJWfY

[1] https://tim.blog/2017/06/04/nick-szabo/

[2] http://www.businessinsider.com/angellist-ceo-naval-ravikant-shares-his-favorite-books-2015-8

[3] http://www.killingbuddha.co/the-present/2016/10/17/naval-ravikant-on-the-give-and-take-of-the-modern-world

[4] “Being teleological is the second worst thing you can be as a Historian. The worst is being Eurocentric.” – Joel Mokyr

[5] “Biological and Cultural Evolution.” 1984. ICR Monograph Series 20. https://idriesshahfoundation.org/biological-and-cultural-evolution/

[6] Berners-Lee writes of “interconnected groups of people acting as if they shared a larger intuitive brain,” defining social machines on the internet as “processes in which the people do the creative work and the machine does the administration.” (1999) Smart and Shadbolt provide an updated version: “Social Machines are Web-based socio-technical systems in which the human and technological elements play the role of participant machinery with respect to the mechanistic realisation of system level processes.” (2014)

[7] “Extension lectures offered many middle-class women almost their only contact with education beyond the secondary level, and in consequence women came to use the new movement in greater numbers than any other social group, and frequently displayed the greatest personal application.” – Lawrence Goldman (Dons and Workers, 1995: 88)

[8]  A blockchain is “a place [digital ledger] for storing data that is maintained by a network of nodes without anyone in charge.” – Jeremy Clark (2016, https://users.encs.concordia.ca/~clark/talks/2016_edemocracy.pdf)

[9]  See Kevin O’Brien’s (2018) “China, Russia, USA in Race to Use Blockchain for Military Operations.” https://bitcoinist.com/china-russia-usa-blockchain-military/ and Salvador Llopsis Sanchez’ “Blockchain Technology in Defence.” https://www.eda.europa.eu/webzine/issue14/cover-story/blockchain-technology-in-defence

[10] Andrew Braun’s (2018) “Blockchain & Agriculture: A Look at the Issues & Projects Aiming to Solve Them” https://blockonomi.com/blockchain-agriculture/ and “Digging into Blockchain in Agriculture.” https://blockchain.wtf/2018/11/industry-impacts/digging-into-blockchain-in-agriculture/

[11]  Zohar Elhanini’s (2018) “How Blockchain Changed The Art World In 2018.” https://www.forbes.com/sites/zoharelhanani/2018/12/17/how-blockchain-changed-the-art-world-in-2018/#30caa5333074

[12] “Without the need for any central control or mediator blockchains allow for leaderless democracy – a new way of governing human behaviour online through ‘one computer one vote’.” http://kmi.open.ac.uk/projects/name/open-blockchain

[13] “Bitcoin is an immutable evidence system, a ledger that stops fraud.” – Craig Steven Wright https://medium.com/@craig_10243/the-great-mining-swindle-2dec8ffa819d

[14] https://consensys.net/social-impact/

[15] “As a result of the new scientific orthodoxy, the origins of organisms and of artifacts are nowadays seen as radically different: blind natural selection versus the purposive, forward-looking, and intelligent activity of designers.” – Phillip Brey (2008)

[16] However, with the noteworthy possibility that Craig Steve Wright was Satoshi Nakamoto, as he is now claiming, as he did in 2016: “I was Satoshi.” (2019)

[17]  “Evolution and Tinkering.” Science, Vol. 196, No. 4295, June 1977: pp. 1161-1166.

[18] This term was used in 1890 by A.R. Wallace, co-discoverer of ‘natural selection’ with Charles Darwin, to distinguish human-made things from natural organisms, after Darwin’s death.

[19] War and Peace in the Global Village. With Quentin Fiore. New York: Bantam, 1968: p. 19.

[20] “The first Green Revolution enabled developing countries to experience large increases in crop production through the use of fertilisers, pesticides and high-yield crop varieties. Between 1960 and 2000, yields for all developing countries rose 208 per cent for wheat, 109 per cent for rice, 157 per cent for maize, 78 per cent for potatoes and 36 per cent for cassava. This success was most felt with rice growers in Asia and lifted many out of poverty. … Capital investments and agricultural extension services are key for farmers to properly adopt new technologies and raise their farms’ productivity. ” – Liu (2017)

[21] As Joseph Lubin of Ethereum and Consensus says, “She’s big, she can’t go back in.” [21] http://www.theepochtimes.com/n3/668104-the-entrepreneur-joe-lubin-coo-of-ethereum/

Author Information: Brian Martin, University of Wollongong, bmartin@uow.edu.au.

Martin, Brian. “Bad Social Science.” Social Epistemology Review and Reply Collective 8, no. 3 (2019): 6-16.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-47a

Image by Sanofi Pasteur via Flickr / Creative Commons

 

People untrained in social science frameworks and methods often make assumptions, observations or conclusions about the social world.[1] For example, they might say, “President Trump is a psychopath,” thereby making a judgement about Trump’s mental state. The point here is not whether this judgement is right or wrong, but whether it is based on a careful study of Trump’s thoughts and behaviour drawing on relevant expertise.

In most cases, the claim “President Trump is a psychopath” is bad psychology, in the sense that it is a conclusion reached without the application of skills in psychological diagnosis expected among professional psychologists and psychiatrists.[2] Even a non-psychologist can recognise cruder forms of bad psychology: they lack the application of standard tools in the field, such as comparison of criteria for psychopathy with Trump’s thought and behaviour.

“Bad social science” here refers to claims about society and social relationships that fall very far short of what social scientists consider good scholarship. This might be due to using false or misleading evidence, making faulty arguments, drawing unsupported conclusions or various other severe methodological, empirical or theoretical deficiencies.

In all sorts of public commentary and private conversations, examples of bad social science are legion. Instances are so common that it may seem pointless to take note of problems with ill-informed claims. However, there is value in a more systematic examination of different sorts of everyday bad social science. Such an examination can point to what is important in doing good social science and to weaknesses in assumptions, evidence and argumentation. It can also provide insights into how to defend and promote high-quality social analysis.

Here, I illustrate several facets of bad social science found in a specific public scientific controversy: the Australian vaccination debate. It is a public debate in which many partisans make claims about social dynamics, so there is ample material for analysis. In addition, because the debate is highly polarised, involves strong emotions and is extremely rancorous, it is to be expected that many deviations from calm, rational, polite discourse would be on display.

Another reason for selecting this topic is that I have been studying the debate for quite a number of years, and indeed have been drawn into the debate as a “captive of controversy.”[3] Several of the types of bad social science are found on both sides of the debate. Here, I focus mainly on pro-vaccination campaigners for reasons that will become clear.

In the following sections, I address several facets of bad social science: ad hominem attacks, not defining terms, use of limited and dubious evidence, misrepresentation, lack of reference to alternative viewpoints, lack of quality control, and drawing of unjustified conclusions. In each case, I provide examples from the Australian public vaccination debate, drawing on my experience. In a sense, selecting these topics represents an informal application of grounded theory: each of the shortcomings became evident to me through encountering numerous instances. After this, I note that there is a greater risk of deficient argumentation when defending orthodoxy.

With this background, I outline how studying bad social science can be of benefit in three ways: as a pointer to particular areas in which it is important to maintain high standards, as a toolkit for responding to attacks on social science, and as a reminder of the need to improve public understanding of social science approaches.

Ad Hominem

In the Australian vaccination debate, many partisans make adverse comments about opponents as a means of discrediting them. Social scientists recognise that ad hominem argumentation, namely attacking the person rather than dealing with what they say, is illegitimate for the purposes of making a case.

In the mid 1990s, Meryl Dorey founded the Australian Vaccination Network (AVN), which became the leading citizens’ group critical of government vaccination policy.[4] In 2009, a pro-vaccination citizens’ group called Stop the Australian Vaccination Network (SAVN) was set up with the stated aim of discrediting and shutting down the AVN.[5] SAVNers referred to Dorey with a wide range of epithets, for example “cunt.”[6]

What is interesting here is that some ad hominem attacks contain an implicit social analysis. One of them is “liar.” SAVNer Ken McLeod accused Dorey of being a liar, giving various examples.[7] However, some of these examples show only that Dorey persisted in making claims that SAVNers believed had been refuted.[8] This does not necessarily constitute lying, if lying is defined, as it often is by researchers in the area, as consciously intending to deceive.[9] To the extent that McLeod failed to relate his claims to research in the field, his application of the label “liar” constitutes bad social science.

Another term applied to vaccine critics is “babykiller.” In the Australian context, this word contains an implied social analysis, based on these premises: public questioning of vaccination policy causes some parents not to have their children vaccinated, leading to reduced vaccination rates and thence to more children dying of infectious diseases.

“Babykiller” also contains a moral judgement, namely that public critics of vaccination are culpable for the deaths of children from vaccination-preventable diseases. Few of those applying the term “babykiller” provide evidence to back up the implicit social analysis and judgement, so the label in these instances represents bad social science.

There are numerous other examples of ad hominem in the vaccination debate, on both sides. Some of them might be said to be primarily abuse, such as “cunt.” Others, though, contain an associated or implied social analysis, so to judge its quality it is necessary to assess whether the analysis conforms to conventions within social science.

Undefined terms

In social science, it is normal to define key concepts, either by explicit definitions or descriptive accounts. The point is to provide clarity when the concept is used.

One of the terms used by vaccination supporters in the Australian debate is “anti-vaxxer.” Despite the ubiquity of this term in social and mass media, I have never seen it defined. This is significant because of the considerable ambiguity involved. “Anti-vaxxer” might refer to parents who refuse all vaccines for their children and themselves, parents who have their children receive some but not all recommended vaccines, parents who express reservations about vaccination, and/or campaigners who criticise vaccination policy.

The way “anti-vaxxer” is applied in practice tends to conflate these different meanings, with the implication that any criticism of vaccination puts you in the camp of those who refuse all vaccines. The label “anti-vaxxer” has been applied to me even though I do not have a strong view about vaccination.[10]

Because of the lack of a definition or clear meaning, the term “anti-vaxxer” is a form of ad hominem and also represents bad social science. Tellingly, few social scientists studying the vaccination issue use the term descriptively.

In their publications, social scientists may not define all the terms they use because their meanings are commonly accepted in the field. Nearly always, though, some researchers pay close attention to any widely used concept.[11] When such a concept remains ill-defined, this may be a sign of bad social science — especially when it is used as a pejorative label.

Limited and Dubious Evidence

Social scientists normally seek to provide strong evidence for their claims and restrict their claims to what the evidence can support. In public debates, this caution is often disregarded.

After SAVN was formed in 2009, one of its initial claims was that the AVN believed in a global conspiracy to implant mind-control chips via vaccinations. The key piece of evidence SAVNers provided to support this claim was that Meryl Dorey had given a link to the website of David Icke, who was known to have some weird beliefs, such as that the world is ruled by shape-shifting reptilian humanoids.

The weakness of this evidence should be apparent. Just because Icke has some weird beliefs does not mean every document on his website involves adherence to weird beliefs, and just because Dorey provided a link to a document does not prove she believes in everything in the document, much less subscribes to the beliefs of the owner of the website. Furthermore, Dorey denied believing in a mind-control global conspiracy.

Finally, even if Dorey had believed in this conspiracy, this does not mean other members of the AVN, or the AVN as an organisation, believed in the conspiracy. Although the evidence was exceedingly weak, several SAVNers, after I confronted them on the matter, initially refused to back down from their claims.[12]

Misrepresentation

When studying an issue, scholars assume that evidence, sources and other material should be represented fairly. For example, a quotation from an author should fairly present the author’s views, and not be used out of context to show something different than what the author intended.

Quite a few campaigners in the Australian vaccination debate use a different approach, which might be called “gotcha”. Quotes are used to expose writers as incompetent, misguided or deluded. Views of authors are misrepresented as a means of discrediting and dismissing them.

Judy Wilyman did her PhD under my supervision and was the subject of attack for years before she graduated. On 13 January 2016, just two days after her thesis was posted online, it was the subject of a front-page story in the daily newspaper The Australian. The journalist, despite having been informed of a convenient summary of the thesis, did not mention any of its key ideas, instead claiming that it involved a conspiracy theory. Quotes from the thesis, taken out of context, were paraded as evidence of inadequacy.

This journalistic misrepresentation of Judy’s thesis was remarkably influential. It led to a cascade of hostile commentary, with hundreds of online comments on the numerous stories in The Australian, an online petition signed by thousands of people, and calls by scientists for Judy’s PhD to be revoked. In all the furore, not a single critic of her thesis posted a fair-minded summary of its contents.[13]

Alternative Viewpoints?

In high-quality social science, it is common to defend a viewpoint, but considered appropriate to examine other perspectives. Indeed, when presenting a critique, it is usual to begin with a summary of the work to be criticised.

In the Australian vaccination debate, partisans do not even attempt to present the opposing side’s viewpoint. I have never seen any campaigner provide a summary of the evidence and arguments supporting the opposition’s viewpoint. Vaccination critics present evidence and arguments that cast doubt on the government’s vaccination policy, and never try to summarise the evidence and arguments supporting it. Likewise, backers of the government’s policy never try to summarise the case against it.

There are also some intermediate viewpoints, divergent from the entrenched positions in the public debate. For example, there are some commentators who support some vaccines but not all the government-recommended ones, or who support single vaccines rather than multiple vaccines. These non-standard positions are hardly ever discussed in public by pro-vaccination campaigners.[14] More commonly, they are implicitly subsumed by the label “anti-vaxxer.”

To find summaries of arguments and evidence on both sides, it is necessary to turn to work by social scientists, and then only the few of them studying the debate without arguing for one side or the other.[15]

Quality Control

When making a claim, it makes sense to check it. Social scientists commonly do this by checking sources and/or by relying on peer review. For contemporary issues, it’s often possible to check with the person who made the claim.

In the Australian vaccination debate, there seems to be little attempt to check claims, especially when they are derogatory claims about opponents. I can speak from personal experience. Quite a number of SAVNers have made comments about my work, for example in blogs. On not a single occasion has any one of them checked with me in advance of publication.

After SAVN was formed and I started writing about free speech in the Australian vaccination debate, I sent drafts of some of my papers to SAVNers for comment. Rather than using this opportunity to send me corrections and comments, the response was to attack me, including by making complaints to my university.[16] Interestingly, the only SAVNer to have been helpful in commenting on drafts is another academic.

Another example concerns Andrew Wakefield, a gastroenterologist who was lead author of a paper in The Lancet suggesting that the possibility that the MMR triple vaccine (measles, mumps and rubella) might be linked to autism should be investigated. The paper led to a storm of media attention.

Australian pro-vaccination campaigns, and quite a few media reports, refer to Wakefield’s alleged wrongdoings, treating them as discrediting any criticism of vaccination. Incorrect statements about Wakefield are commonplace, for example that he lost his medical licence due to scientific fraud. It is a simple matter to check the facts, but apparently few do this. Even fewer take the trouble to look into the claims and counterclaims about Wakefield and qualify their statements accordingly.[17]

Drawing Conclusions

Social scientists are trained to be cautious in drawing conclusions, ensuring that they do not go beyond what can be justified from data and arguments. In addition, it is standard to include a discussion of limitations. This sort of caution is often absent in public debates.

SAVNers have claimed great success in their campaign against the AVN, giving evidence that, for example, their efforts have prevented AVN talks from being held and reduced media coverage of vaccine critics. However, although AVN operations have undoubtedly been hampered, this does not necessarily show that vaccination rates have increased or, more importantly, that public health has benefited.[18]

Defending Orthodoxy

Many social scientists undertake research in controversial areas. Some support the dominant views, some support an unorthodox position and quite a few try not to take a stand. There is no inherent problem in supporting the orthodox position, but doing so brings greater risks to the quality of research.

Many SAVNers assume that vaccination is a scientific issue and that only people with scientific credentials, for example degrees or publications in virology or epidemiology, have any credibility. This was apparent in an article by philosopher Patrick Stokes entitled “No, you’re not entitled to your opinion” that received high praise from SAVNers.[19] It was also apparent in the attack on Judy Wilyman, whose PhD was criticised because it was not in a scientific field, and because she analysed scientific claims without being a scientist. The claim that only scientists can validly criticise vaccination is easily countered.[20] The problem for SAVNers is that they are less likely to question assumptions precisely because they support the dominant viewpoint.

There is a fascinating aspect to campaigners supporting orthodoxy: they themselves frequently make claims about vaccination although they are not scientists with relevant qualifications. They do not apply their own strictures about necessary expertise to themselves. This can be explained as deriving from “honour by association,” a process parallel to guilt by association but less noticed because it is so common. In honour by association, a person gains or assumes greater credibility by being associated with a prestigious person, group or view.

Someone without special expertise who asserts a claim that supports orthodoxy implicitly takes on the mantle of the experts on the side of orthodoxy. It is only those who challenge orthodoxy who are expected to have relevant credentials. There is nothing inherently wrong with supporting the orthodox view, but it does mean there is less pressure to examine assumptions.

My initial example of bad social science was calling Donald Trump a psychopath. Suppose you said Trump has narcissistic personality disorder. This might not seem to be bad social science because it accords with the views of many psychologists. However, agreeing with orthodoxy, without accompanying deployment of expertise, does not constitute good social science any more than disagreeing with orthodoxy.

Lessons

It is all too easy to identify examples of bad social science in popular commentary. They are commonplace in political campaigning and in everyday conversations.

Being attuned to common violations of good practice has three potential benefits: as a useful reminder to maintain high standards; as a toolkit for responding to attacks on social science; and as a guide to encouraging greater public awareness of social scientific thinking and methods.

Bad Social Science as a Reminder to Maintain High Standards

Most of the kinds of bad social science prevalent in the Australian vaccination debate seldom receive extended attention in the social science literature. For example, the widely used and cited textbook Social Research Methods does not even mention ad hominem, presumably because avoiding it is so basic that it need not be discussed.

It describes five common errors in everyday thinking that social scientists should avoid: overgeneralisation, selective observation, premature closure, the halo effect and false consensus.[21] Some of these overlap with the shortcomings I’ve observed in the Australian vaccination debate. For example, the halo effect, in which prestigious sources are given more credibility, has affinities with honour by association.

The textbook The Craft of Research likewise does not mention ad hominem. In a final brief section on the ethics of research, there are a couple of points that can be applied to the vaccination debate. For example, ethical researchers “do not caricature or distort opposing views.” Another recommendation is that “When you acknowledge your readers’ alternative views, including their strongest objections and reservations,” you move towards more reliable knowledge and honour readers’ dignity.[22] Compared with the careful exposition of research methods in this and other texts, the shortcomings in public debates are seemingly so basic and obvious as to not warrant extended discussion.

No doubt many social scientists could point to the work of others in the field — or even their own — as failing to meet the highest standards. Looking at examples of bad social science can provide a reminder of what to avoid. For example, being aware of ad hominem argumentation can help in avoiding subtle denigration of authors and instead focusing entirely on their evidence and arguments. Being reminded of confirmation bias can encourage exploration of a greater diversity of viewpoints.

Malcolm Wright and Scott Armstrong examined 50 articles that cited a method in survey-based research that Armstrong had developed years earlier. They discovered that only one of the 50 studies had reported the method correctly. They recommend that researchers send drafts of their work to authors of cited studies — especially those on which the research depends most heavily — to ensure accuracy.[23] This is not a common practice in any field of scholarship but is worth considering in the interests of improving quality.

Bad Social Science as a Toolkit for Responding to Attacks

Alan Sokal wrote an intentionally incoherent article that was published in 1996 in the cultural studies journal Social Text. Numerous commentators lauded Sokal for carrying out an audacious prank that revealed the truth about cultural studies, namely that it was bunk. These commentators had not carried out relevant studies themselves, nor were most of them familiar with the field of cultural studies, including its frameworks, objects of study, methods of analysis, conclusions and exemplary pieces of scholarship.

To the extent that these commentators were uninformed about cultural studies yet willing to praise Sokal for his hoax, they were involved in a sort of bad social science. Perhaps they supported Sokal’s hoax because it agreed with their preconceived ideas, though investigation would be needed to assess this hypothesis.

Most responses to the hoax took a defensive line, for example arguing that Sokal’s conclusions were not justified. Only a few argued that interpreting the hoax as showing the vacuity of cultural studies was itself poor social science.[24] Sokal himself said it was inappropriate to draw general conclusions about cultural studies from the hoax,[25] so ironically it would have been possible to respond to attackers by quoting Sokal.

When social scientists come under attack, it can be useful to examine the evidence and methods used or cited by the attackers, and to point out, as is often the case, that they fail to measure up to standards in the field.

Encouraging Greater Public Awareness of Social Science Thinking and Methods

It is easy to communicate with like-minded scholars and commiserate about the ignorance of those who misunderstand or wilfully misrepresent social science. More challenging is to pay close attention to the characteristic ways in which people make assumptions and reason about the social world and how these ways often fall far short of the standards expected in scholarly circles.

By identifying common forms of bad social science, it may be possible to better design interventions into public discourse to encourage more rigorous thinking about evidence and argument, especially to counter spurious and ill-founded claims by partisans in public debates.

Conclusion

Social scientists, in looking at research contributions, usually focus on what is high quality: the deepest insights, the tightest arguments, the most comprehensive data, the most sophisticated analysis and the most elegant writing. This makes sense: top quality contributions offer worthwhile models to learn from and emulate.

Nevertheless, there is also a role for learning from poor quality contributions. It is instructive to look at public debates involving social issues in which people make judgements about the same sorts of matters that are investigated by social scientists, everything from criminal justice to social mores. Contributions to public debates can starkly show flaws in reasoning and the use of evidence. These flaws provide a useful reminder of things to avoid.

Observation of the Australian vaccination debate reveals several types of bad social science, including ad hominem attacks, failing to define terms, relying on dubious sources, failing to provide context, and not checking claims. The risk of succumbing to these shortcomings seems to be magnified when the orthodox viewpoint is being supported, because it is assumed to be correct and there is less likelihood of being held accountable by opponents.

There is something additional that social scientists can learn by studying contributions to public debates that have serious empirical and theoretical shortcomings. There are likely to be characteristic failures that occur repeatedly. These offer supplementary guidance for what to avoid. They also provide insight into what sort of training, for aspiring social scientists, is useful for moving from unreflective arguments to careful research.

There is also a challenge that few scholars have tackled. Given the prevalence of bad social science in many public debates, is it possible to intervene in these debates in a way that fosters greater appreciation for what is involved in good quality scholarship, and encourages campaigners to aspire to make sounder contributions?

Contact details: bmartin@uow.edu.au

References

Blume, Stuart. Immunization: How Vaccines Became Controversial. London: Reaktion Books, 2017.

Booth, Wayne C.; Gregory G. Colomb, Joseph M. Williams, Joseph Bizup and William T. FitzGerald, The Craft of Research, fourth edition. Chicago: University of Chicago Press, 2016.

Collier, David; Fernando Daniel Hidalgo and Andra Olivia Maciuceanu, “Essentially contested concepts: debates and applications,” Journal of Political Ideologies, 11(3), October 2006, pp. 211–246.

Ekman, Paul. Telling Lies: Clues to Deceit in the Marketplace, Politics, and Marriage. New York: Norton, 1985.

Hilgartner, Stephen, “The Sokal affair in context,” Science, Technology, & Human Values, 22(4), Autumn 1997, pp. 506–522.

Lee, Bandy X. The Dangerous Case of Donald Trump: 27 Psychiatrists and Mental Health Experts Assess a President. New York: St. Martin’s Press, 2017.

Martin, Brian; and Florencia Peña Saint Martin. El mobbing en la esfera pública: el fenómeno y sus características [Public mobbing: a phenomenon and its features]. In Norma González González (Coordinadora), Organización social del trabajo en la posmodernidad: salud mental, ambientes laborales y vida cotidiana (Guadalajara, Jalisco, México: Prometeo Editores, 2014), pp. 91-114.

Martin, Brian. “Debating vaccination: understanding the attack on the Australian Vaccination Network.” Living Wisdom, no. 8, 2011, pp. 14–40.

Martin, Brian. “On the suppression of vaccination dissent.” Science & Engineering Ethics. Vol. 21, No. 1, 2015, pp. 143–157.

Martin, Brian. Evidence-based campaigning. Archives of Public Health, 76, no. 54. (2018), https://doi.org/10.1186/s13690-018-0302-4.

Martin, Brian. Vaccination Panic in Australia. Sparsnäs, Sweden: Irene Publishing, 2018.

Ken McLeod, “Meryl Dorey’s trouble with the truth, part 1: how Meryl Dorey lies, obfuscates, prevaricates, exaggerates, confabulates and confuses in promoting her anti-vaccination agenda,” 2010, http://www.scribd.com/doc/47704677/Meryl-Doreys-Trouble-With-the-Truth-Part-1.

Neuman, W. Lawrence. Social Research Methods: Qualitative and Quantitative Approaches, seventh edition. Boston, MA: Pearson, 2011.

Scott, Pam; Evelleen Richards and Brian Martin, “Captives of controversy: the myth of the neutral social researcher in contemporary scientific controversies,” Science, Technology, & Human Values, Vol. 15, No. 4, Fall 1990, pp. 474–494.

Sokal, Alan D. “What the Social Text affair does and does not prove,” in Noretta Koertge (ed.), A House Built on Sand: Exposing Postmodernist Myths about Science (New York: Oxford University Press, 1998), pp. 9–22

Stokes, Patrick. “No, you’re not entitled to your opinion,” The Conversation, 5 October 2012, https://theconversation.com/no-youre-not-entitled-to-your-opinion-9978.

Wright, Malcolm, and J. Scott Armstrong, “The ombudsman: verification of citations: fawlty towers of knowledge?” Interfaces, 38 (2), March-April 2008.

[1] Thanks to Meryl Dorey, Stephen Hilgartner, Larry Neuman, Alan Sokal and Malcolm Wright for valuable feedback on drafts.

[2] For informed commentary on these issues, see Bandy X. Lee, The Dangerous Case of Donald Trump: 27 Psychiatrists and Mental Health Experts Assess a President (New York: St. Martin’s Press, 2017).

[3] Pam Scott, Evelleen Richards and Brian Martin, “Captives of controversy: the myth of the neutral social researcher in contemporary scientific controversies,” Science, Technology, & Human Values, Vol. 15, No. 4, Fall 1990, pp. 474–494.

[4] The AVN, forced to change its name in 2014, became the Australian Vaccination-skeptics Network. In 2018 it voluntarily changed its name to the Australian Vaccination-risks Network.

[5] In 2014, SAVN changed its name to Stop the Australian (Anti-)Vaccination Network.

[6] Brian Martin and Florencia Peña Saint Martin. El mobbing en la esfera pública: el fenómeno y sus características [Public mobbing: a phenomenon and its features]. In Norma González González (Coordinadora), Organización social del trabajo en la posmodernidad: salud mental, ambientes laborales y vida cotidiana (Guadalajara, Jalisco, México: Prometeo Editores, 2014), pp. 91-114.

[7] Ken McLeod, “Meryl Dorey’s trouble with the truth, part 1: how Meryl Dorey lies, obfuscates, prevaricates, exaggerates, confabulates and confuses in promoting her anti-vaccination agenda,” 2010, http://www.scribd.com/doc/47704677/Meryl-Doreys-Trouble-With-the-Truth-Part-1.

[8] Brian Martin, “Debating vaccination: understanding the attack on the Australian Vaccination Network,” Living Wisdom, no. 8, 2011, pp. 14–40, at pp. 28–30.

[9] E.g., Paul Ekman, Telling Lies: Clues to Deceit in the Marketplace, Politics, and Marriage (New York: Norton, 1985).

[10] On Wikipedia I am categorised as an “anti-vaccination activist,” a term that is not defined on the entry listing those in the category. See Brian Martin, “Persistent bias on Wikipedia: methods and responses,” Social Science Computer Review, Vol. 36, No. 3, June 2018, pp. 379–388.

[11] See for example David Collier, Fernando Daniel Hidalgo and Andra Olivia Maciuceanu, “Essentially contested concepts: debates and applications,” Journal of Political Ideologies, 11(3), October 2006, pp. 211–246.

[12] Brian Martin. “Caught in the vaccination wars (part 3)”, 23 October 2012, http://www.bmartin.cc/pubs/12hpi-comments.html.

[13] The only possible exception to this statement is Michael Brull, “Anti-vaccination cranks versus academic freedom,” New Matilda, 7 February 2016, who reproduced my own summary of the key points in the thesis relevant to Australian government vaccination policy. For my responses to the attack, see http://www.bmartin.cc/pubs/controversy.html – Wilyman, for example “Defending university integrity,” International Journal for Educational Integrity, Vol. 13, No. 1, 2017, pp. 1–14.

[14] Brian Martin, Vaccination Panic in Australia (Sparsnäs, Sweden: Irene Publishing, 2018), pp. 15–24.

[15] E.g., Stuart Blume, Immunization: How Vaccines Became Controversial (London: Reaktion Books, 2017).

[16] Brian Martin. “Caught in the vaccination wars”, 28 April 2011, http://www.bmartin.cc/pubs/11savn/.

[17] For own commentary on Wakefield, see “On the suppression of vaccination dissent,” Science & Engineering Ethics, Vol. 21, No. 1, 2015, pp. 143–157.

[18] Brian Martin. Evidence-based campaigning. Archives of Public Health, Vol. 76, article 54, 2018, https://doi.org/10.1186/s13690-018-0302-4.

[19] Patrick Stokes, “No, you’re not entitled to your opinion,” The Conversation, 5 October 2012, https://theconversation.com/no-youre-not-entitled-to-your-opinion-9978.

[20] Martin, Vaccination Panic in Australia, 292–304.

[21] W. Lawrence Neuman, Social Research Methods: Qualitative and Quantitative Approaches, seventh edition (Boston, MA: Pearson, 2011), 3–5.

[22] Wayne C. Booth, Gregory G. Colomb, Joseph M. Williams, Joseph Bizup and William T. FitzGerald, The Craft of Research, fourth edition (Chicago: University of Chicago Press, 2016), 272–273.

[23] Malcolm Wright and J. Scott Armstrong, “The ombudsman: verification of citations: fawlty towers of knowledge?” Interfaces, 38 (2), March-April 2008, 125–132.

[24] For a detailed articulation of this approach, see Stephen Hilgartner, “The Sokal affair in context,” Science, Technology, & Human Values, 22(4), Autumn 1997, pp. 506–522. Hilgartner gives numerous citations to expansive interpretations of the significance of the hoax.

[25] See for example Alan D. Sokal, “What the Social Text affair does and does not prove,” in Noretta Koertge (ed.), A House Built on Sand: Exposing Postmodernist Myths about Science (New York: Oxford University Press, 1998), pp. 9–22, at p. 11: “From the mere fact of publication of my parody, I think that not much can be deduced. It doesn’t prove that the whole field of cultural studies, or the cultural studies of science — much less the sociology of science — is nonsense.”

Author Information: Nuria Anaya-Reig, Universidad Rey Juan Carlos, nuria.anaya@urjc.es

Anaya-Reig, Nuria. “Teorías Implícitas del Investigador: Un Campo por Explorar Desde la Psicología de la Ciencia.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 36-41.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-434

Image by Joan via Flickr / Creative Commons

 

This article is a Spanish-language version of Nuria Anaya-Reig’s earlier contribution, written by the author herself:

Anaya-Reig, Nuria. “Implicit Theories Influencing Researchers: A Field for the Psychology of Science to Explore.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 25-30.

¿Qué concepciones tienen los investigadores sobre las características que debe reunir un estudiante para ser considerado un potencial buen científico? ¿En qué medida influyen esas creencias en la selección de candidatos? Estas son las preguntas fundamentales que laten en el trabajo de Caitlin Donahue Wylie (2018). Mediante un estudio cualitativo de tipo etnográfico, se entrevista a dos profesores de ingeniería en calidad de investigadores principales (IP) y a estudiantes de sendos grupos de doctorado, la mayoría graduados, como investigadores noveles. En total, la muestra es de 27 personas.

Los resultados apuntan a que, entre este tipo de investigadores, es común creer que el interés, la asertividad y el entusiasmo por lo que se estudia son indicadores de un futuro buen investigador. Además, los entrevistados consideran que el entusiasmo está relacionado con el deseo de aprender y la ética en el trabajo. Finalmente, se sugiere una posible exclusión no intencional en la selección de investigadores a causa de la aplicación involuntaria de sesgos por parte del IP, relativa a la preferencia de características propias de grupos mayoritarios (tales como etnia, religión o sexo), y se proponen algunas ideas para ayudar a minimizarlos.

Teorías Implícitas en los Sótanos de la Investigación

En esencia, el trabajo de Wylie (2018) muestra que el proceso de selección de nuevos investigadores por parte de científicos experimentados se basa en teorías implícitas. Quizás a simple vista puede parecer una aportación modesta, pero la médula del trabajo es sustanciosa y no carece de interés para la Psicología de la Ciencia, al menos por tres razones.

Para empezar, porque estudiar tales cuestiones constituye otra forma de aproximarse a la compresión de la psique científica desde un ángulo distinto, ya que estudiar la psicología del científico es uno de los ámbitos de estudio centrales de esta subdisciplina (Feist 2006). En segundo término, porque, aunque la pregunta de investigación se ocupa de una cuestión bien conocida por la Psicología social y, en consecuencia, aunque los resultados del estudio sean bastante previsibles, no dejan de ser nuevos datos y, por tanto, valiosos, que enriquecen el conocimiento teórico sobre las ideas implícitas: es básico en ciencia, y propio del razonamiento científico, diferenciar teorías de pruebas (Feist 2006).

En último lugar, porque la Psicología de la Ciencia, en su vertiente aplicada, no puede ignorar el hecho de que las creencias implícitas de los científicos, si son erróneas, pueden tener su consiguiente reflejo negativo en la población de investigadores actual y futura (Wylie 2018).

Ya Santiago Ramón y Cajal, en su faceta como psicólogo de la ciencia (Anaya-Reig and Romo 2017), reflexionaba sobre este asunto hace más de un siglo. En el capítulo IX, “El investigador como maestro”, de su obra Reglas y consejos sobre investigación científica (1920) apuntaba:

¿Qué signos denuncian el talento creador y la vocación inquebrantable por la indagación científica?

Problema grave, capitalísimo, sobre el cual han discurrido altos pensadores e insignes pedagogos, sin llegar a normas definitivas. La dificultad sube de punto considerando que no basta encontrar entendimientos perspicaces y aptos para las pesquisas de laboratorio sino conquistarlos definitivamente para el culto de la verdad original.

Los futuros sabios, blanco de nuestros desvelos educadores, ¿se encuentran por ventura entre los discípulos más serios y aplicados, acaparadores de premios y triunfadores en oposiciones?

Algunas veces, sí, pero no siempre. Si la regla fuera infalible, fácil resultara la tarea del profesor, bastaríale dirigirse a los premios extraordinarios de la licenciatura y a los números primeros de las oposiciones a cátedras. Mas la realidad se complace a menudo en burlar previsiones y malograr esperanzas. (Ramón y Cajal 1920, 221-222)

A Vueltas con las Teorías Implícitas

Recordemos brevemente que las teorías ingenuas o implícitas son creencias estables y organizadas que las personas hemos elaborado intuitivamente, sin el rigor del método científico. La mayoría de las veces se accede a su contenido con mucha dificultad, ya que la gente desconoce que las tiene, de ahí su nombre. Este hecho no solo dificulta una modificación del pensamiento, sino que lleva a buscar datos que confirmen lo que se piensa, es decir, a cometer sesgos confirmatorios (Romo 1997).

Las personas vamos identificando y organizando las regularidades del entorno gracias al aprendizaje implícito o incidental, basado en el aprendizaje asociativo, pues necesitamos adaptarnos a las distintas situaciones a las que nos enfrentamos. Elaboramos teorías ingenuas que nos ayuden a comprender, anticipar y manejar de la mejor manera posible las variadas circunstancias que nos rodean. Vivimos rodeados de una cantidad de información tan abrumadora, que elaborar teorías implícitas, aprendiendo qué elementos tienden a presentarse juntos, constituye una forma muy eficaz de hacer el mundo mucho más predecible y controlable, lo que, naturalmente, incluye el comportamiento humano.

De hecho, el contenido de las teorías implícitas es fundamentalmente de naturaleza social (Wegner and Vallacher 1977), como muestra el hecho de que buena parte de ellas pueden agruparse dentro las llamadas Teorías Implícitas de la Personalidad (TIP), categoría a la que, por cierto, bien pueden adscribirse las creencias de los investigadores que nos ocupan.

Las TIP se llaman así porque su contenido versa básicamente sobre cualidades personales o rasgos de personalidad y son, por definición, idiosincráticas, si bien suele existir cierta coincidencia entre los miembros de un mismo grupo social.

Entendidas de modo amplio, pueden definirse como aquellas creencias que cada persona tiene sobre el ser humano en general; por ejemplo, pensar que el hombre es bueno por naturaleza o todo lo contrario. En su acepción específica, las TIP se refieren a las creencias que tenemos sobre las características personales que suelen presentarse juntas en gente concreta. Por ejemplo, con frecuencia presuponemos que un escritor tiene que ser una persona culta, sensible y bohemia (Moya 1996).

Conviene notar también que las teorías implícitas se caracterizan frente a las científicas por ser incoherentes y específicas, por basarse en una causalidad lineal y simple, por componerse de ideas habitualmente poco interconectadas, por buscar solo la verificación y la utilidad. Sin embargo, no tienen por qué ser necesariamente erróneas ni inservibles (Pozo, Rey, Sanz and Limón 1992). Aunque las teorías implícitas tengan una capacidad explicativa limitada, sí tienen capacidad descriptiva y predictiva (Pozo Municio 1996).

Algunas Reflexiones Sobre el Tema

Científicos guiándose por intuiciones, ¿cómo es posible? Pero, ¿por qué no? ¿Por qué los investigadores habrían de comportarse de un modo distinto al de otras personas en los procesos de selección? Se comportan como lo hacemos todos habitualmente en nuestra vida cotidiana con respecto a los más variados asuntos. Otra manera de proceder resultaría para cualquiera no solo poco rentable, en términos cognitivos, sino costoso y agotador.

A fin de cuentas, los investigadores, por muy científicos que sean, no dejan de ser personas y, como tales, buscan intuitivamente respuestas a problemas que, si bien condicionan de modo determinante los resultados de su labor, no son el objeto en sí mismo de su trabajo.

Por otra parte, tampoco debe sorprender que diferentes investigadores, poco o muy experimentados, compartan idénticas creencias, especialmente si pertenecen al mismo ámbito, pues, según se ha apuntado, aunque las teorías implícitas se manifiestan en opiniones o expectativas personales, parte de su contenido tácito es compartido por numerosas personas (Runco 2011).

Todo esto lleva, a su vez, a hacer algunas otras observaciones sobre el trabajo de Wylie (2018). En primer lugar, tratándose de teorías implícitas, más que sugerir que los investigadores pueden estar guiando su selección por un sesgo perceptivo, habría que afirmarlo. Como se ha apuntado, las teorías implícitas operan con sesgos confirmatorios que, de hecho, van robusteciendo sus contenidos.

Otra cuestión es preguntarse con qué guarda relación dicho sesgo: Wylie (2018) sugiere que está relacionado con una posible preferencia por las características propias de los grupos mayoritarios a los que pertenecen los IP basándose en algunos estudios que han mostrado que en ciencia e ingeniería predominan hombres, de raza blanca y de clase media, lo que puede contribuir a recibir mal a aquellos estudiantes que no se ajusten a estos estándares o que incluso ellos mismos abandonen por no sentirse cómodos.

Sin duda, esa es una posible interpretación; pero otra es que el sesgo confirmatorio que muestran estos ingenieros podría deberse a que han observado esos rasgos las personas que han  llegado a ser buenas en su disciplina, en lugar de estar relacionado con su preferencia por interactuar con personas que se parecen física o culturalmente a ellos.

Es oportuno señalar aquí nuevamente que las teorías implícitas no tienen por qué ser necesariamente erróneas, ni inservibles (Pozo, Rey, Sanz and Limón 1992). Es lo que ocurre con parte de las creencias que muestra este grupo de investigadores: ¿acaso los científicos, en especial los mejores, no son apasionados de su trabajo?, ¿no dedican muchas horas y mucho esfuerzo a sacarlo adelante?, ¿no son asertivos? La investigación ha establecido firmemente (Romo 2008) que todos los científicos creativos muestran sin excepción altas dosis de motivación intrínseca por la labor que realizan.

Del mismo modo, desde Hayes (1981) sabemos que se precisa una media de 10 años para dominar una disciplina y lograr algo extraordinario. También se ha observado que muestran una gran autoconfianza y que son espacialmente arrogantes y hostiles. Es más, se sabe que los científicos, en comparación con los no científicos, no solo son más asertivos, sino más dominantes, más seguros de sí mismos, más autónomos e incluso más hostiles (Feist 2006). Varios trabajos, por ejemplo, el de Feist y Gorman (1998), han concluido que existen diferencias en los rasgos de personalidad entre científicos y no científicos.

Pero, por otro lado, esto tampoco significa que las concepciones implícitas de la gente sean necesariamente acertadas. De hecho, muchas veces son erróneas. Un buen ejemplo de ello es la creencia que guía a los investigadores principales estudiados por Wylie para seleccionar a los graduados en relación con sus calificaciones académicas. Aunque dicen que las notas son un indicador insuficiente, a continuación matizan su afirmación: “They believe students’ demonstrated willingness to learn is more important, though they also want students who are ‘bright’ and achieve some ‘academic success.’” (2018, 4).

Sin embargo, la evidencia empírica muestra que ni las puntuaciones altas en grados ni en pruebas de aptitud predicen necesariamente el éxito en carreras científicas (Feist 2006) y que el genio creativo no está tampoco necesariamente asociado con el rendimiento escolar extraordinario y, lo que es más, numerosos genios han sido estudiantes mediocres (Simonton 2006).

Conclusión

La Psicología de la Ciencia va acumulando datos para orientar en la selección de posibles buenos investigadores a los científicos interesados: véanse, por ejemplo, Feist (2006) o Anaya-Reig (2018). Pero, ciertamente, a nivel práctico, estos conocimientos serán poco útiles si aquellos que más partido pueden sacarles siguen anclados a creencias que pueden ser erróneas.

Por tanto, resulta de interés seguir explorando las teorías implícitas de los investigadores en sus diferentes disciplinas. Su explicitación es imprescindible como paso inicial, tanto para la Psicología de la Ciencia si pretende que ese conocimiento cierto acumulado tenga repercusiones reales en los laboratorios y otros centros de investigación, como para aquellos científicos que deseen adquirir un conocimiento riguroso sobre las cualidades propias del buen investigador.

Todo ello teniendo muy presente que la naturaleza implícita de las creencias personales dificulta el proceso, porque, como se ha señalado, supone que el sujeto entrevistado desconoce a menudo que las posee (Pozo, Rey, Sanz and Limón 1992), y que su modificación requiere, además, un cambio de naturaleza conceptual o representacional (Pozo, Scheuer, Mateos Sanz and Pérez Echeverría 2006).

Por último, tal vez no sea razonable promover entre todos los universitarios de manera general ciertas habilidades, sin tener en consideración que reúnen determinados atributos. Por obvio que sea, hay que recordar que los recursos educativos, como los de cualquier tipo, son necesariamente limitados. Si, además, sabemos que solo un 2% de las personas se dedican a la ciencia (Feist 2006), quizás valga más la pena poner el esfuerzo en mejorar la capacidad de identificar con tino a aquellos que potencialmente son válidos. Otra cosa sería como tratar de entrenar para cantar ópera a una persona que no tiene cualidades vocales en absoluto.

Contact details: nuria.anaya@urjc.es

References

Anaya-Reig, N. 2018. “Cajal: Key Psychological Factors in the Self-Construction of a Genius.” Social Epistemology. doi: 10.1080/02691728.2018.1522555.

Anaya-Reig, N., and M. Romo. 2017. “Cajal, Psychologist of Science.” The Spanish Journal of Psychology 20: e69. doi: 10.1017/sjp.2017.71.

Feist, G. J. 2006. The Psychology of Science and the Origins of the Scientific Mind. New Haven, CT: Yale University Press.

Feist, G. J., and M. E. Gorman. 1998. “The Psychology of Science: Review and Integration of a Nascent Discipline.” Review of General Psychology 2 (1): 3–47. doi: 10.1037/1089-2680.2.1.3.

Hayes, J. R. 1981. The Complete Problem Solver. Philadelphia, PA: Franklin Institute Press.

Moya, M. 1996. “Percepción social y personas.” In Psicología social, 93-119. Madrid, Spain: McGraw-Hill.

Pozo Municio, J. I. 1996. Aprendices y maestros. La nueva cultura del aprendizaje. Madrid, Spain: Alianza.

Pozo, J. I., M. P. Rey, A. Sanz, and M. Limón. 1992. “Las ideas de los alumnos sobre la ciencia como teorías implícitas.” Infancia y Aprendizaje 57: 3-22.

Pozo, J. I., N. Scheuer, M. M. Mateos Sanz, and M. P. Pérez Echeverría. 2006. “Las teorías implícitas sobre el aprendizaje y la enseñanza.” In Nuevas formas de pensar la enseñanza y el aprendizaje: las concepciones de profesores y alumnos, 95-134. Barcelona, Spain: Graó.

Ramón y Cajal, S. 1920. Reglas y consejos sobre investigación científica. (Los tónicos de la voluntad). 5th ed. Madrid, Spain: Nicolás Moya.

Ramón y Cajal, S. 1999. Advice for a Young Investigator, translated by N. Swanson and L. W. Swanson. Cambridge, MA: The MIT Press.

Romo, M. 1997. Psicología de la creatividad. Barcelona, Spain: Paidós.

Romo, M. 2008. Epistemología y Psicología. Madrid, Spain: Pirámide.

Runco, M. 2011. “Implicit theories.” In Encyclopaedia of Creativity, edited by M. Runco and S. R. Pritzker, 644-646. 2nd ed. Elsevier.

Simonton, D. K. 2006. “Creative genius, Knowledge, and Reason. The Lives and Works of Eminents Creators.” In Creativity and reason in cognitive development, edited by J. C. Kaufman and J. Baer, 43-59. New York, NY: Cambridge University Press.

Wegner, D. M., and R. R, Vallacher. 1977. Implicit Psychology. An introduction to Social Cognition. New York, NY: Oxford University Press.

Wylie, C. D. 2018. “‘I Just Love Research’: Beliefs About What Makes Researchers Successful.” Social Epistemology 32 (4): 262-271, doi: 10.1080/02691728.2018.1458349.

Author Information: Nuria Anaya-Reig, Rey Juan Carlos University, nuria.anaya@urjc.es.

Anaya-Reig, Nuria. “Implicit Theories Influencing Researchers: A Field for the Psychology of Science to Explore.” Social Epistemology Review and Reply Collective 7, no. 11 (2018): 25-30.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-42K

From the 2014 White House Science Fair.
Image by NASA HQ Photo via Flickr / Creative Commons

 

This essay is in reply to:

Wylie, C. D. 2018. “‘I Just Love Research’: Beliefs About What Makes Researchers Successful.” Social Epistemology 32 (4): 262-271, doi: 10.1080/02691728.2018.1458349.

What traits in a student do researchers believe characterize a good future scientist? To what degree do these beliefs influence the selection of candidates? These are fundamental questions that resonate in the work of Caitlin Donahue Wylie (2018). As part of a qualitative ethnographic study, an interview was given to two engineering professors working as principal investigators (PIs), as well as to their respective groups of graduate students, most of whom were already working as new researchers. The total sample consisted of 27 people.

Results indicate that, among this class of researchers, interest, assertiveness, and enthusiasm for one’s own field of study are commonly regarded as key signs of a good future researcher. Moreover, the interviewees believe enthusiasm to be related to a desire to learn and a strong work ethic. Lastly, the research suggests that possible, unintentional exclusions may occur during candidate selection due to biases on the part of the PIs, reflecting preferences for features belonging to majority groups (such as ethnicity, religion and gender). This essay offers some ideas that may help minimize such biases.

Implicit Theories Undergirding Research

Essentially, the work of Wylie (2018) demonstrates that experienced scientists base their selection process for new researchers on implicit theories. While this may at first appear to be a rather modest contribution, the core of Wylie’s research is substantial and of great relevance to the psychology of science for at least three reasons.

First, studying such matters offers different angle from which to investigate and attempt to understand the scientific psyche: studying the psychology of scientists is one of the central areas of research in this subdiscipline (Feist 2006). Second, although the research question addresses a well-known issue in social psychology and the results of the study are thus quite predictable, the latter nevertheless constitute new data and are therefore valuable in their own right. Indeed, they enrich theoretical knowledge about implicit ideas given that, in science and scientific reasoning, it is essential to differentiate between tests and theories (Feist 2006).

Finally, because in the way it is currently being applied, the psychology of science cannot turn a blind eye to the fact that if scientists’ implicit beliefs are mistaken, those beliefs may have negative repercussions for the population of current and future researchers (Wylie 2018).

In his role as psychologist of science (Anaya-Reig and Romo 2017), Ramón y Cajal mused upon this issue over a century ago. In “The Investigator as Teacher,” chapter IX of his work Reglas y consejos sobre investigación científica (1920), he noted:

¿Qué signos denuncian el talento creador y la vocación inquebrantable por la indagación científica?

[What signs identify creative talent and an irrevocable calling for scientific research?]

Problema grave, capitalísimo, sobre el cual han discurrido altos pensadores e insignes pedagogos, sin llegar a normas definitivas. La dificultad sube de punto considerando que no basta encontrar entendimientos perspicaces y aptos para las pesquisas de laboratorio sino conquistarlos definitivamente para el culto de la verdad original.

[This serious and fundamentally important question has been discussed at length by deep thinkers and noted teachers, without coming to any real conclusions. The problem is even more difficult when taking into account the fact that it is not enough to find capable and clear-sighted and capable minds for laboratory research; they must also be genuine converts to the worship of original data.]

Los futuros sabios, blanco de nuestros desvelos educadores, ¿se encuentran por ventura entre los discípulos más serios y aplicados, acaparadores de premios y triunfadores en oposiciones?

[Are future scientists—the goal of our educational vigilance—found by chance among the most serious students who work diligently, those who win prizes and competitions?]

Algunas veces, sí, pero no siempre. Si la regla fuera infalible, fácil resultara la tarea del profesor, bastaríale dirigirse a los premios extraordinarios de la licenciatura y a los números primeros de las oposiciones a cátedras. Mas la realidad se complace a menudo en burlar previsiones y malograr esperanzas. (Ramón y Cajal 1920, 221-222)

[Sometimes, but not always. If the rule were infallible, the teacher’s work would be easy. He could simply focus his efforts on the outstanding prizewinners among the degree candidates, and on those at the top of the list in professional competitions. But reality often takes pleasure in laughing at predictions and in blasting hopes. (Ramón y Cajal 1999, 141)]

Returning to Implicit Theories

Let us briefly recall that naïve or implicit theories are stable and organized beliefs that people have formed intuitively, without the rigor of the scientific method; their content can be accessed only with great difficulty, given that people are unaware that they have them. This makes not only modifying them difficult but also leads those who possess them to search for facts that confirm what they already believe or, in other words, to fall prey to confirmation bias (Romo 1997).

People tend to identify and organize regularities in their environment thanks to implicit or incidental learning, which is based on associative learning, due to the need to adapt to the varying situations with which we are faced. We formulate naïve theories that help us comprehend, anticipate and deal with the disparate situations confronting us in the best way possible. Indeed, we are surrounded by a such an overwhelming amount of information that formulating implicit theories, learning which things seem to appear together at the same time, is a very effective way of making the world more predictable and controllable.

Naturally, human behavior is no exception to this rule. In fact, the content of implicit theories is fundamentally of a social nature (Wegner and Vallacher 1977), as is revealed by the fact that a good portion of such theories take the form of so-called Implicit Personality Theories (IPT), a category to which the beliefs of the researchers under consideration here also belong.

IPTs get their name because their content consists of personal qualities or personality traits. They are idiosyncratic, even if there indeed are certain coincidences among members of the same social group.

Understood broadly, IPTs can be defined as those beliefs that everyone has about human beings in general; for example, that man is by nature good, or just the opposite. Defined more precisely, IPTs refer to those beliefs that we have about the personal characteristics of specific types of people. For example, we frequently assume that a writer need be a cultured, sensitive and bohemian sort of person (Moya 1996).

It should be noted that implicit theories, in contrast to those of a scientific nature, are also characterized by their specificity and incoherence, given that they are based on simple, linear coincidences, are composed of ideas that are habitually interconnected, and seek only verification and utility. Still, this does not necessarily mean that such ideas are necessarily mistaken or useless (Pozo, Rey, Sanz and Limón 1992). Although implicit theories have a limited explanatory power, they do have descriptive and predictive capacities (Pozo Municio 1996).

Some Reflections on the Subject

Scientists being led by their intuitions…what is going on? Then again, what is wrong with that? Why must researchers behave differently from other people when engaged in selection processes? Scientists behave as we all do in our daily lives when it comes to all sorts of things. Any other way of proceeding would not just be unprofitable but also would be, in cognitive terms, costly and exhausting.

All things considered, researchers, no matter how rigorously scientific they may be, are still people and as such intuitively seek out answers to problems which influence their labor in specific ways while not in themselves being the goal of their work.

Moreover, we should not be surprised either when different researchers, whether novice or seasoned, share identical beliefs, especially if they work within the same field, since, as noted above, although implicit theories reveal themselves in opinions or personal expectations, part of their tacit content is shared by many people (Runco 2011).

The above leads one, in turn, to make further observations about the work of Wylie (2018). In the first place, as for implicit theories, rather than simply suggesting that researchers’ selections may be guided by a perceptual bias, it must be affirmed that this indeed is the case. As has been noted, implicit theories operate with confirmation biases which in fact reinforce their content.

Another matter is what sorts of biases these are: Wylie (2018) suggests that they often take the form of a possible preference for certain features that are characteristic of the majority groups to which the PIs belong, a conclusion based on several studies showing that white, middle-class men predominate in the fields of science and engineering, which may cause them to react poorly to students who do not meet those standards and indeed may even lead to the latter giving up because of the discomfort they feel in such environments.

This is certainly one possible interpretation; another is that the confirmation bias exhibited by these researchers might arise because they have observed such traits in people who have achieved excellence in their field and therefore may not, in fact, be the result of a preference for interacting with people who resemble them physical or culturally.

It is worth noting here that implicit theories need not be mistaken or useless (Pozo, Rey, Sanz and Limón 1992). Indeed, this is certainly true for the beliefs held by the group of researchers. Aren’t scientists, especially the best among them, passionate about their work? Do they not dedicate many hours to it and put a great deal of effort into carrying it out? Are they not assertive? Research has conclusively shown (Romo 2008) that all creative scientists, without exception, exhibit high levels of intrinsic motivation when it comes to the work that they do.

Similarly, since Hayes (1981) we have known that it takes an average of ten years to master a discipline and achieve something notable within it. It has also been observed that researchers exhibit high levels of self-confidence and tend to be arrogant and aggressive. Indeed, it is known that scientists, as compared to non-scientists, are not only more assertive but also more domineering, more self-assured, more self-reliant and even more hostile (Feist 2006). Several studies, like that of Feist and Gorman (1998) for example, have concluded that there are differences in personality traits between scientists and non-scientists.

On the other hand, this does not mean that people’s implicit ideas are necessarily correct. In fact, they are often mistaken. A good example of this is one belief that guided those researchers studied by Wylie as they selected graduates according to their academic credentials. Although they claimed that grades were an insufficient indicator, they then went on to qualify that claim: “They believe students’ demonstrated willingness to learn is more important, though they also want students who are ‘bright’ and achieve some ‘academic success.’” (2018, 4).

However, the empirical evidence shows that neither high grades nor high scores on aptitude tests are reliable predictors of a successful scientific career (Feist 2006). The evidence also suggests that creative genius is not necessarily associated with academic performance. Indeed, many geniuses were mediocre students (Simonton 2006).

Conclusion

The psychology of science continues to amass data to help orient the selection of potentially good researchers for those scientists interested in recruiting them: see, for example Feist (2006) or Anaya-Reig (2018). At the practical level, however, this knowledge will be of little use if those who are best able to benefit from it continue to cling to beliefs that may be mistaken.

Therefore, it is of great interest to keep exploring the implicit theories held by researchers in different disciplines. Making them explicit is an essential first step both for the psychology of science, if that discipline’s body of knowledge is to have practical repercussions in laboratories as well as other research centers, as well as for those scientists who wish to acquire rigorous knowledge about what inherent qualities make a good researcher, all while keeping in mind that the implicit nature of personal beliefs makes such a process difficult.

As noted above, subjects who are interviewed are often unaware that they possess them (Pozo, Rey, Sanz and Limón 1992). Moreover, modifying them requires a change of a conceptual or representational nature (Pozo, Scheuer, Mateos Sanz and Pérez Echeverría 2006).

Lastly, it may perhaps be unreasonable to promote certain skills among university students in general without considering the aptitudes necessary for acquiring them. Although it may be obvious, it should be remembered that educational resources, like those of all types, are necessarily limited. Since we know that only 2% of the population devotes itself to science (Feist 2006), it may very well be more worthwhile to work on improving our ability to target those students who have potential. Anything else would be like trying to train a person who has no vocal talent whatsoever to sing opera.

Contact details: nuria.anaya@urjc.es

References

Anaya-Reig, N. 2018. “Cajal: Key Psychological Factors in the Self-Construction of a Genius.” Social Epistemology. doi: 10.1080/02691728.2018.1522555.

Anaya-Reig, N., and M. Romo. 2017. “Cajal, Psychologist of Science.” The Spanish Journal of Psychology 20: e69. doi: 10.1017/sjp.2017.71.

Feist, G. J. 2006. The Psychology of Science and the Origins of the Scientific Mind. New Haven, CT: Yale University Press.

Feist, G. J., and M. E. Gorman. 1998. “The Psychology of Science: Review and Integration of a Nascent Discipline.” Review of General Psychology 2 (1): 3–47. doi: 10.1037/1089-2680.2.1.3.

Hayes, J. R. 1981. The Complete Problem Solver. Philadelphia, PA: Franklin Institute Press.

Moya, M. 1996. “Percepción social y personas.” In Psicología social, 93-119. Madrid, Spain: McGraw-Hill.

Pozo Municio, J. I. 1996. Aprendices y maestros. La nueva cultura del aprendizaje. Madrid, Spain: Alianza.

Pozo, J. I., M. P. Rey, A. Sanz, and M. Limón. 1992. “Las ideas de los alumnos sobre la ciencia como teorías implícitas.” Infancia y Aprendizaje 57: 3-22.

Pozo, J. I., N. Scheuer, M. M. Mateos Sanz, and M. P. Pérez Echeverría. 2006. “Las teorías implícitas sobre el aprendizaje y la enseñanza.” In Nuevas formas de pensar la enseñanza y el aprendizaje: las concepciones de profesores y alumnos, 95-134. Barcelona, Spain: Graó.

Ramón y Cajal, S. 1920. Reglas y consejos sobre investigación científica. (Los tónicos de la voluntad). 5th ed. Madrid, Spain: Nicolás Moya.

Ramón y Cajal, S. 1999. Advice for a Young Investigator, translated by N. Swanson and L. W. Swanson. Cambridge, MA: The MIT Press.

Romo, M. 1997. Psicología de la creatividad. Barcelona, Spain: Paidós.

Romo, M. 2008. Epistemología y Psicología. Madrid, Spain: Pirámide.

Runco, M. 2011. “Implicit theories.” In Encyclopaedia of Creativity, edited by M. Runco and S. R. Pritzker, 644-646. 2nd ed. Elsevier.

Simonton, D. K. 2006. “Creative genius, Knowledge, and Reason. The Lives and Works of Eminents Creators.” In Creativity and reason in cognitive development, edited by J. C. Kaufman and J. Baer, 43-59. New York, NY: Cambridge University Press.

Wegner, D. M., and R. R, Vallacher. 1977. Implicit Psychology. An introduction to Social Cognition. New York, NY: Oxford University Press.

Wylie, C. D. 2018. “‘I Just Love Research’: Beliefs About What Makes Researchers Successful.” Social Epistemology 32 (4): 262-271, doi: 10.1080/02691728.2018.1458349.

Author Information: Bernard Wills, Sir Wilfred Grenfell College (Memorial University), bwills@grenfell.mun.ca.

Wills, Bernard. “Weak Scientism: The Prosecution Rests.” Social Epistemology Review and Reply Collective 7, no. 10 (2018): 31-36.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-41T

Whoever has provoked men to rage against him has always gained a party in his favour too

Image by Vetustense Photorogue via Flickr / Creative Commons

 

On a lazy afternoon there is nothing like another defense of Weak Scientism to get the juices flowing. This one “Why Scientific Knowledge is Still the Best” is quite the specimen. It includes, among other delights, an attempt to humble my perceived pride based on a comparison between myself and my wonderful colleague Dr. Svetlana Barkanova. (Mizrahi, 2018c, 20)

Here I must concede defeat. I don’t hold a candle to the esteemed Dr. Barkanova and would never claim to be her equal. Plus, I need no metrics to convince me of this. I am well aware of her overall excellence as she is an acquaintance of mine. However, this petty display overshoots its mark. All I said was that journals have, in fact, published things (by me) Mizrahi explicitly claimed no journal would publish (2018b, 46) and, frankly, I think I have established that point with any objective reader. I am certainly not bragging or claiming I have some rock star status as a scholar. Let’s proceed then to address the specific arguments he offers in his essay.

Material Causes Behind Intellectual Appearances

I will begin with quantity. This is a point he claims I overemphasize though at the same time he claims it is a crucial component of his own argument. (2018c,19) At any rate, he goes on yet another tangent about the superior quantity and impact of scientific research. To this I respond again, so what? It is no doubt true that more research and more ‘impactful’ research is produced in the sciences but why is this so?

To quote Bill Clinton, “It’s the economy stupid”. Science serves the interests of corporations and the military in ways that the humanities do not and so more money gets directed to the sciences. Since this is the case more scientific research is produced overall.

Now one could make an argument that this speaks to an overall greater utility for the sciences as opposed to other domains, but this is not the argument Mizrahi makes. Rather he asserts raw quantity itself as a feature that makes for the superiority of science. In both my replies I explained the problem with this and in neither of his replies has Mizrahi rebutted my points.

I pointed out a. that commercials are not superior to great artworks even though their number and impact is greater and b. Shakespeare scholarship would not be superior to physics if it simply happened that there were more of it. Mizrahi’s response to this is to complain about the word ‘odd’ (Mizrahi, 19) as if I intended it as a gratuitous personal insult. Actually though, I intended only to imply that his position seemed odd. It still seems odd to me to claim that if Shakespeare scholars suddenly put out a tremendous burst of articles (and pulled into the lead in the great race to produce more and more research) then that would somehow throw particle physics in the shade.

But, if Mizrahi wants to accept that conclusion then he is certainly welcome to it. If he wants to say that weak scientism is only contingently true and that it is only contingently the case that the sciences happen currently to produce more impactful research (for whatever reason), then he has done only what he all too often does; won a debating point by reducing his own thesis to a truism, here, that more =more. (Mizrahi, 19) At any rate, the frustrating thing here is that while Mizrahi asserts again and again the quantitative superiority of science he never condescends to explain why quantity is a valid metric in the first place, he asserts the fact without explaining why I or anyone else should regard that fact as significant.[1]

An Unanswered Question: Recursivity and Science

And, since Mizrahi is obviously sensitive on the point, let me say that calling an argument a sophism is merely an objective description not a personal insult as Mizrahi seems to think. (Mizrahi, 21) Mizrahi still does not recognize the fallacy, perhaps a kinder, better word than sophism (mea culpa), he committed in his reply to my point concerning recursive knowledge. Let me try again. My point was simple. Any argument founded on the claimed quantitative superiority of science founders on the fact that recursive processes, any recursive processes, can produce an infinity of true propositions.

In response to this Mizrahi said that this is not a problem for scientism for we can reflect recursively on scientific propositions in the same manner. To this I responded by saying that this was true but irrelevant as this had nothing whatsoever to do with whether a proposition was scientific or not. Nor does his account of scientific explanation include reflexivity as a source of knowledge. Reflecting recursively on a scientific proposition is not the same as thinking scientifically.  His response his fallacious because it conflates two distinct processes.

This is why it does not matter in the least whether two people, a scientist or non-scientist, can produce an equal amount of knowledge by performing recursive acts in parallel. Neither are doing science. This perfectly obvious point is something Mizrahi claims he addresses in his replies to Brown (Mizrahi, 21) yet my examination of the passages he cites leaves me baffled for nothing in them touches remotely on the question of recursivity or explains how reflecting recursively on a scientific proposition is equivalent to uttering a scientific proposition as a scientist.

Since Mizrahi does not intend to reply any further I suppose I will just have to scratch my head on this one and bewail my own lack of native wit. Plus, as Mizrahi seems to set great store by citations and references even in informal spaces like a review and reply collective it is a little jarring to see HIS not quite panning out (more on this below however).[2]

Systems and Ideologies

Why does Dr. Mizrahi still think I am calling him a racist when I intended to speak only in terms of systemic and not personal racism (Mizrahi, 21-22)?   In a systemic and so intersectional context, non-white identity does not mean one cannot occupy a place of privilege. He still does not see the difference between an ad hominem attack and an ideological critique of scientism. (Mizrahi, 23) Lorraine Code and Helen Longino, among others, have explained how standard accounts of scientific method have (WITTINGLY OR NOT!!) excluded women as knowers and Mizrahi can consult their works if he is interested.[3]  He may also consult Edward Said on how pretensions to scientific ‘objectivity’ underwrite colonialism.

I, however, will use a different example, one closer to my own interests and experience. In the institution in which I teach a significant portion of the students are of indigenous Miq’maw heritage. They are, by and large, NOT interested in hearing that their elders convey a secondary and qualitatively inferior kind of knowledge when compared to western scientists. Now, you could say that this is simple perversity on their part; they should ‘man up’ and accept the gospel of weak scientism! Things are not however so simple.

It is idle to claim that the experience of colonial oppression is irrelevant because science is universal, objective and politically neutral. It is idle to claim that the elevation of scientific procedures to qualitative superiority has no social and political ramifications for those whose knowledge forms are thereby granted second class status. This is because the question of scientism is bound up with the question of authority.

The fact that Indigenous knowledge traditions are grounded in local knowledge, in traditional lore and in story means that on questions of importance to them indigenous peoples cannot speak. It means they have to listen to others who ‘know better’ because the propositions they utter have the form of science.[4]

Thus, whether intended or not, the elevation of scientific knowledge to superior status over indigenous knowledge elevates white settlers to authority over indigenous people and justifies the theft of their land and even of their children. Worse, indigenous people can see for themselves (because they are not blind) that this privileging of settler knowledge over their own is not benign. It is viciously exploitative and intended to keep indigenous peoples in a place of dependence and inferiority. Thus, Mizrahi’s facile assumption that scientism is ideologically innocent will not stand even cursory examination.

Partiality of Knowledge and the Limits of Learning

When I say that Mizrahi’s position is self-interested I am again simply pointing out a fact. If I were to write a paper arguing that the humanities are qualitatively superior to the sciences, deserved more funding than the sciences and that the hermeneutical practices of the humanities should be adopted by the sciences would Mizrahi not wonder if I was, in fact, being a little bit partial? Of course he would.

I, though, am not making that kind of argument, he is. I am not suggesting anyone is inferior to anyone; he is and as such I think it is perfectly legitimate to ask whether his position is tainted with bias. This is so especially as he has no much to say about the lack of ‘good faith’ in others.

On now to our unexpectedly long-lived example of Joyce scholars. Here I must thank Mizrahi for proving my point for me. Unaware that he is shooting his own argument in the foot he takes great pains to distinguish simplicity in scientific explanation from simplicity as an aesthetic quality.[5] He also distinguishes ‘accommodation’ (which the Joyce scholar seeks) from ‘novel prediction’ (which the scientist seeks). (Mizrahi, 25) It is indeed the case, as I myself asserted, that explanation in the humanities and in the sciences are related analogically not univocally. Terms from one domain do not immediately transfer directly to the other.

This is a perfect illustration of why scientific explanation is not the same as literary explanation. Simplicity is a desideratum for both forms of explanation but there is no answer to the question of whether general relativity is simpler than reader response theory for the obvious reason that different disciplines will parse the notion of simplicity differently.

But if this is so I ask again what makes a scientific theory qualitatively better than a critical reading of Joyce when they do not employ commensurate standards and have such fundamentally different aims? I ask again, what could ‘better’ possibly mean in this context? In what sense is a scientific theory simpler than a Joyce commentary if on Mizrahi’s own admission we are not dealing with univocal standards or senses of simplicity? In what sense is a scientific theory more coherent if we are not using ‘coherence’ in the same way in both domains?

Further I asked and ask again why the Joyce scholar even needs to make a novel prediction? Why is it a problem for his discipline if he does not use things he does not need? Further, Mizrahi resorts yet again to the canard that I am accusing him of saying the Joyce scholar does not produce knowledge as if this was even an answer to my question. (Mizrahi, 26)

Next, Scriabin. I think the best description of what my daughter did with the Prometheus chord is that she reverse engineered it. She worked backward from it to tell a story about how it came to be. Obviously this did not require any novel prediction about future Prometheus chords by future Scriabins. There is one Prometheus chord and it already exists. Further, the process by which it was created occurred once in the past.

Thus we are constructing an explanatory story about the past concerning a singular object not formulating a general law or making a testable prediction. This kind of story is used in all kinds of contexts. It is used here in music theory. It is used in those sciences concerned with past events. It is used by law enforcement to reconstruct a crime. Now, even if by some feat of prestidigitation one could contort such explanatory stories into the form of testable predictions this would be an after the fact rationalization not description of how actual people reason.

A World of Citations

Thus, let me emphasize once again that testability does not make science superior to on non-science for the simple reason that non-science does not typically need tests such as Mizrahi describes. Or, to put it another way testing is not employed in the same way in science and non-science so that if one says that, in some sense, the Joyce scholar ‘tests’ his ideas against the text one is speaking analogically not univocally as I attempted to point out in my previous reply. (Wills, 2018b, 38) Thus, Mizrahi’s claim about testability (Mizrahi, 28) is, yet again, beside the point.[6]

Now I turn to the minor objections. Dr. Mizrahi is upset that I have I have not cited the extensive literature on scientism. (Mizrahi, 18) Well Mizrahi has professed to show that science is superior to things like historiography and literary criticism even though he himself does not cite anything from those fields and shows no familiarity with what goes on in them.

Two can play at the rhetoric of citation and it is Mizrahi who claims that scientific procedures are better than non-scientific ones without making any direct comparison with the latter except for his cherished bugbear ‘armchair philosophy’. To return to the question of privilege, Mizrahi seems to assume that he is owed a deference he does not need to grant to others. As Latour says, citation is not accidental but essential to the rhetoric of an academic paper. (Latour; 1987, 30-62) Mizrahi’s use of the rhetoric of citation conveys the message that that his side has an epistemic privilege the other side does not: they are obliged to engage his literature but he is not obliged to engage theirs.

Again, Mizrahi accuses me of Eurocentric bias in citing Augustine and Aristotle (Mizrahi, 23) yet a glance at his own references does not reveal ANY citations from Shankara, Ashvaghosa, al Ghazzali, al Farabi, Ibn Sina, Ibn Rushd, Lao Tzu, Kung Fu Tzu, or any other thinker outside the western tradition. Miizrahi’s own citation list betrays the very story he is trying to tell about mine!  Finally, in a somewhat involved passage he responds to the charge that he vacillates between Weak and Strong Scientism by citing the full text of a passage from one of his replies to Brown. (Mizrahi, 24) I don’t why he does this because his words say the exact same thing even when put in this larger context.

He reports that certain philosophers and scientists think of knowledge as “the scholarly work or research produced in scientific fields of study studies, as opposed to non-scientific study.” He then states, directly, that he follows this view. (Mizrahi, 24) This does indeed look like vacillation between weak and strong scientism.

However, I will not hammer him on one passage for what might, after all, be an unintentional slip or loose phrasing. If he says his position is weak scientism and weak scientism only then I take him at his word.

Conclusion

I will reiterate again the one basic reason why I think weak scientism is unconvincing and that is that it seems to be an exercise in bare arithmetic. Is there more scientific research than non-scientific? Well, more is better! Does science have 4 of the features of good explanation and history only 3? Science wins! This purely arithmetic procedure completely ignores the contexts in which different scholars work and how they reach their conclusions.  I conclude by saying what I said in my first reply: that Mizrahi’s Weak Scientism is the mountain that gave birth to the proverbial mouse.

Contact details: bwills@grenfell.mun.ca

References

Bohannon, John. “Hate Journal Impact Factors? New Study Gives You One More Reason.” Science Magazine. 6 July 2016. Retrieved from: http://www.sciencemag.org/news/2016/07/hate-journal-impact-factors-new-study-gives-you-one-more-reason.

Mizrahi, Moti. “What’s So Bad About Scientism?” Social Epistemology 31, no. 4 (2017): 351-367.

Mizrahi, Moti. “Weak Scientism Defended Once More.” Social Epistemology Review and Reply Collective 7, no. 6 (2018): 41-50.

Van Wesel, Maarten; Sally Wyatt, and Jeroen ten Haaf. “What A Difference a Colon Makes: How Superficial Factors Influence Subsequent Citation.” Scientometrics 98, no. 3 (2014): 1601-1615.

Wills, Bernard. “On the Limits of Any Scientism.” Social Epistemology Review and Reply Collective 7, no. 7 (2018): 34-39.

Wills, Bernard. “Why Mizrahi Needs to Replace Weak Scientism With an Even Weaker Scientism.” Social Epistemology Review and Reply Collective 7, no. 5 (2018): 18-24.

[1] Mizrahi is not going to like this but some have questioned whether impact ratings and other quantitative metrics have the significance sometimes claimed for them. See Callaway, as well as Van Wesel, Wyatt,  ten Haaff, and Bohanon. Indeed, Mizrahi seems to have internalized the standards of the university’s corporate masters (with their spurious emphasis on external metrics) to an uncritical and disturbing degree.

[2] Is Mizrahi claiming in these passages that ‘scientific knowledge’ is any knowledge that happens to be produced by a scientist as ‘practitioner’ in a field (Mizrahi 21) whether accidental to her practice or not? If so, he has yet again defended his thesis at the cost of making it trivial.

[3] He may begin with the Stanford Encyclopedia of Philosophy if he likes.

[4]  See D. Simmonds on this point (addressing an anti-indigenous activist notorious in Canada): “My particular interest here is the way in which science has been reified by Widdowson and Howard and used to legitimate state decision-making on behalf of oppressed peoples. Science is counterposed to indigenous traditional knowledge, which by way of a children’s parable (The Emperor’s New Clothes) is denounced as mere superstition in the service of a corrupt “aboriginal industry.” The state is called upon to harness scientific rationalism in the old colonial interest of “civilizing the savages.” In the words of Widdowson and Howard, “It is not clear how the remnants of Neolithic culture that are inhibiting this development can be addressed without intensive government planning and intervention” (252).

[5] Simplicity as I use it here does not refer to ‘simple language’ but to the economy of a work’s design. I admit though that I should have distinguished between two kinds of simplicity here. The simplicity of the work itself and the simplicity of the critic’s exposition of the work which of course formally differ. It is the latter case that more closely resembles the simplicity of a scientific theory though if Mizrahi wants to deny they are identical that is entirely to my own purpose for I deny this as well.

[6] This speaks to the overall banality of Mizrahi’s thesis. He tells us that the best explanation is one “explains the most, leaves out the least, is consistent with background knowledge, is the least complicated, and yields independently testable predictions.” (Mizrahi, 28) He then adds “Wills seems to grant that “unity, simplicity and coherence are good making properties of explanations, but not testability. But why not testability?”. (Mizrahi, 28) Well I have said many times why not. Testability as Mizrahi defines it is not relevant to all inquiries. It is not even relevant to all scientific inquiries. ‘Testing’ can take different forms that resemble each other analogically not univocally. I don’t know how many different ways I can say this: the test of a thesis on metaphysics is elenchic. The test of a thesis about Joyce is a close examination of his texts. The test of an archeological claim is the examination of artefacts. Mizrahi’s entire argument boils down to the claim that science beats non-science 4 to 3! Yet clearly Mizrahi has tilted the field by asking non-science to conform to a standard external to it and applied arbitrarily. Unity, coherence, testability and so on are resemblance terms that cash out differently in different inquiries.

Author Information: Robin McKenna, University of Liverpool, r.j.mckenna@liverpool.ac.uk.

McKenna, Robin. “McBride on Knowledge and Justification.” Social Epistemology Review and Reply Collective 7, no. 9 (2018): 53-59.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-417

Image by Ronan Shahnav via Flickr / Creative Commons

 

I would like to thank the editors of the Social Epistemology Review and Reply Collective for giving me the opportunity to review Mark McBride’s rich and rewarding book. To begin, I will give a—fairly high-level—overview of its contents. I will then raise some concerns and make some (mildly) critical comments.

Overview

The book is split into two parts. Part 1 concerns the issue of basic knowledge (and justification), whereas the second concerns (putative necessary) conditions on knowledge (specifically, conclusive reasons, sensitivity and safety conditions). We can start with Part 1. As McBride defines it, basic knowledge is “knowledge (or justification) which is immediate, in the sense that one’s justification for the known proposition doesn’t rest on any justification for believing other propositions” (p. 1).

Two central issues in Part 1 are (i) what, exactly, is wrong with Moore’s “proof” of the external world (Chapter 1) (ii) what, exactly, is wrong with inferences that yield “easy knowledge” (Chapters 2-3). Take these arguments, which for ease of reference I’ll call MOORE and EASY-K respectively:

MOORE:

(Visual appearance as of having hands).
1-M. I have hands.
2-M. If I have hands, an external world exists.
3-M. An external world exists.

EASY-K:

(Visual appearance as of a red table).
1-EK. The table is red.
2-EK. If the table is red, then it is not white with red lights shining on it.
3-EK. The table is not white with red lights shining on it.

It seems like a visual appearance as of having hands can give one knowledge of 1-M, and 2-M seems to be knowable a priori. But it seems wrong to hold that one can thereby come to know 3-M. (And mutatis mutandis for EASY-K and 3-EK).

I want to single out three of McBride’s claims about MOORE and EASY-K. First, it is commonly taken that “dogmatist” responses to MOORE (such as Pryor 2000) are at a disadvantage with respect to “conservative” responses (such as Wright 2004). The dogmatist holds that having a visual appearance as of hands provides immediate warrant for 1-M, whereas the conservative holds that one can have warrant for 1-M only if one has a prior entitlement to accept 3-M. Thus the dogmatist seems forced to accept that warrant can “transmit” from the premises of MOORE to the conclusion, whereas the conservative can deny that warrant transmission occurs.

In Chapter 1 McBride turns this on its head. First, he argues that, while a conservative such as Crispin Wright can maintain that the premises of MOORE don’t transmit “non-evidential” warrant to the conclusion, he must allow that “evidential” warrant does transmit from the premises to the conclusion. Second, he argues that Wright cannot avail himself of what McBride (following Davies 2004) takes to be a promising diagnosis of the real problem with MOORE. According to Martin Davies, MOORE is inadequate because it is of no use in the epistemic project of settling the question whether the external world exists. But, for Wright, there can be no such project, because the proposition that the external world exists is the “cornerstone” on which all epistemic projects are built.

Second, in Chapter 3 McBride seeks to show that the dogmatist can supplement Davies’ account of the problem with Moore’s proof in order to diagnose the problem with EASY-K. According to McBride, EASY-K is problematic not just in that it is of no use in settling the question whether the table is not white with red lights shining on it, but also in that there are all sorts of ways in which one could settle this question (e.g. by investigating the lighting sources surrounding the table thoroughly).

Thus, EASY-K is problematic in a way that MOORE isn’t: while one could avail oneself of a better argument for the conclusion of EASY-K, it is harder to see what sort of argument could improve on MOORE.

Third, while Part 1 is generally sympathetic to the dogmatist position, Chapter 5 argues that the dogmatist faces a more serious problem. The reader interested in the details of the argument should consult Chapter 5. Here, I just try to explain the gist. Say you endorse a closure principle on knowledge like this:

CLOSURE: Necessarily, if S knows p, competently deduces q from p, and thereby comes to believe q, while retaining knowledge of p throughout, then S knows q (p. 159).

It follows that, if one comes to know 1-EK (the table is red) by having an appearance as of a red table, then competently deduces 3-EK (the table is not white with red lights shining on it) from 1-EK while retaining knowledge of 1-EK, then one knows 3-EK. But—counter-intuitively—having an appearance as of a red table can lower the credence one ought to have in 3-EK (see pp. 119-20 for the reason why).

It therefore seems inarguable that, if you are in a position to know 3-EK after having the appearance, you must have been in a position to know the 3-EK prior to the appearance. So it seems like the conservative position must be right after all. In order for your appearance as of a red table to furnish knowledge that there is a red table you must have been in a position to know that the table was not white with red lights shining on it prior to having the appearance as of a red table.

The second part of McBride’s book concerns putative (necessary) conditions on knowledge, in particular conclusive reasons (Chapter 6), sensitivity (Chapter 7) and safety (Chapter 8). McBride dedicates a chapter to each condition; the book finishes with a (brief) application of safety to legal knowledge (Chapter 9). While most epistemologists tend to argue that either sensitivity or (exclusive) safety are a (necessary) condition on knowledge, McBride provides a (qualified) defense of both.

In the case of sensitivity, this is in part because, if sensitivity were a condition on knowledge, then—as Nozick (1981) famously held—CLOSURE would be false, and so the argument against dogmatism (about knowledge) in Chapter 5 would be disarmed. Because of the centrality of sensitivity to the argument in Part 1, and because the chapters on conclusive reasons and sensitivity revolve around similar issues, I focus on sensitivity in what follows.

Here is an initial statement of sensitivity:

SENSITIVITY: S knows p only if S sensitively believes p, where S sensitively believes p just in case, were p false, S would not believe p (p. 160).

Chapter 7 (on sensitivity) is largely concerned with rebutting an objection from John Hawthorne (2004) to the effect that the sensitivity theorist must also reject these two principles:

EQUIVALENCE: If you know a priori that p and q are equivalent and you know p, then you are in a position to know q.

DISTRIBUTION: If one knows p and q, then one is in a position to know p and to know q.

Suppose I have an appearance as of a zebra. So I know:

(1) That is a zebra.

By EQUIVALENCE I can know:

(2) That is a zebra and that is not a cleverly disguised mule.

So by DISTRIBUTION I can know:

(3) That is not a cleverly disguised mule.

But, by SENSITIVITY, while I can know (1), I can’t know (3) because, if I were looking at a cleverly disguised mule, I would still believe I was looking at a zebra. Hawthorne concludes that the sensitivity theorist must deny a range of plausible principles, not just CLOSURE.

McBride’s basic response is that, while SENSITIVITY is problematic as stated, it can be modified in such a way that the sensitivity-theorist can deny EQUIVALENCE but keep DISTRIBUTION. More importantly, this rejection of EQUIVALENCE can be motivated on the grounds that initially motivate SENSITIVITY. Put roughly, the idea is that simple conjunctions like (4) already cause problems for SENSITIVITY:

(4) I have a headache and I have all my limbs.

Imagine you form the belief in (4) purely from your evidence of having a headache (and don’t worry about how this might be possible). While you clearly don’t know (4), your belief does satisfy SENSITIVITY, because, if (4) were false, you wouldn’t still believe it (if you didn’t have a headache, you wouldn’t believe you did, and so you wouldn’t believe (4)).

The underlying problem is that SENSITIVITY tells you to go the nearest possible world in which the relevant belief is false and asks what you believe there, but a conjunctive belief is false so long as one of the conjuncts is false, and it might be that one of the conjuncts is false in a nearby possible world, whereas the other is false in a more distant possible world. So the sensitivity theorist needs to restrict SENSITIVITY to atomic propositions and add a new condition for conjunctive propositions:

SENSITIVITY*: If p is a conjunctive proposition, S knows p only if S believes each of the conjuncts of p sensitively (p. 167).

If we make this modification, the sensitivity theorist now has an independent reason to reject EQUIVALENCE, but is free to accept DISTRIBUTION.

Critical Discussion

While this only touches on the wealth of topics discussed in McBride’s book, I will now move on to the critical discussion. I will start by registering two general issues about the book. I will then develop two criticisms in a little more length, one for each part of the book.

First, while the book makes compelling reading for those already versed in the literatures on transmission failure, easy knowledge and modal conditions on knowledge, the central problematics are rarely motivated at any length. Moreover, while McBride does draw numerous (substantive) connections between the chapters, the book lacks a unifying thesis. All this to say: This is maybe more of a book for the expert than the novice. But the expert will find a wealth of interesting material to chew over.

Second, readers of the Collective might find the individualism of McBride’s approach striking. McBride is almost exclusively concerned with the epistemic statuses of individuals’ beliefs, where those beliefs are formed through simple processes like perception and logical inference. The one part of the book that does gesture in a more social direction (McBride’s discussion of epistemic projects, and the dialectical contexts in which they are carried out) is suggestive, but isn’t developed in much detail.

Turning now to more substantive criticisms, in Part 1 McBride leans heavily on Davies’ solution to the problem with MOORE. I want to make two comments here. First, it is natural to interpret Davies’ solution as an inchoate form of contextualism (DeRose 1995; Lewis 1996): whether MOORE (and EASY-K?) transmits warrant to its conclusion depends on the context in which one runs the inference, in particular, the project in which one is engaged.

This raises a host of questions. For example: does McBride hold that, if we keep the context (project) fixed, no transmission failure occurs? That is: if we’re working with the (easier) project of deciding what to believe, does an instance of MOORE transmit warrant from premises to conclusion? If so, then if we’re working with the (harder) project of settling the question, does an instance of MOORE fail to transmit warrant? (This would fit with the more general contextualist line in response to the skeptical problem, so this is only a request for clarification).

Second, and more importantly, we need to distinguish between the project of fully settling the question whether p and the project of partially settling the question whether p. Let’s grant McBride (and Davies) that someone who runs through an instance of MOORE has not fully settled the question whether there is an external world. But why think that—at least by the dogmatist’s lights—they haven’t partially settled the question? If dogmatism is true, then having the appearance as of a hand provides immediate warrant for believing that one has a hand, and so, via MOORE, for believing that there is an external world.

McBride (like many others) finds this conclusion unpalatable, and he invokes the distinction between the project of deciding what to believe and the project of settling the question in order to avoid it. But this distinction is overly simplistic. We can settle questions for different purposes, and with different degrees of stability (cf. “the matter is settled for all practical purposes”). The dogmatist seems forced to allow that MOORE is perfectly good for settling the question of whether there is an external world for a range of projects, not just one.

(I have a parallel worry about the solution to the problem of easy knowledge. Let’s grant McBride that one problem with EASY-K is that there are far better ways of trying to establish that the table is not white but bathed in red light. But why think that—at least by the dogmatist’s lights—it isn’t a way of trying to establish this? To point out that there are better ways of establishing a conclusion is not yet to show that this particular way is no way at all of establishing the conclusion).

Finally, in his response to Hawthorne’s objection to the sensitivity theorist McBride is at pains to show that his modification of SENSITIVITY isn’t ad hoc. To my mind, he does an excellent job of showing that the sensitivity theorist should reject EQUIVALENCE for reasons entirely independent of Hawthorne’s objection.

This suggests (at least to me) that the problem is not one of ad hocness, but rather that sensitivity theorists are forced to endorse a wide range of what Keith DeRose (1995) calls “abominable conjunctions” (cf. “I know that I have hands, but I don’t know that I’m not a handless brain in a vat”). DeRose’s own response to this problem is to embed something like SENSITIVITY in a contextualist theory of knowledge attributions. DeRose proposes the following “rule”:

Rule of Sensitivity: When it’s asserted that S knows (or doesn’t know) p, then, if necessary, enlarge the sphere of epistemically relevant worlds so that it at includes the closest worlds in which p is false (cf 1995, 37).

His idea is that, when the question of whether S knows p becomes a topic of conversation, we expand the range of worlds in which S’s belief must be sensitive. Imagine I assert “I know that I have hands”. In order for this assertion to be true, it must be the case that, if I didn’t have hands, I wouldn’t believe that I did.

But now imagine I assert “I know that I’m not a handless brain in a vat”. In order for this new assertion to be true, it must be the case that, if I were a handless brain in a vat, I wouldn’t believe that I wasn’t. Plausibly, this will not be the case, so I can’t truly assert “I know that I’m not a handless brain in a vat”. But no abominable conjunction results, because I can no longer truly assert “I know that I have hands” either.

My suggestion is that, if McBride were to adopt DeRose’s contextualist machinery, he would not only have a way of responding to the problem of abominable conjunctions, but also an interesting modification to DeRose’s “rule of sensitivity”.

For note that DeRose’s rule seems subject to the same problem McBride sees with SENSITIVITY: when I assert “I have a headache and I have all my limbs” we only need to expand the range of worlds to include worlds in which I don’t have a headache, and so my assertion will remain true in the updated context created by my assertion. Further, adopting this suggestion would furnish another link between Part 1 and Part 2: solving the problem of basic knowledge and formulating a satisfactory sensitivity condition both require adopting a contextualist theory of knowledge attributions.

Contact details: r.j.mckenna@liverpool.ac.uk

References

Davies, Martin. 2004. ‘Epistemic Entitlement, Warrant Transmission and Easy Knowledge’. Aristotelian Society Supplementary Volume 78 (1): 213–245.

DeRose, Keith. 1995. ‘Solving the Skeptical Problem’. Philosophical Review 104 (1): 1–52.

Hawthorne, John. 2004. Knowledge and Lotteries. Oxford University Press.

Lewis, David. 1996. ‘Elusive Knowledge’. Australasian Journal of Philosophy 74 (4): 549–67.

Nozick, Robert. 1981. Philosophical Explanations. Harvard University Press.

Pryor, James. 2000. ‘The Skeptic and the Dogmatist’. Noûs 34 (4): 517–549.

Wright, Crispin. 2004. ‘Warrant for Nothing (and Foundations for Free)?’ Aristotelian Society Supplementary Volume 78 (1): 167–212.

Author Information: Moti Mizrahi, Florida Institute of Technology, mmizrahi@fit.edu.

Mizrahi, Moti. “Why Scientific Knowledge Is Still the Best.” Social Epistemology Review and Reply Collective 7, no. 9 (2018): 18-32.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-40I

For context, see also:

Image by Specious Reasons via Flickr / Creative Commons

 

It is common knowledge among scholars and researchers that the norms of academic research dictate that one must enter an academic conversation by properly acknowledging, citing, and engaging with the work done by other scholars and researchers in the field, thereby showing that a larger conversation is taking place.[1] See, for example, Graff and Birkenstein (2018, 1-18) on “entering the conversation.” Properly “entering the conversation” is especially important when one aims to criticize the work done by other scholars and researchers in the field.

In my previous reply to Bernard Wills’ attack on Weak Scientism (Wills 2018a), I point out that Wills fails in his job as a scholar who aims to criticize work done by other scholars and researchers in the field (Mizrahi 2018b, 41), since Wills does not cite or engage with the paper in which I defend Weak Scientism originally (Mizrahi 2017a), the very thesis he seeks to attack. Moreover, he does not cite or engage with the papers in my exchange with Christopher Brown (Mizrahi 2017b; 2018a), not to mention other works in the literature on scientism.

In his latest attack, even though he claims to be a practitioner of “close reading” (Wills 2018b, 34), it appears that Wills still has not bothered to read the paper in which I defend the thesis he seeks to attack (Mizrahi 2017a), or any of the papers in my exchange with Brown (Mizrahi 2017b; 2018a), as evidenced by the fact that he does not cite them at all. To me, these are not only signs of lazy scholarship but also an indication that Wills has no interest in engaging with my arguments for Weak Scientism in good faith. For these reasons, this will be my second and final response to Wills. I have neither the time nor the patience to debate lazy scholars who argue in bad faith.

On the Quantitative Superiority of Scientific Knowledge

In response to my empirical data on the superiority of scientific knowledge over non-scientific knowledge in terms of research output and research impact (Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-22; Mizrahi 2018b, 42-44), Wills (2018b, 34) claims that he has “no firm opinion at all as to whether the totality of the sciences have produced more ‘stuff’ than the totality of the humanities between 1997 and 2017 and the reason is that I simply don’t care.”

I would like to make a few points in reply. First, the sciences produce more published research, not just “stuff.” Wills’ use of the non-count noun ‘stuff’ is misleading because it suggests that research output cannot be counted or measured. However, research output (as well as research impact) can be counted and measured, which is why we can use this measure to determine that scientific research (or knowledge) is better than non-scientific research (or knowledge).

Second, my defense of Weak Scientism consists of a quantitative argument and a qualitative argument, thereby showing that scientific knowledge is superior to non-scientific knowledge both quantitatively and qualitatively, which are the two ways in which one thing can be said to be better than another (Mizrahi 2017a, 354). If Wills really does not care about the quantitative argument for Weak Scientism, as he claims, then why is he attacking my defense of Weak Scientism at all?

After all, showing that “scientific knowledge is [quantitatively] better – in terms of research output (i.e. more publications) and research impact (i.e. more citations) – than non-scientific knowledge” is an integral part of my defense of Weak Scientism (Mizrahi 2017a, 358). To know that, however, Wills would have to read the paper in which I make these arguments for Weak Scientism (Mizrahi 2017a). In his (2018a) and (2018b), I see no evidence that Wills has read, let alone read closely, that paper.

Third, for someone who says that he “simply [doesn’t] care” about quantity (Wills 2018b, 34), Wills sure talks about it a lot. For example, Wills claims that a “German professor once told [him] that in the first half of the 20th Century there were 40,000 monographs on Franz Kafka alone!” (Wills 2018a, 18) and that “Shakespeare scholars have all of us beat” (Wills 2018a, 18). Wills’ unsupported claims about quantity turn out to be false, of course, as I show in my previous reply (Mizrahi 2018b, 42-44). Readers will notice that Wills does not even try to defend those claims in his (2018b).

Fourth, whether Wills cares about quantity or has opinions on the matter is completely beside the point. With all due respect, Wills’ opinions about research output in academic disciplines are worthless, especially when we have data on research output in scientific and non-scientific disciplines. The data show that scientific disciplines produce more research than non-scientific disciplines and that scientific research has a greater impact than non-scientific research (Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-22; Mizrahi 2018b, 42-44).

Wills (2018b, 35) thinks that the following is a problem for Weak Scientism: “what if it were true that Shakespeare scholars produced more papers than physicists?” (original emphasis) Lacking in good arguments, as in his previous attack on Weak Scientism, Wills resorts to making baseless accusations and insults, calling me “an odd man” for thinking that literature would be better than physics in his hypothetical scenario (Wills 2018b, 35). But this is not a problem for Weak Scientism at all and there is nothing “odd” about it.

What Wills fails to understand is that Weak Scientism is not supposed to be a necessary truth. That is, Weak Scientism does not state that scientific knowledge must be quantitatively and qualitatively better than non-scientific knowledge. Rather, Weak Scientism is a contingent fact about the state of academic research. As a matter of fact, scientific disciplines produce better research than non-scientific disciplines do.

Moreover, the data we have (Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-22; Mizrahi 2018b, 42-44) give us no reason to think that these trends in research output and research impact are likely to change any time soon. Of course, if Wills had read my original defense of Weak Scientism (Mizrahi 2017a), and my replies to Brown, he would have known that I have discussed all of this already (Mizrahi 2017b, 9-10; 2018a, 9-13).

Likewise, contrary to what Wills (2018b, 36, footnote 2) seems to think, there is nothing odd about arguing for a thesis according to which academic research produced by scientific disciplines is superior to academic research produced by non-scientific disciplines, “while leaving open the question whether non-scientific knowledge outside the academy may be superior to science” (original emphasis). If Wills were familiar with the literature on scientism, he would have been aware of the common distinction between “internal scientism” and “external scientism.”

See, for example, Stenmark’s (1997, 16-18) distinction between “academic-internal scientism” and “academic-external scientism” as well as Peels (2018, 28-56) on the difference between “academic scientism” and “universal scientism.” Again, a serious scholar would have made sure that he or she is thoroughly familiar with the relevant literature before attacking a research paper that aims to make a contribution to that literature (Graff and Birkenstein 2018, 1-18).

Wills also seems to be unaware of the fact that my quantitative argument for Weak Scientism consists of two parts: (a) showing that scientific research output is greater than non-scientific research output, and (b) showing that the research impact of scientific research is greater than that of non-scientific research (Mizrahi 2017a, 356-358). The latter is measured, not just by publications, but also by citations. Wills does not address this point about research impact in his attacks on Weak Scientism. Since he seems to be proud of his publication record, for he tells me I should search for his published papers on Google (Wills 2018b, 35), let me to illustrate this point about research impact by comparing Wills’ publication record to a colleague of his from a science department at his university.

According to Google Scholar, since completing his doctorate in Religious Studies at McMaster University in 2003, Wills has published ten research articles (excluding book reviews). One of his research articles was cited three times, and three of his research articles were cited one time each. That is six citations in total.

On the other hand, his colleague from the Physics program at Memorial University, Dr. Svetlana Barkanova, has published 23 research articles between 2003 and 2018, and those articles were cited 53 times. Clearly, in the same time, a physicist at Wills’ university has produced more research than he did (130% more research), and her research has had a greater impact than his (783% more impact). As I have argued in my (2017a), this is generally the case when research produced by scientific disciplines is compared to research produced by non-scientific disciplines (Table 1).

Table 1. H Index by subject area, 1999-2018 (Source: Scimago Journal & Country Rank)

H Index
Physics 927
Psychology 682
Philosophy 161
Literature 67

Reflecting on One’s Own Knowledge

In his first attack on Weak Scientism, Wills (2018a, 23) claims that one “can produce a potential infinity of knowledge simply by reflecting recursively on the fact of [one’s] own existence.” In response, I pointed out that Wills (2018a, 23) himself admits that this reflexive procedure applies to “ANY fact” (original capitalization), which means that it makes no difference in terms of the quantity of knowledge produced in scientific versus non-scientific disciplines.

As I have come to expect from him, Wills (2018b, 35) resorts to name-calling again, rather than giving good arguments, calling my response “sophism,” but he seems to miss the basic logical point, even though he admits again that extending one’s knowledge by reflexive self-reflection “can be done with any proposition at all” (Wills 2018b, 35). Of course, if “it can be done with any proposition at all” (Wills 2018b, 35; emphasis added), then it can be done with scientific propositions as well, for the set of all propositions includes scientific propositions.

To illustrate, suppose that a scientist knows that p and a non-scientist knows that q. Quantitatively, the amount of scientific and non-scientific knowledge is equal in this instance (1 = 1). Now the scientist reflects on her own knowledge that p and comes to know that she knows that p, i.e., she knows that Kp. Similarly, the non-scientist reflects on her knowledge that q and comes to know that she knows that q, i.e., she knows that Kq. Notice that, quantitatively, nothing has changed, i.e., the amount of scientific versus non-scientific knowledge is still equal: two items of scientific knowledge (p and Kp) and two items of non-scientific knowledge (q and Kq).

Wills might be tempted to retort that p may be an item of scientific knowledge but Kp is not because it is not knowledge that is produced by scientific procedures. However, if Wills were to retort in this way, then it would be another indication of sloppy scholarship on his part. In my original paper (Mizrahi 2017a, 356), and in my replies to Brown (Mizrahi 2017b, 12-14; Mizrahi 2018a, 14-15), I discuss at great length my characterization of disciplinary knowledge as knowledge produced by practitioners in the field. I will not repeat those arguments here.

Baseless Accusations of Racism and Colonialism

After raising questions about whether I am merely rationalizing my “privilege” (Wills 2018a, 19), Wills now says that his baseless accusations of racism and colonialism are “not personal” (Wills 2018b, 35). His concern, Wills (2018b, 35) claims, is “systemic racism” (original emphasis). As a white man, Wills has the chutzpah to explain (or white-mansplain, if you will) to me, an immigrant from the Middle East, racism and colonialism.

My people were the victims of ethnic cleansing and genocide, lived under British colonial rule, and are still a persecuted minority group. Since some of my ancestors died fighting the British mandate, I do not appreciate using the term ‘colonialism’ to describe academic disputes that are trifle in comparison to the atrocities brought about by racism and colonialism.

Perhaps Wills should have used (or meant to use) the term ‘imperialism’, since it is sometimes used to describe the expansion of a scientific theory into new domains (Dupré 1994). This is another sign of Wills’ lack of familiarity with the literature on scientism. Be that as it may, Wills continues to assert without argument that my “defense of weak-scientism is ideologically loaded,” that it implies “the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers,” and that I make “hegemonic claims for science from which [I] stand to benefit” (Wills 2018b, 36).

In response, I must admit that I have no idea what sort of “ideologies” Weak Scientism is supposed to be loaded with, since Wills does not say what those are. Wills (2018b, 36) asserts without argument that “the position [I] take on scientism has social, political and monetary implications,” but he does not specify those implications. Nor does he show how social and political implications (whatever those are) are supposed to follow from the epistemic thesis of Weak Scientism (Mizrahi 2017a, 353). I am also not sure why Wills thinks that Weak Scientism implies “the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers” (Wills 2018b, 36), since he provides no arguments for these assertions.

Of course, Weak Scientism entails that there is non-scientific knowledge (Mizrahi 2018b, 41). If there is non-scientific knowledge, then there are non-scientific knowers. In that case, on Weak Scientism, non-scientists are not excluded from “the circle of knowers.” In other words, on Weak Scientism, the circle of knowers includes non-scientists, which can be women and people of color, of course (recall Dr. Svetlana Barkanova). Contrary to what Wills seems to think, then, Weak Scientism cannot possibly entail “the exclusion of various others such as women or indigenous peoples from the socially sanctioned circle of knowers” (Wills 2018b, 36).

In fact, if it is “the exclusion of various others” that Wills (2018b, 36) is genuinely concerned about, then he is undoubtedly aware of the fact that it is precisely white men like him who are guilty of systematically excluding “various others,” such as women (Paxton et al. 2012) and people of color (Botts et al. 2014), from the academic discipline of philosophy (American Philosophical Association 2014). As anyone who is familiar with the academic discipline of philosophy knows, “philosophy faces a serious diversity problem” (Van Norden 2017b, 5). As Amy Ferrer (2012), Executive Director of the American Philosophical Association (APA), put it on Brian Leiter’s blog, Leiter Reports:

philosophy is one of the least diverse humanities fields, and indeed one of the least diverse fields in all of academia, in terms of gender, race, and ethnicity. Philosophy has a reputation for not only a lack of diversity but also an often hostile climate for women and minorities (emphasis added).

In light of the lack of diversity in academic philosophy, some have gone as far as arguing that contemporary philosophy is racist and xenophobic; otherwise, argues Bryan Van Norden (2017a), it is difficult to explain “the fact that the rich philosophical traditions of China, India, Africa, and the Indigenous peoples of the Americas are completely ignored by almost all philosophy departments in both Europe and the English-speaking world.”

In fact, Wills’ attacks on Weak Scientism illustrate how white men like him attempt to keep philosophy white and “foreigner-free” (Cherry and Schwitzgebel 2016). They do so by citing and discussing the so-called “greats,” which are almost exclusively Western men. Citations are rather scarce in Wills’ replies, but when he cites, he only cites “the greats,” like Aristotle and Augustine (see Schwitzgebel et al. 2018 on the “Insularity of Anglophone Philosophy”).

As for his claim that I “stand to benefit” (Wills 2018b, 36) from my defense of Weak Scientism, I have no idea what Wills is talking about. I had no idea that History and Philosophy of Science (HPS) and Science and Technology Studies (STS) “can often assert hegemony over other discourses” (Wills 2018b, 36). I bet this will come as a surprise to other HPS and STS scholars and researchers. They will probably be shocked to learn that they have that kind of power over other academic disciplines.

More importantly, even if it were true that I “stand to benefit” (Wills 2018b, 36) from my defense of Weak Scientism, nothing about the merit of my defense of Weak Scientism would follow from that. That is, to argue that Weak Scientism must be false because I stand to benefit from it being true is to argue fallaciously. In particular, it is an informal fallacy of the circumstantial ad hominem type known as “poisoning the well,” which “alleges that the person has a hidden agenda or something to gain and is therefore not an honest or objective arguer” (Walton and Krabbe 1995, 111).

It is as fallacious as arguing that climate change is not real because climate scientists stand to benefit from climate research or that MMR vaccines are not safe (e.g., cause autism) because medical researchers stand to benefit from such vaccines (Offit 2008, 213-214). These are the sort of fallacious arguments that are typically made by those who are ignorant of the relevant science or are arguing in bad faith.

In fact, the same sort of fallacious reasoning can be used to attack any scholar or researcher in any field of inquiry whatsoever, including Wills. For instance, just as my standing to benefit from defending Weak Scientism is supposed to be a reason to believe that Weak Scientism is false, or Paul Offit’s standing to gain from MMR vaccines is supposed to be a reason to believe that such vaccines are not safe, Wills’ standing to benefit from his attacks on Weak Scientism (e.g., by protecting his position as a Humanities professor) would be a reason to believe that his attacks on Weak Scientism are flawed.

Indeed, the administrators at Wills’ university would have a reason to dismiss his argument for a pay raise on the grounds that he stands to benefit from it (Van Vleet 2011, 16). Of course, such reasoning is fallacious no matter who is the target. Either MMR vaccines are safe and effective or they are not regardless of whether Offit stands to benefit from them. Climate change is real whether climate scientists stand to benefit from doing climate research. Likewise, Weak Scientism is true or false whether or not I stand to benefit from defending it.

Image by Maia Valenzuela via Flickr / Creative Commons

 

Revisiting the Joyce Scholar

Wills (2018b, 36) returns to his example of the Joyce scholar as an example of non-scientific knowledge “that come[s] from an academic context.” As I have already pointed out in my previous reply (Mizrahi 2018b, 41-42), it appears that Wills fails to grasp the difference between Strong Scientism and Weak Scientism. Only Strong Scientism rules out knowledge that is not scientific. On Weak Scientism, there is both scientific and non-scientific knowledge. Consequently, examples of non-scientific knowledge from academic disciplines other than scientific ones do not constitute evidence against Weak Scientism.

Relatedly, Wills claims to have demonstrated that I vacillate between Strong Scientism and Weak Scientism and cites page 22 of his previous attack (Wills 2018a, 22). Here is how Wills (2018a, 22) argues that I vacillate between Strong Scientism and Weak Scientism:

Perhaps it is the awareness of such difficulties that leads Mizhari [sic] to his stance of ‘Weak Scientism’. It is not a stance he himself entirely sticks to. Some of his statements imply the strong version of scientism as when he tells us the [sic] knowledge is “the scholarly work or research produced in scientific fields of study, such as the natural sciences, as opposed to non-scientific fields, such as the humanities” [Mizrahi 2018a, 22].

However, the full passage Wills cites as evidence of my vacillation between Strong Scientism and Weak Scientism is from the conclusion of my second reply to Brown (Mizrahi 2018a) and it reads as follows:

At this point, I think it is quite clear that Brown and I are talking past each other on a couple of levels. First, I follow scientists (e.g., Weinberg 1994, 166-190) and philosophers (e.g., Haack 2007, 17-18 and Peels 2016, 2462) on both sides of the scientism debate in treating philosophy as an academic discipline or field of study, whereas Brown (2017b, 18) insists on thinking about philosophy as a personal activity of “individual intellectual progress.” Second, I follow scientists (e.g., Hawking and Mlodinow 2010, 5) and philosophers (e.g., Kidd 2016, 12-13 and Rosenberg 2011, 307) on both sides of the scientism debate in thinking about knowledge as the scholarly work or research produced in scientific fields of study, such as the natural sciences, as opposed to non-scientific fields of study, such as the humanities, whereas Brown insists on thinking about philosophical knowledge as personal knowledge.

Clearly, in this passage, I am talking about how ‘knowledge’ is understood in the scientism debate, specifically, that knowledge is the published research or scholarship produced by practitioners in academic disciplines (see also Mizrahi 2017a, 353). I am not saying that non-scientific disciplines do not produce knowledge. How anyone can interpret this passage as evidence of vacillation between Strong Scientism and Weak Scientism is truly beyond me. To me, this amounts to “contextomy” (McGlone 2005), and thus further evidence of arguing in bad faith on Wills’ part.

Wills also misunderstands, as in his previous attack on Weak Scientism, the epistemic properties of unity, coherence, simplicity, and testability, and their role in the context of hypothesis testing and theory choice. For he seems to think that “a masterful exposition of Portrait of the Artist as Young Man will show the unity, coherence and simplicity of the work’s design to the extent that these are artistically desired features” (Wills 2018b, 36). Here Wills is equivocating on the meaning of the terms ‘unity’, ‘coherence’, and ‘simplicity’.

There is a difference between the epistemic and the artistic senses of these terms. For example, when it comes to novels, such as A Portrait of the Artist as Young Man, ‘simplicity’ may refer to literary style and language. When it comes to explanations or theories, however, ‘simplicity’ refers to the number of entities posited or assumptions taken for granted (Mizrahi 2016). Clearly, those are two different senses of ‘simplicity’ and Wills is equivocating on the two. As far as Weak Scientism is concerned, it is the epistemic sense of these terms that is of interest to us. Perhaps Wills fails to realize that Weak Scientism is an epistemic thesis because he has not read my (2017a), where I sketch the arguments for this thesis, or at least has not read it carefully enough despite claiming to be a practitioner of “close reading” (Wills 2018b, 34).

When he says that the Joyce scholar “tests [what he says] against the text,” Wills (2018b, 37) reveals his misunderstanding of testability once again. On Wills’ description of the work done by the Joyce scholar, what the Joyce scholar is doing amounts to accommodation, not novel prediction. I have already discussed this point in my previous reply to Wills (Mizrahi 2018b, 47) and I referred him to a paper in which I explain the difference between accommodation and novel prediction (Mizrahi 2012). But it appears that Wills has no interest in reading the works I cite in my replies to his attacks. Perhaps a Stanford Encyclopedia of Philosophy entry on the difference between accommodation and prediction would be more accessible (Barnes 2018).

Wills finds it difficult to see how the work of the Joyce scholar can be improved by drawing on the methods of the sciences. As Wills (2018b, 37) writes, “What in this hermeneutic process would be improved by ‘scientific method’ as Mizrahi describes it? Where does the Joyce scholar need to draw testable consequences from a novel hypothesis and test it with an experiment?” (original emphasis)

Because he sees no way the work of the Joyce scholar can benefit from the application of scientific methodologies, Wills thinks it follows that I have no choice but to say that the work of the Joyce scholar does not count as knowledge. As Wills (2018b, 37) writes, “It seems to me that only option for Mizrahi here is to deny that the Joyce scholar knows anything (beyond the bare factual information) and this means, alas, that his position once again collapses into strong scientism.”

It should be clear, however, that this is a non sequitur. Even if it is true that scientific methodologies are of no use to the Joyce scholar, it does not follow that the work of the Joyce scholar does not count as knowledge. Again, Weak Scientism is the view that scientific knowledge is better than non-scientific knowledge. This means that scientists produce knowledge using scientific methods, whereas non-scientists produce knowledge using non-scientific methods, it’s just that scientists produce better knowledge using scientific methods that are superior to non-scientific methods in terms of the production of knowledge. Non-scientists can use scientific methods to produce knowledge in their fields of inquiry. But even if they do not use scientific methods in their work, on Weak Scientism, the research they produce still counts as knowledge.

Moreover, it is not the case that scientific methodologies are of no use to literary scholars. Apparently, Wills is unaware of the interdisciplinary field in which the methods of computer science and data science are applied to the study of history, literature, and philosophy known as the “Digital Humanities.” Becoming familiar with work in Digital Humanities will help Wills understand what it means to use scientific methods in a literary context. Since I have already discussed all of this in my original paper (Mizrahi 2017a) and in my replies to Brown (Mizrahi 2017b; 2018a), I take this as another reason to think that Wills has not read those papers (or at least has not read them carefully enough).

To me, this is a sign that he is not interested in engaging with Weak Scientism in good faith, especially since my (2017a) and my replies to Brown are themselves instances of the use of methods from data science in HPS, and since I have cited two additional examples of work I have done with Zoe Ashton that illustrates how philosophy can be improved by the introduction of scientific methods (Ashton and Mizrahi 2018a and 2018b). Again, it appears that Wills did not bother to read (let alone read closely) the works I cite in my replies to his attacks.

Toward the end of his discussion of the Joyce scholar, Wills (2018b, 37) says that using scientific methods “may mean better knowledge in many cases.” If he accepts that using scientific methods “may mean better knowledge in many cases” (Wills 2018b, 37), then Wills thereby accepts Weak Scientism as well. For to say that using scientific methods “may mean better knowledge in many cases” (Wills 2018b, 37) is to say that scientific knowledge is generally better than non-scientific knowledge.

Of course, there are instances of bad science, just as there are instances of bad scholarship in any academic discipline. Generally speaking, however, research done by scientists using the methods of science will likely be better (i.e., quantitatively better in terms of research output and research impact as well as qualitatively better in terms of explanatory, predictive, and instrumental success) than research done by non-scientists using non-scientific methods. That is Weak Scientism and, perhaps unwittingly, Wills seems to have accepted it by granting that using scientific methods “may mean better knowledge in many cases” (Wills 2018b, 37).

Inference to the Best Explanation

In my (2017a), as well as in my replies to Brown (Mizrahi 2017b; 2018a) and to Wills (Mizrahi 2018b), I have argued that Inference to the Best Explanation (IBE) is used in both scientific and non-scientific disciplines. As McCain and Poston (2017, 1) put it:

Explanatory reasoning is quite common. Not only are rigorous inferences to the best explanation (IBE) used pervasively in the sciences, explanatory reasoning is virtually ubiquitous in everyday life. It is not a stretch to say that we implement explanatory reasoning in a way that is “so routine and automatic that it easily goes unnoticed” [Douven 2017].

Once this point is acknowledged, it becomes clear that, when judged by the criteria of good explanations, such as unity, coherence, simplicity, and testability, scientific IBEs are generally better than non-scientific IBEs (Mizrahi 2017a, 360; Mizrahi 2017b, 19-20; Mizrahi 2018a, 17; Mizrahi 2018b, 46-47).

In response, Wills tells the story of his daughter who has attempted to reason abductively in class once. Wills (2018b, 38) begins by saying “Let me go back to my daughter,” even though it is the first time he mentions her in his (2018b), and then goes on to say that she once explained “how Scriabin created [the Prometheus] chord” to the satisfaction of her classmates.

But how is this supposed to be evidence against Weak Scientism? In my (2017a), I discuss how IBE is used in non-scientific disciplines and I even give an example from literature (Mizrahi 2017a, 361). Apparently, Wills is unaware of that, which I take to be another indication that he has not read the paper that defends the thesis he seeks to criticize. Again, to quote Wills (2018b, 38) himself, “All disciplines use abduction,” so to give an example of IBE from a non-scientific discipline does nothing at all to undermine Weak Scientism. According to Weak Scientism, all academic disciplines produce knowledge, and many of them do so by using IBE, it’s just that scientific IBEs are better than non-scientific IBEs.

Wills asserts without argument that, in non-scientific disciplines, there is no need to test explanations even when IBE is used to produce knowledge. As Wills (2018b, 38) writes, “All disciplines use abduction, true, but they do not all arrive at the ‘best explanation’ by the same procedures.” For Wills (2018b, 38), his daughter did not need to test her hypothesis about “how Scriabin created [the Prometheus] chord.” Wills does not tell us what the hypothesis in question actually is, so it is hard to tell whether it is testable or not. To claim that it doesn’t need to be tested, however, even when the argument for it is supposed to be an IBE, would be to misuse or abuse IBE rather than use it.

That is, if one were to reason to the best explanation without judging competing explanations by the criteria of unity, coherence, simplicity, testability, and the like, then one would not be warranted in concluding that one’s explanation is the best among those considered. That is just how IBE works (Psillos 2007). To say that an explanation is the best is to say that, among the competing explanations considered, it is the one that explains the most, leaves out the least, is consistent with background knowledge, is the least complicated, and yields independently testable predictions (Mizrahi 2017a, 360-362).

Wills (2018b, 39) seems to grant that “unity, simplicity and coherence” are good-making properties of explanations, but not testability. But why not testability? Why an explanation must be simple in order to be a good explanation, but not testable? Wills does not say. Again (Mizrahi 2018b, 47), I would urge Wills to consult logic and reasoning textbooks that discuss IBE. In those books, he will find that, in addition to unity, coherence, and simplicity, testability is one of the “characteristics that are necessary conditions for any explanation to qualify as being a reasonable empirical explanation” (Govier 2010, 300).

In other words, IBE is itself the procedure by which knowledge is produced. This procedure consists of “an inference from observations and a comparison between competing hypotheses to the conclusion that one of those hypotheses best explains the observations” (Mizrahi 2018c). For example (Sinnott-Armstrong and Fogelin 2015, 196):

  • Observation: Your lock is broken and your valuables are missing.
  • Explanation: The hypothesis that your house has been burglarized, combined with previously accepted facts and principles, provides a suitably strong explanation of observation 1.
  • Comparison: No other hypothesis provides an explanation nearly as good as that in 2.
  • Conclusion: Your house was burglarized.

As we can see, the procedure itself requires that we compare competing hypotheses. As I have mentioned already, “common standards for assessing explanations” (Sinnott-Armstrong and Fogelin 2015, 195) include unity, coherence, simplicity, and testability. This means that, if the hypothesis one favors as the best explanation for observation 1 cannot be tested, then one would not be justified in concluding that it is the best explanation, and hence probably true. That is simply how IBE works (Psillos 2007).

Contrary to what Wills (2018b, 39) seems to think, those who reason abductively without comparing competing explanations by the criteria of unity, coherence, simplicity, and testability are not using IBE, they are misusing or abusing it (Mizrahi 2017a, 360-361). To reason abductively without testing your competing explanations is as fallacious as reasoning inductively without making sure that your sample is representative of the target population (Govier 2010, 258-262).

Image by Specious Reasons via Flickr / Creative Commons

 

The Defense Rests

Fallacious reasoning, unfortunately, is what I have come to expect from Wills after reading and replying to his attacks on Weak Scientism. But this is forgivable, of course, given that we all fall prey to mistakes in reasoning on occasion. Even misspelling my last name several times (Wills 2018a, 18, 22, 24) is forgivable, so I accept Wills’ (2018b, 39) apology. What is unforgivable, however, is lazy scholarship and arguing in bad faith. As I have argued above, Wills is guilty of both because, despite claiming to be a practitioner of “close reading” (Wills 2018b, 34), Wills has not read the paper in which I defend the thesis he seeks to attack (Mizrahi 2017a), or any of the papers in my exchange with Brown (Mizrahi 2017b; 2018a), as evidenced by the fact that he does not cite them at all (not to mention citing and engaging with other works on scientism).

This explains why Wills completely misunderstands Weak Scientism and the arguments for the quantitative superiority (in terms of research output and research impact) as well as qualitative superiority (in terms of explanatory, predictive, and instrumental success) of scientific knowledge over non-scientific knowledge. For these reasons, this is my second and final response to Wills. I have neither the time nor the patience to engage with lazy scholarship that was produced in bad faith.

Contact details: mmizrahi@fit.edu

References

Ashton, Zoe and Moti Mizrahi. “Intuition Talk is Not Methodologically Cheap: Empirically Testing the ‘Received Wisdom’ About Armchair Philosophy.” Erkenntnis 83, no. 3 (2018a): 595-612.

Ashton, Zoe and Moti Mizrahi. “Show Me the Argument: Empirically Testing the Armchair Philosophy Picture.” Metaphilosophy 49, no. 1-2 (2018b): 58-70.

American Philosophical Association. “Minorities in Philosophy.” Data and Information on the Field of Philosophy. Accessed on August 13, 2018. http://c.ymcdn.com/sites/www.apaonline.org/resource/resmgr/data_on_profession/minorities_in_philosophy.pdf.

Barnes, Eric Christian. “Prediction versus Accommodation.” In The Stanford Encyclopedia of Philosophy (Fall 2018 Edition), edited by E. N. Zalta. Accessed on August 14, 2018. https://plato.stanford.edu/archives/fall2018/entries/prediction-accommodation/.

Botts, Tina Fernandes, Liam Kofi Bright, Myisha Cherry, Guntur Mallarangeng, and Quayshawn Spencer. “What Is the State of Blacks in Philosophy?” Critical Philosophy of Race 2, no. 2 (2014): 224-242.

Cherry, Myisha and Eric Schwitzgebel. “Like the Oscars, #PhilosophySoWhite.” Los Angeles Times, March 04, 2016. Accessed on August 13, 2018. http://www.latimes.com/opinion/op-ed/la-oe-0306-schwitzgebel-cherry-philosophy-so-white-20160306-story.html.

Douven, Igor. “Abduction.” In The Stanford Encyclopedia of Philosophy, edited by E. N. Zalta (Summer 2017 Edition). Accessed on August 14, 2018. https://plato.stanford.edu/archives/sum2017/entries/abduction/.

Dupré, John. “Against Scientific Imperialism.” PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994, no. 2 (1994): 374-381.

Ferrer, Amy. “What Can We Do about Diversity?” Leiter Reports: A Philosophy Blog, December 04, 2012. Accessed on August 13, 2018. http://leiterreports.typepad.com/blog/2012/12/what-can-we-do-about-diversity.html.

Govier, Trudy. A Practical Study of Argument. Seventh Edition. Belmont, CA: Wadsworth, 2010.

Graff, Gerald and Cathy Birkenstein. They Say/I Say: The Moves that Matter in Academic Writing. Fourth Edition. New York: W. W. Norton & Co., 2018.

Haack, Susan. Defending Science–within Reason: Between Scientism and Cynicism. New York: Prometheus Books, 2007.

Hawking, Stephen and Leonard Mlodinow. The Grand Design. New York: Bantam Books, 2010.

Kidd, I. J. “How Should Feyerabend Have Defended Astrology? A Reply to Pigliucci.” Social Epistemology Review and Reply Collective 5, no. 6 (2016): 11-17.

McCain, Kevin and Ted Poston. “Best Explanations: An Introduction.” In Best Explanations: New Essays on Inference to the Best Explanation, edited by K. McCain and T. Poston, 1-6. Oxford: Oxford University Press, 2017.

McGlone, Matthew S. “Contextomy: The Art of Quoting out of Context.” Media, Culture & Society 27, no. 4 (2005): 511-522.

Mizrahi, Moti. “Why the Ultimate Argument for Scientific Realism Ultimately Fails.” Studies in the History and Philosophy of Science 43, no. 1 (2012): 132-138.

Mizrahi, Moti. “Why Simpler Arguments are Better.” Argumentation 30, no. 3 (2016): 247-261.

Mizrahi, Moti. “What’s So Bad about Scientism?” Social Epistemology 31, no. 4 (2017a): 351-367.

Mizrahi, Moti. “In Defense of Weak Scientism: A Reply to Brown.” Social Epistemology Review and Reply Collective 6, no. 11 (2017b): 9-22.

Mizrahi, Moti. “More in Defense of Weak Scientism: Another Reply to Brown.” Social

Epistemology Review and Reply Collective 7, no. 4 (2018a): 7-25.

Mizrahi, Moti. “Weak Scientism Defended Once More.” Social Epistemology Review and Reply Collective 7, no. 6 (2018b): 41-50.

Mizrahi, Moti. “The ‘Positive Argument’ for Constructive Empiricism and Inference to the Best Explanation. Journal for General Philosophy of Science (2018c): https://doi.org/10.1007/s10838-018-9414-3.

Offit, Paul A. Autism’s False Prophets: Bad Science, Risky Medicine, and the Search for a Cure. New York: Columbia University Press, 2008.

Paxton, Molly, Carrie Figdor, and Valerie Tiberius. “Quantifying the Gender Gap: An Empirical Study of the Underrepresentation of Women in Philosophy.” Hypatia 27, no. 4 (2012): 949-957.

Peels, Rik. “The Empirical Case Against Introspection.” Philosophical Studies 17, no. 9 (2016): 2461-2485.

Peels, Rik. “A Conceptual Map of Scientism.” In Scientism: Prospects and Problems, edited by J. De Ridder, R. Peels, and R. Van Woudenberg, 28-56. New York: Oxford University Press, 2018.

Psillos, Stathis. “The Fine Structure of Inference to the Best Explanation. Philosophy and Phenomenological Research 74, no. 2 (2007): 441-448.

Rosenberg, Alexander. The Atheist’s Guide to Reality: Enjoying Life Without Illusions. New York: W. W. Norton, 2011.

Scimago Journal & Country Rank. “Subject Bubble Chart.” SJR: Scimago Journal & Country Rank. Accessed on August 13, 2018. http://www.scimagojr.com/mapgen.php?maptype=bc&country=US&y=citd.

Schwitzgebel, Eric, Linus Ta-Lun Huang, Andrew Higgins, Ivan Gonzalez-Cabrera. “The Insularity of Anglophone Philosophy: Quantitative Analyses.” Philosophical Papers 47, no. 1 (2018): 21-48.

Sinnott-Armstrong, Walter and Robert Fogelin. Understanding Arguments. Ninth Edition. Stamford, CT: Cengage Learning, 2015.

Stenmark, Mikael. “What is Scientism?” Religious Studies 33, no. 1 (1997): 15-32.

Van Norden, Bryan. “Western Philosophy is Racist.” Aeon, October 31, 2017a. Accessed on August 12, 2018. https://aeon.co/essays/why-the-western-philosophical-canon-is-xenophobic-and-racist.

Van Norden, Bryan. Taking Back Philosophy: A Multicultural Manifesto. New York: Columbia University Press, 2017b.

Van Vleet, Jacob E. Informal Logical Fallacies: A Brief Guide. Lahman, MD: University Press of America, 2011.

Walton, Douglas N. and Erik C. W. Krabbe. Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning. Albany: State University of New York Press, 1995.

Weinberg, Steven. Dreams of a Final Theory: The Scientist’s Search for the Ultimate Laws of Nature. New York: Random House, 1994.

Wills, Bernard. “Why Mizrahi Needs to Replace Weak Scientism With an Even Weaker Scientism.” Social Epistemology Review and Reply Collective 7, no. 5 (2018a): 18-24.

Wills, Bernard. “On the Limits of any Scientism.” Social Epistemology Review and Reply Collective 7, no. 7 (2018b): 34-39.

[1] I would like to thank Adam Riggio for inviting me to respond to Bernard Wills’ second attack on Weak Scientism.

Heidegger Today, Paolo Palladino

SERRC —  August 23, 2018 — 1 Comment

Author Information: Paolo Palladino, Lancaster University, p.palladino@lancaster.ac.uk

Palladino, Paolo. “Heidegger Today: On Jeff Kochan’s Science and Social Existence.” Social Epistemology Review and Reply Collective 7, no. 8 (2018): 41-46.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-40b

Art by Philip Beasley
Image by Sean Salmon via Flickr / Creative Commons

 

I have been invited to participate in the present symposium on Jeff Kochan’s Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge. I would like to preface my response by expressing my gratitude to the editors of Social Epistemology for the opportunity to comment on this provocative intervention and by noting the following about my response’s intellectual provenance.

I have long worked at the intersection of historical, philosophical and sociological modes of inquiry into the making of scientific accounts and technological interventions in the material world, but at an increasing distance from the field of science and technology studies, widely defined. As a result, I am neither invested in disciplinary purity, nor party in the longstanding arguments over the sociology of scientific knowledge and its presuppositions about the relationship between the social and natural orders.

I must also admit, however, to being increasingly attracted to the ontological questions which the wider field of science and technology studies has posed in recent years. All this is important to how I come to think about both Science as Social Existence and the argument between Kochan and Raphael Sassower over the merits of Science as Social Existence.

Kochan’s Problems of the Strong Programme

As the full title of Science as Social Existence evinces, Kochan’s principal matter of concern is the sociology of scientific knowledge. He regards this as the field of study that is dedicated to explaining the production of knowledge about the material world in sociological terms, as these terms are understood among proponents of the so-called “strong programme”. As Kochan’s response to Sassower conveys pointedly, he is concerned with two problems in particular.

The first of these is that the sociology of scientific knowledge is hostage to a distinction between the inquiring subject and the objective world such that it is difficult to understand exactly how this subject is ever able to say anything meaningful about the objective world. The second, closely related problem is that the sociology of scientific knowledge cannot then respond to the recurrent charge that it holds to an unsustainable relationship between the social and natural orders.

Kochan proposes that Martin Heidegger’s existential phenomenology provides the wherewithal to answer these two problems. This, he suggests, is to the benefit of science and technology studies, the wider, interdisciplinary field of study, which the sociology of scientific knowledge could justifiably be said to have inaugurated but has also grown increasingly detached from the latter. Incidentally, while Kochan himself refers to this wider field as “science studies”, “science and technology studies” seems preferable because it not only enjoys greater currency, but also conveys more accurately the focus on practices and materiality from which stems the divergence between the enterprises Kochan seeks to distinguish.

Anyway, as becomes evident in the course of reading Science as Social Existence, Kochan’s proposal calls first for the correction of Joseph Rouse’s and Bruno Latour’s arguably mistaken reading of Heidegger, particularly in regard to Heidegger’s pivotal distinction between essence and existence, and to Heidegger’s further insistence upon the historicity of Being. This is followed by the obligatory illustration of what is to be gained from such a philosophical excursus.

Kochan thus goes on to revisit what has become a classic of science and technology studies, namely the arguments between Robert Boyle and Thomas Hobbes over the former’s signal invention, the air-pump. Kochan shows here how Heidegger’s thought enables a more symmetric account of the relationship between the social and natural order at issue in the arguments between Boyle and Hobbes, so disarming Latour’s otherwise incisive objection that the sociology of scientific knowledge is a neo-Kantian enterprise that affords matter no agency in the making of the world we inhabit. From this point of view, Science as Social Existence would not only seem to answer important conceptual problems, but also offer a helpful explication and clarification of the notoriously difficult Heideggerian corpus.

It should also be noted, however, that this corpus has actually played a marginal role in the development of science and technology studies and that leading figures in the field have nonetheless occasionally felt compelled to interrogate texts such as Heidegger’s Question Concerning Technology. Such incongruity about the place of Heidegger within the evolution of science and technology studies is perhaps important to understanding Sassower’s caustic line of questioning about what exactly is to be gained from the turn to Heidegger, which Science as Social Existence seeks to advance.

Real Love or a Shotgun Marriage?

Bluntly, Sassower asks why anyone should be interested in marrying Heideggerian existential phenomenology and the sociology of scientific knowledge, ultimately characterising this misbegotten conjunction as a “shotgun marriage’. My immediate answer is that Science as Social Existence offers more than just a detailed and very interesting, if unconventional, examination of the conceptual problems besetting the sociology of scientific knowledge.

As someone schooled in the traditions of history and philosophy of science who has grown increasingly concerned about the importance of history, I particularly welcome the clarification of the role that history plays in our understanding of scientific knowledge and technological practice. Kochan, following Heidegger to the letter, explains how the inquiring subject and the objective world are to be understood as coming into being simultaneously and how the relationship between the two varies in a manner such that what is and what can be said about the nature of that which is are a matter of historical circumstance.

As a result, history weighs upon us not just discursively, but also materially, and so much so that the world we inhabit must be understood as irreducibly historical. As Kochan puts it while contrasting Kant’s and Heidegger’s understanding of finitude:

For Heidegger … the essence of a thing is not something we receive from it, but something it possesses as a result of the socio-historically conditioned metaphysical projection within which it is let be what it is. On Heidegger’s account, not even an infinitely powerful intellect could grasp the intrinsic, independently existing essence of a thing, because no such essence exists. Hence, the finitude of our receptivity is not the issue; the issue is, instead, the finitude of our projectivity. The range of possible conceptualisations of a thing is conditioned by the historical tradition of the subject attempting to make sense of that thing. Only within the finite scope of possibilities enabled by the subject’s tradition can it experience a thing as intelligible, not to mention develop a clearly defined understanding of what it is (258-9).

Literally, tradition matters. Relatedly, I also welcome how Science as Social Existence helps me to clarify the ambiguities of Heidegger’s comportment toward scientific inquiry, which would have been very useful some time ago, as I tried to forge a bridge between the history of biology and a different set of philosophers to those usually considered within the history and philosophy of science, not just Heidegger, but also Michel Foucault and Gilles Deleuze.

As I sought to reflect upon the wider implications of Heidegger’s engagement with the biological sciences of his day, Science as Social Existence would have enabled me to fend off the charge that I misunderstood Heidegger’s distinction between ontic and ontological orders, between the existence of something and the meaning attributed to it. Thus, Kochan points out that:

Metaphysical knowledge is, according to Heidegger, a direct consequence of our finitude, our inescapable mortality, rather than of our presumed ability to transcend that finitude, to reach, infinitely, for heaven. Because the finitude of our constructive power makes impossible a transcendent grasp of the thing in-itself — leaving us to be only affected by it in its brute, independent existence — our attention is instead pushed away from the thing-in-itself and towards the constructive categories we must employ in order to make sense of it as a thing present-at-hand within-the-world.

For Heidegger, metaphysics is nothing other than the study of these categories and their relations to one another. Orthodox metaphysics, in contrast, treats these existential categories as ontic, that is, as extant mental things referring to the intrinsic properties of the things we seek to know, rather than as ontological, that is, as the existential structures of being-in-the-world which enable us to know those things (133-4).

The clarification would have helped me to articulate how the ontic and ontological orders are so inextricably related to one another and, today, so entangled with scientific knowledge and technological practice that Heidegger’s reading of Eugen Korschelt’s lectures on ageing and death matters to our understanding of the fissures within Heidegger’s argument. All this seems to me a wholly satisfactory answer to Sassower’s question about the legitimacy of the conjunction Kochan proposes. This said, Heidegger and sociology are not obvious companions and I remain unpersuaded by what Science as Social Existence might have to offer the more sociologically inclined field of science and technology studies. This, I think, is where the cracks within the edifice that is Science as Social Existence begin to show.

An Incompleteness

There is something unsettling about Science as Social Existence and the distinctions it draws between the sociology of scientific knowledge and the wider field of science and technology studies. For one thing, Science as Social Existence offers an impoverished reading of science and technology studies whereby the field’s contribution to the understanding the production of scientific knowledge and related technological practices is equated with Latour’s criticism of the sociology of scientific knowledge, as the latter was articulated in arguments with David Bloor nearly two decades ago.

Science as Social Existence is not nearly as interested in the complexity of the arguments shaping this wider field as it is in the heterogeneity of philosophical positions taken within the sociology of scientific knowledge with respect to the relationship between knowledge and the material world. It bears repeating at this point that Kochan defines the latter enterprise in the narrowest terms, which also seem far more attuned to philosophical, than sociological considerations. Such narrowness should perhaps come as no surprise given the importance that the sociology of scientific knowledge has attached to the correspondence theory of truth, but there also is much more to the history of philosophy than just the Cartesian and Kantian confrontations with Plato and Aristotle, which Heidegger privileges and Kochan revisits to answer the questions Rouse and Latour have asked of the sociology of scientific knowledge.

Sassower’s possibly accidental reference to a “Spinozist approach” is a useful reminder of both alternative philosophical traditions with respect to materiality, relationality and cognitive construction, and how a properly sociological inquiry into the production of scientific knowledge and technological practices might call for greater openness to the heterogeneity of contemporary social theory. This might even include actor-network theory and its own distinctive reformulation of Spinozist monadology. However, Science as Social Existence is not about any of this, and, as Kochan’s response to Sassower reminds us, we need to respond to its argument on its own terms. Let me then say something about Kochan’s configuration of phenomenology and sociological thought, which is just as unsettling as the relationship Kochan posits between the sociology of scientific knowledge and the wider field of science and technology studies.

Ethnomethodology is the most obvious inheritor to the phenomenological tradition which Kochan invokes to address the problems confronting the sociology of scientific knowledge, and it has also played a very important role in the evolution of science and technology studies. Key ethnomethodological interventions are ambivalent about Heideggerian constructions of phenomenology, but Kochan does not appear to have any great interest in either this sociological tradition or, relatedly, what might be the implications of Heidegger’s divergence from Edmund Husserl’s understanding of the phenomenological project for the relationship between subjects and knowledge.

Instead, Kochan prefers to weld together existential phenomenology and interactionist social theory, because, as he puts it, “interactionist social theory puts the individual subject at the methodological centre of explanations of social, and thus also of cognitive, order” (372). This, however, raises troubling questions about Kochan’s reading and mobilisation of Heidegger. Kochan equates the subject and Being, but Heidegger himself felt the need to develop the term beyond its more conventional connotations of “existence” as he came to understand the subject and Being as closely related, but not one and the same. As Kochan himself notes Being “is not a thing, substance, or object” (39). This form of existence is to be understood instead as a performative operation, if not a becoming.

Furthermore, Kochan would seem to underestimate the importance of Heidegger’s understanding of the relationship between social existence and the fullest realisation of this form of existence. While Heidegger undoubtedly regards Being as emerging from within the fabric of intersubjective relations, Heidegger also maintains that authentic Being realises itself by extricating itself from other beings and so confronting the full meaning of its finitude. As a result, one is compelled to ask what exactly is Kochan’s understanding of the subject and its subjectivity, particularly in relation to the location of “knowledge”.

Possible Predecessors Gone Unacknowledged

Strikingly, these are the kinds of questions that Foucault asks about phenomenology, an enterprise which he regards as contributing to the consolidation of the modern subject. Yet, Kochan would appear to dismiss Foucault’s work, even though Foucault has much to say about not just the historicity of the subject, but also about its entanglement with mathēsis, a concept central to Kochan’s analysis of the encounter between Boyle and Hobbes. Despite the richness and symmetry of the account Kochan offers, it seems quite unsatisfactory to simply observe in a footnote that “Heidegger’s usage of mathēsis differs from that of Michel Foucault, who defines it as ‘the science of calculable order’” (234 n20).

Put simply, there is something amiss about all the slippage around questions of subjectivity, as well as the relationship between the historical and ontological ordering of the world, which calls into question the sociological foundations of the account of the sociology of scientific knowledge which Science as Social Existence seeks to articulate.

Clearly, Kochan mistrusts sociological critiques of the subject, and one of the reasons Kochan provides for the aversion is articulated most pithily in the following passage from his response to Sassower, in relation to the sociological perspectives that have increasingly come to dominate science and technology studies. Kochan writes:

What interests these critics … are fields of practice. Within these fields, the subject is constituted. But the fundamental unit of analysis is the field – or system – not the subject. Subjectivity is, on this theory, a derivative phenomenon, at best, a secondary resource for sociological analysis. From my perspective, because subjectivity is fundamental to human existence, it cannot be eliminated in this way.

In other words, if the subject is constructed, then its subjectivity and structures of feeling can provide no insight into our present condition. This, however, is a very familiar conundrum, one that, in another guise, has long confronted science and technology studies: That something is constructed does not necessarily amount to its “elimination”. The dividing issue at the heart of Science as Social Existence would then seem to be less the relationship between scientific knowledge and the material constitution of the world about us, and more whether one is interested in the clarity of transcendental analytics or charting the topological complexities of immanent transformation.

My preference, however, is to place such weighty and probably irresolvable issues in suspension. It seems to me that it might be more productive to reconsider instead how the subject is constituted and wherein lie its distinctive capacities to determine what is and what can be done, here and now. Anthropological perspectives on the questions science and technology studies seek to pose today suggest that this might be how to build most productively upon the Heideggerian understanding of the subject and the objective world as coming into being simultaneously.

Perhaps, however, I am just another of those readers destined to be “unhappy” about Science as Social Existence, but I am not sure that this is quite right because I hope to have conveyed how much I enjoyed thinking about the questions Science as Social Existence poses, and I would just like to hear more about what Kochan thinks of such alternative approaches to reading Heidegger today.

Contact details: p.palladino@lancaster.ac.uk

References

Kochan, Jeff. Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge. Cambridge: Open Book Publishers, 2017.

Author Information: Moti Mizrahi, Florida Institute of Technology, mmizrahi@fit.edu

Mizrahi, Moti. “Weak Scientism Defended Once More.” Social Epistemology Review and Reply Collective 7, no. 6 (2018): 41-50.

The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3Yx

See also:

One of Galileo’s original compasses, on display at the Museo Galileo, a feature of the Instituto e Museo di Storia della Scienza in Florence, Italy.
Image by Anders Sandberg via Flickr / Creative Commons

 

Bernard Wills (2018) joins Christopher Brown (2017, 2018) in criticizing my defense of Weak Scientism (Mizrahi 2017a, 2017b, 2018a). Unfortunately, it seems that Wills did not read my latest defense of Weak Scientism carefully, nor does he cite any of the other papers in my exchange with Brown. For he attributes to me the view that “other disciplines in the humanities [in addition to philosophy] do not produce knowledge” (Wills 2018, 18).

Of course, this is not my view and I affirm no such thing, contrary to what Wills seems to think. I find it hard to explain how Wills could have made this mistake, given that he goes on to quote me as follows: “Scientific knowledge can be said to be qualitatively better than non-scientific knowledge insofar as such knowledge is explanatorily, instrumentally, and predictively more successful than non-scientific knowledge” (Mizrahi 2018a, 7; quoted in Wills 2018, 18).

Clearly, the claim ‘Scientific knowledge is better than non-scientific knowledge’ entails that there is non-scientific knowledge. If the view I defend entails that there is non-scientific knowledge, then it cannot also be my view that “science produces knowledge and all the other things we tend to call knowledge are in fact not knowledge at all but something else” (Wills 2018, 18).

Even if he somehow missed this simple logical point, reading the other papers in my exchange with Brown should have made it clear to Wills that I do not deny the production of knowledge by non-scientific disciplines. In fact, I explicitly state that “science produces scientific knowledge, mathematics produces mathematical knowledge, philosophy produces philosophical knowledge, and so on” (Mizrahi 2017a, 353). Even in my latest reply to Brown, which is the only paper from my entire exchange with Brown that Wills cites, I explicitly state that, if Weak Scientism is true, then “philosophical knowledge would be inferior to scientific knowledge both quantitatively (in terms of research output and research impact) and qualitatively (in terms of explanatory, instrumental, and predictive success)” (Mizrahi 2018a, 8).

If philosophical knowledge is quantitatively and qualitatively inferior to scientific knowledge, then it follows that there is philosophical knowledge. For this reason, only a rather careless reader could attribute to me the view that “other disciplines in the humanities [in addition to philosophy] do not produce knowledge” (Wills 2018, 18).

There Must Be Some Misunderstanding

Right from the start, then, Wills gets Weak Scientism wrong, even though he later writes that, according to Weak Scientism, “there may be knowledge of some sort outside of the sciences” (Wills 2018, 18). He says that he will ignore the quantitative claim of Weak Scientism and focus “on the qualitative question and particularly on the claim that science produces knowledge and all the other things we tend to call knowledge are in fact not knowledge at all but something else” (Wills 2018, 18). Wills can focus on whatever he wants, of course, but that is not Weak Scientism.

Weak Scientism is not the view that only science produces real knowledge; that is Strong Scientism (Mizrahi 2017a, 353). Rather, Weak Scientism is the view that, “Of all the knowledge we have [i.e., there is knowledge other than scientific knowledge], scientific knowledge is the best knowledge” (Mizrahi 2017a, 354). In other words, scientific knowledge “is simply the best; better than all the rest” (Mizrahi 2017b, 20). Wills’ criticism, then, misses the mark completely. That is, it cannot be a criticism against Weak Scientism, since Weak Scientism is not the view that “science produces knowledge and all the other things we tend to call knowledge are in fact not knowledge at all but something else” (Wills 2018, 18).

Although he deems the quantitative superiority of scientific knowledge over non-scientific knowledge “a tangential point,” and says that he will not spend time on it, Wills (2018, 18) remarks that “A German professor once told [him] that in the first half of the 20th Century there were 40,000 monographs on Franz Kafka alone!” Presumably, Wills’ point is that research output in literature exceeds that of scientific disciplines. Instead of relying on gut feelings and hearsay, Wills should have done the required research in order to determine whether scholarly output in literature really does exceed the research output of scientific disciplines.

If we look at the Scopus database, using the data and visualization tools provided by Scimago Journal & Country Rank, we can see that research output in a natural science like physics and a social science like psychology far exceeds research output in humanistic disciplines like literature and philosophy. On average, psychology has produced 15,000 more publications per year than either literature or philosophy between the years 1999 and 2017. Likewise, on average, physics has produced 54,000 more publications per year than either literature or philosophy between the years 1999 and 2017 (Figure 1). 

Figure 1. Research output in Literature, Philosophy, Physics, and Psychology from 1999 to 2017 (Source: Scimago Journal & Country Rank)

Contrary to what Wills seems to think or what his unnamed German professor may have told him, then, it is not the case that literary scholars produce more work on Shakespeare or Kafka alone than physicists or psychologists produce. The data from the Scopus database show that, on average, it takes literature and philosophy almost two decades to produce what psychology produces in two years or what physics produces in a single year (Mizrahi 2017a, 357-359).

In fact, using JSTOR Data for Research, we can check Wills’ number, as reported to him by an unnamed German professor, to find out that there are 13,666 publications (i.e., journal articles, books, reports, and pamphlets) on Franz Kafka from 1859 to 2018 in the JSTOR database. Clearly, that is not even close to “40,000 monographs on Franz Kafka alone” in the first half of the 20th Century (Wills 2018, 18). By comparison, as of May 22, 2018, the JSTOR database contains more publications on the Standard Model in physics and the theory of conditioning in behavioral psychology than on Franz Kafka or William Shakespeare (Table 1).

Table 1. Search results for ‘Standard Model’, ‘Conditioning’, ‘William Shakespeare’, and ‘Franz Kafka’ in the JSTOR database as a percentage of the total number of publications, n = 12,633,298 (Source: JSTOR Data for Research)

  Number of Publications Percentage of JSTOR corpus
Standard Model 971,968 7.69%
Conditioning 121,219 0.95%
William Shakespeare 93,700 0.74%
Franz Kafka 13,667 0.1%

Similar results can be obtained from Google Books Ngram Viewer when we compare published work on Shakespeare, which Wills thinks exceeds all published work in other disciplines, for he says that “Shakespeare scholars have all of us beat” (Wills 2018, 18), with published work on a contemporary of Shakespeare (1564-1616) from another field of study, namely, Galileo (1564-1642). As we can see from Figure 2, from 1700 to 2000, ‘Galileo’ consistently appears in more books than ‘William Shakespeare’ does.

Figure 2. Google Books results for ‘William Shakespeare’ and ‘Galileo’ from 1700 to 2000 (Source: Google Books Ngram Viewer)

Racking Up the Fallacies

Wills continues to argue fallaciously when he resorts to what appears to be a fallacious ad hominem attack against me. He asks (rhetorically?), “Is Mr. Mizrahi producing an argument or a mere rationalization of his privilege?” (Wills 2018, 19) It is not clear to me what sort of “privilege” Wills wants to claim that I have, or why he accuses me of colonialism and sexism, since he provides no arguments for these outrageous charges. Moreover, I do not see how this is at all relevant to Weak Scientism. Even if I am somehow “privileged” (whatever Wills means by that), Weak Scientism is either true or false regardless.

After all, I take it that Wills would not doubt his physician’s diagnoses just because he or she is “privileged” for working at a hospital. Whether his physician is “privileged” for working at a hospital has nothing to do with the accuracy of his or her diagnoses. For these reasons, Wills’ ad hominem is fallacious (as opposed to a legitimate ad hominem as a rebuttal to an argument from authority, see Mizrahi 2010). I think that SERRC readers will be better served if we focus on the ideas under discussion, specifically, Weak Scientism, not the people who discuss them.

Speaking of privilege and sexism, however, it might be worth noting that, throughout his paper, Wills refers to me as ‘Mr. Mizrahi’ (rather than ‘Dr. Mizrahi’ or simply ‘Mizrahi’, as is the norm in academic publications), and that he has misspelled my name on more than one occasion (Wills 2018, 18, 22, 24). Studies suggest that addressing female doctors with ‘Ms.’ or ‘Mrs.’ rather than ‘Dr.’ might reveal gender bias (see, e.g., Files et al. 2017). Perhaps forms of address reveal not only gender bias but also ethnic or racial bias when people with non-white or “foreign” names are addressed as Mr. (or Ms.) rather than Dr. (Erlenbusch 2018).

Aside from unsubstantiated claims about the amount of research produced by literary scholars, fallacious appeals to the alleged authority of unnamed German professors, and fallacious ad hominem attacks, does Wills offer any good arguments against Weak Scientism? He spends most of his paper (pages 19-22) trying to show that there is knowledge other than scientific knowledge, such as knowledge produced in the fields of “Law and Music Theory” (Wills 2018, 20). This, however, does nothing at all to undermine Weak Scientism. For, as mentioned above, Weak Scientism is the view that scientific knowledge is superior to non-scientific knowledge, which means that there is non-scientific knowledge; it’s just not as good as scientific knowledge (Mizrahi 2017a, 356).

The Core of His Concept

Wills finally gets to Weak Scientism on the penultimate page of his paper. His main objection against Weak Scientism seems to be that it is not clear to him how scientific knowledge is supposed to be better than non-scientific knowledge. For instance, he asks, “Better in what context? By what standard of value?” (Wills 2018, 23) Earlier he also says that he is not sure what are the “certain relevant respect” in which scientific knowledge is superior to non-scientific knowledge (Wills 2018, 18).

Unfortunately, this shows that Wills either has not read the other papers in my exchange with Brown or at least has not read them carefully. For, starting with my first defense of Weak Scientism (2017a), I explain in great detail the ways in which scientific knowledge is better than non-scientific knowledge. Briefly, scientific knowledge is quantitatively better than non-scientific knowledge in terms of research output (i.e., more publications) and research impact (i.e., more citations). Scientific knowledge is qualitatively better than non-scientific knowledge in terms of explanatory, instrumental, and predictive success (Mizrahi 2017a, 364; Mizrahi 2017b, 11).

Wills tries to challenge the claim that scientific knowledge is quantitatively better than non-scientific knowledge by exclaiming, “Does science produce more knowledge that [sic] anything else? Hardly” (Wills 2018, 23). He appeals to Augustine’s idea that one “can produce a potential infinity of knowledge simply by reflecting recursively on the fact of [one’s] own existence” (Wills 2018, 23). In response, I would like to borrow a phrase from Brown (2018, 30): “good luck getting that published!”

Seriously, though, the point is that Weak Scientism is a thesis about academic knowledge or research. In terms of research output, scientific disciplines outperform non-scientific disciplines (see Figure 1 and Table 1 above; Mizrahi 2017a, 357-359; Mizrahi 2018a, 20-21). Besides, just as “recursive processes can extend our knowledge indefinitely in the field of mathematics,” they can also extend our knowledge in other fields as well, including scientific fields. That is, one “can produce a potential infinity of knowledge simply by reflecting recursively on the” (Wills 2018, 23) Standard Model in physics or any other scientific theory and/or finding. For this reason, Wills’ objection does nothing at all to undermine Weak Scientism.

Wills (2018, 23) tries to problematize the notions of explanatory, instrumental, and predictive success in an attempt to undermine the claim that scientific knowledge is qualitatively better than non-scientific knowledge in terms of explanatory, instrumental, and predictive success. But it seems that he misunderstands these notions as they apply to the scientism debate.

As far as instrumental success is concerned, Wills (2018, 23) asks, “Does science have (taken in bulk) more instrumental success than other knowledge forms? How would you even count given that craft knowledge has roughly 3 million-year head start?” Even if it is true that “craft knowledge has roughly 3 million-year head start,” it is irrelevant to whether Weak Scientism is true or false. This is because Weak Scientism is a thesis about academic knowledge or research produced by academic fields of study (Mizrahi 2017a, 356; Mizrahi 2017b, 11; Mizrahi 2018a, 12).

Solving the Problem and Explaining the Issue

As far as explanatory success is concerned, Wills (2018, 23) writes, “Is science more successful at explanation? Hardly, if science could solve problems in literature or history then these fields would not even exist.” There are a couple of problems with this objection. First, explaining and problem solving are not the same thing (Mizrahi and Buckwalter 2014). Second, what makes scientific explanations good explanations are the good-making properties that are supposed to make all explanations (both scientific and non-scientific) good explanations, namely, unification, coherence, simplicity, and testability (Mizrahi 2017a, 360-362; Mizrahi 2017b, 19-20; Mizrahi 2018a, 17).

I have already made this point several times in my replies to Brown, which Wills does not cite, namely, that Inference to the Best Explanation (IBE) is used in both scientific and non-scientific contexts (Mizrahi 2017a, 362). That is, “IBE is everywhere” (Mizrahi 2017b, 20). It’s just that scientific IBEs are better than non-scientific IBEs because they exhibit more of (and to a greater extent) the aforementioned properties that make any explanation a good explanation (Mizrahi 2018b).

As far as predictive success is concerned, Wills (2018, 23) asks, “Does science make more true predictions? Again how would you even count given that for millions of years, human beings survived by making hundreds of true predictions daily?” There are a few problems with this objection as well. First, even if it is true that “for millions of years, human beings survived by making hundreds of true predictions daily,” it is irrelevant to whether Weak Scientism is true or false, since Weak Scientism is a thesis about academic knowledge or research produced by academic fields of study (Mizrahi 2017a, 356; Mizrahi 2017b, 11; Mizrahi 2018a, 12).

Second, contrary to what Wills (2018, 24) seems to think, testing predictions in science is not simply a matter of making assertions and then checking to see if they are true. For one thing, a prediction is not simply an assertion, but rather a consequence that follows from a hypothesis plus auxiliary hypotheses (Mizrahi 2015). For another, a prediction needs to be novel such that we would not expect it to be the case except from the vantage point of the theory that we are testing (Mizrahi 2012).

As I have advised Brown (Mizrahi 2018, 17), I would also advise Wills to consult logic and reasoning textbooks, not because they provide support for the claim that “science is instrumentally successful, explanatory and makes true predictions,” as Wills (2018, 23) erroneously thinks, but because they discuss hypothesis testing in science. For Wills’ (2018, 24) remark about Joyce scholars suggests a failure to understand how hypotheses are tested in science.

Third, like Brown (2017, 49), Wills (2018, 23) admits that, just like science, philosophy is in the explanation business. For Wills (2018, 23) says that, “certainty, instrumental success, utilitarian value, predictive power and explanation all exist elsewhere in ways that are often not directly commensurable with the way they exist in science” (emphasis added). But if distinct fields of study have the same aim (i.e., to explain), then their products (i.e., explanations) can be evaluated with respect to similar criteria, such as unification, coherence, simplicity, and testability (Mizrahi 2017a, 360-362; Mizrahi 2017b, 19-20; Mizrahi 2018a, 17).

In other words, there is no incommensurability here, as Wills seems to think, insofar as both science and philosophy produce explanations and those explanations must exhibit the same good-making properties that make all explanations good explanations (Mizrahi 2018a, 17; 2018b).

“You Passed the Test!”

If Wills (2018, 24) wants to suggest that philosophers should be “testing their assertions in the ways peculiar to their disciplines,” then I would agree. However, “testing” does not simply mean making assertions and then checking to see if they are true, as Wills seems to think. After all, how would one check to see if assertions about theoretical entities are true? To test a hypothesis properly, one must derive a consequence from it (plus auxiliary assumptions) that would be observed only if the hypothesis (plus the auxiliary assumptions) is true.

Observations and/or experimentation would then indicate to one whether the consequence obtains or not (Mizrahi 2012). Of course, some philosophers have been doing just that for some time now (Knobe 2017). For instance, some experimental philosophers test hypotheses about the alleged intuitiveness of philosophical ideas and responses to thought experiments (see, e.g., Kissinger-Knox et al. 2018). I welcome such empirical work in philosophy.

Contrary to what Wills (2018, 19) seems to think, then, my aim is not to antagonize philosophers. Rather, my aim is to reform philosophy. In particular, as I have suggested in my recent reply to Brown (Mizrahi 2018a, 22), I think that philosophy would benefit from adopting not only the experimental methods of the cognitive and social sciences, as experimental philosophers have done, but also the methods of data science, such as data mining and corpus analysis (see, e.g., Ashton and Mizrahi 2018a and 2018b).

Indeed, the XPhi Replicability Project recently published a report on replication studies of 40 experimental studies according to which experimental studies “successfully replicated about 70% of the time” (Cova et al. 2018). With such a success rate, one could argue that the empirical revolution in philosophy is well under way (see also Knobe 2015). Resistance is futile!

Contact details: mmizrahi@fit.edu

References

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Cova, Florian, Brent Strickland, Angela G Abatista, Aurélien Allard, James Andow, Mario Attie, James Beebe, et al. “Estimating the Reproducibility of Experimental Philosophy.” PsyArXiv, April 21, 2018. doi:10.17605/OSF.IO/SXDAH.

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Mizrahi, M. “In Defense of Weak Scientism: A Reply to Brown.” Social Epistemology Review and Reply Collective 6, no. 11 (2017b): 9-22.

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Mizrahi, M. and Buckwalter, W. “The Role of Justification in the Ordinary Concept of Scientific Progress.” Journal for General Philosophy of Science 45, no. 1 (2014): 151-166.

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Wills, B. “Why Mizrahi Needs to Replace Weak Scientism With an Even Weaker Scientism.” Social Epistemology Review and Reply Collective 7, no. 5 (2018): 18-24.