A big-data contribution to the history of philosophy

The history of philosophy is generally written by subject experts who explore and follow a tradition of thought about which figures and topics were "pivotal" and thereby created an ongoing research field. This is illustrated, for example, in Stephen Schwartz's A Brief History of Analytic Philosophy: From Russell to Rawls. Consider the history of Anglophone philosophy since 1880 as told by a standard narrative in the history of philosophy of this period. One important component was "logicism" -- the idea that the truths of mathematics can be derived from purely logical axioms using symbolic logic. Peano and Frege formulated questions about the foundations of arithmetic; Russell and Whitehead sought to carry out this program of "logicism"; and Gödel proved the impossibility of carrying out this program: any set of axioms rich enough to derive theorems of arithmetic is either incomplete or inconsistent. This narrative serves to connect the dots in this particular map of philosophical development. We might want to add details like the impact of logicism on Wittgenstein and the impact of Tractatus Logico-Philosophicus, but the map is developed by tracing contacts from one philosopher to another, identifying influences, and aggregating groups of topics and philosophers into "schools".

Brian Weatherson, a philosopher at the University of Michigan, has a different idea about how we might proceed in mapping the development of philosophy over the past century (link) (Brian Weatherson, A History of Philosophy Journals: Volume 1: Evidence from Topic Modeling, 1876-2013. Vol. 1. Published by author on Github, 2020; link). Professional philosophy in the past century has been primarily expressed in the pages of academic journals. So perhaps we can use a "big data" approach to the problem of discovering and tracking the emergence of topics and fields within philosophy by analyzing the frequency and timing of topics and concepts as they appear in academic philosophy journals.

Weatherson pursues this idea systematically. He has downloaded from JSTOR the full contents of twelve leading journals in anglophone philosophy for the period 1876-2013, producing a database of some 32,000 articles and lists of all words appearing in each article (as well as their frequencies). Using the big data technique called "topic modeling" he has arrived at 90 subjects (clusters of terms) that recur in these articles. Here is a quick description of topic modeling.

Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA) is an example of topic model and is used to classify text in a document to a particular topic. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions. (link)

Here is Weatherson's description of topic modeling:

An LDA model takes the distribution of words in articles and comes up with a probabilistic assignment of each paper to one of a number of topics. The number of topics has to be set manually, and after some experimentation it seemed that the best results came from dividing the articles up into 90 topics. And a lot of this book discusses the characteristics of these 90 topics. But to give you a more accessible sense of what the data looks like, I’ll start with a graph that groups those topics together into familiar contemporary philosophical subdisciplines, and displays their distributions in the 20th and 21st century journals. (Weatherson, introduction)

Now we are ready to do some history. Weatherson applies the algorithms of LDA topic modeling to this database of journal articles and examines the results. It is important to emphasize that this method is not guided by the intuitions or background knowledge of the researcher; rather, it algorithmically groups documents into clusters based on the frequencies of various words appearing in the documents. Weatherson also generates a short list of keywords for each topic: words of a reasonable frequency in which the probability of the word appearing in articles in the topic is significantly greater than the probability of it occurring in a random article. And he further groups the 90 subjects into a dozen familiar "categories" of philosophy (History of Philosophy, Idealism, Ethics, Philosophy of Science, etc.). This exercise of assigning topics to categories requires judgment and expertise on Weatherson's part; it is not algorithmic. Likewise, the assignment of names to the 90 topics requires expertise and judgment. From the point of view of the LDA model, the topics could be given entirely meaningless names: T1, T2, ..., T90.

Now every article has been assigned to a topic and a category, and every topic has a set of keywords that are algorithmically determined. Weatherson then goes back and examines the frequency of each topic and category over time, presented as graphs of the frequencies of each category in the aggregate (including all twelve journals) and singly (for each journal). The graphs look like this:

We can look at these graphs as measures of the rise and fall of prevalence of various fields of philosophy research in the Anglophone academic world over the past century. Most striking is the contrast between idealism (precipitous decline since 1925) and ethics (steady increase in frequency since about the same time), but each category shows some interesting characteristics.

Now consider the disaggregation of one topic over the twelve journals. Weatherson presents the results of this question for all ninety topics. Here is the set of graphs for the topic "Methodology of Science":

All the journals -- including Ethics and Mind -- have articles classified under the topic of "Methodology of Science". For most journals the topic declines in frequency from roughly the 1950s to 2013. Specialty journals in the philosophy of science -- BJPS and Philosophy of Science -- show a generally higher frequency of "Methodology of Science" articles, but they too reveal a decline in frequency over that period. Does this suggest that the discipline of the philosophy of science declined in the second half of the twentieth century (not the impression most philosophers would have)? Or does it rather reflect the fact that the abstract level of analysis identified by the topic of "Methodology of Science" was replaced with more specific and concrete studies of certain areas of the sciences (biology, psychology, neuroscience, social science, chemistry)?

These results permit many other kinds of questions and discoveries. For example, in chapter 7 Weatherson distills the progression of topics across decades by listing the most popular five topics in each decade:

This table too presents intriguing patterns and interesting questions for further research. For example, from the 1930s through the 1980s a topic within the general field of the philosophy of science is in the list of the top five topics: methodology of science, verification, theories and realism. These topics fall off the list in the 1990s and 2000s. What does this imply -- if anything -- about the prominence or importance of the philosophy of science within Anglophone philosophy in the last several decades? Or as another example -- idealism is the top-ranked topic from the 1890s through the 1940s, only disappearing from the list in the 1960s. This is surprising because the standard narrative would say that idealism was vanquished within philosophy in the 1930s. And another interesting example -- ordinary language. Ordinary language is a topic on the top five list for every decade, and is the most popular topic from the 1950s through the present. And yet "ordinary language philosophy" would generally be thought to have arisen in the 1940s and declined permanently in the 1960s. Finally, topics in the field of ethics are scarce in these lists; "promises and imperatives" is the only clear example from the topics listed here, and this topic appears only in the 1960s and 1970s. That seems to imply that the fields of ethics and social-political philosophy were unimportant throughout this long sweep of time -- hard to reconcile with the impetus given to substantive ethical theory and theory of justice in the 1960s and 1970s. For that matter, the original list of 90 topics identified by the topic-modeling algorithm is surprisingly sparse when it comes to topics in ethics and political philosophy: 2.16 Value, 2.25 Moral Conscience, 2.31 Social Contract Theory, 2.33 Promises and Imperatives, 2.41 War, 2.49 Virtues, 2.53 Liberal Democracy, 2.53 Duties, 2.65 Egalitarianism, 2.70 Medical Ethics and Freud, 2.83 Population Ethics, 2.90 Norms. Where is "Justice" in the corpus?

Above I described this project as a new approach to the history of philosophy (surely applicable as well to other fields such as art history, sociology, or literary criticism). But it seems clear that the modeling approach Weatherson pursues is not a replacement for other conceptions of intellectual history, but rather a highly valuable new source of data and questions that historians of philosophy will want to address. And in fact, this is how Weatherson treats the results of this work: not as replacement but rather as a supplement and a source of new puzzles for expert historians of philosophy.

(There is an interesting parallel between this use of big data and the use of Ngrams, the tool Google created to map the frequency of the occurrences of various words in books over the course of several centuries. Here are several earlier posts on the use of Ngrams: link, link. Gabriel Abend made use of this tool in his research on the history of business ethics in The Moral Background: An Inquiry into the History of Business Ethics. Here is a discussion of Abend's work; link. The topic-modeling approach is substantially more sophisticated because it does not reduce to simple word frequencies over time. As such it is a very significant and innovative contribution to the emerging field of "digital humanities" (link).)

Academic social media

The means through which academics engage in communication and discussion of their ideas have changed significantly in the past decade through the rapid growth of the importance of social media in the dissemination of new ideas. Social media platforms like Twitter, Facebook, Medium, Blogger, Tumblr, and WordPress have become important media for communication in a range of fields, from celebrity gossip to news flashes to the dissemination of new breakthroughs in particle physics. Blogging platforms such as Blogger, Medium, and Wordpress in particular have become a highly accessible place for the expression of ideas, opinions, and social commentary. An idea posted on WordPress is instantly visible in most countries in the world (not including China). And because of the amazing coverage of search engines, that idea can be located by the academic researcher in Mumbai, Helsinki, Buenos Aires, or Des Moines within minutes of posting.

The challenge of social media as a channel for serious ideas and engaged debate is the fact that there are few of the badges of reliability provided by conventional media and academic journals associated with social media. So the hard question is whether social media channels can serve a serious intellectual purpose in terms of the dissemination of knowledge.

The appearance of a second edition of Mark Carrigan's Social Media for Academics is therefore timely. Both young academics -- well versed in the mechanics of social media -- and more senior scholars will find the book interesting and provocative, and many will find useful new ways of presenting and discussing their work using the resources created by social media platforms. I've long been convinced of the value of blogging as a platform for developing and disseminating my work in philosophy and sociology, and I celebrate Mark's efforts to help all of us figure out constructive, intellectually valuable ways of using the various media available to us.

It is interesting to reflect a bit on what an academic -- a professor, a professional political scientist or literary critic or physicist -- wants to accomplish with his or her writing, and whether social media can help with those goals. There are a number of possible goals that come to mind:

1. to explore new ideas and get useful feedback from others about those ideas
2. to achieve solid, well argued results on a topic that will be a permanent part of the corpus in one's field
3. To contribute to important contemporary debates through better insights into current problems (global climate change, war in the Middle East, the threat of rising nationalist-populism)
4. to elevate one's position in the status-hierarchy of the profession
5. to create a "celebrity" reputation in a field that leads to invitations as commentator on public television or CNN

The first motivation is well suited to social media. If one can gather a small network of people with similar interests and a willingness to interact, a blog can be a very good mechanism for testing and improving one's ideas. The second motivation can also be served by social media, in the sense that exposure of one's ideas through social media can help to deepen and refine one's thinking. In order for these ideas to become part of the permanent corpus of one's field of study, it seems likely enough that the ideas and theories will need to find more traditional forms of academic expression -- book chapters, peer-reviewed articles, and books. But these two goals are entirely consistent with being an authentic scholar and academic; they have to do with the pursuit of truth and insight. And they fall in the category of the "new collegiality" that Carrigan discusses (232).

The third goal is a respectable academic goal as well. It is entirely legitimate and appropriate for academics to bring their voices to bear on the issues of the day. Certainly some of the Twitter feeds I appreciate the most come from academics like Michael E. Mann (@MichaelEMann), Branko Milanovic (@BrankoMilan), Juan Cole (@jricole), and Dan Nexon (@dhnexon). And what I appreciate about their tweets is the honesty and relevance their ideas (and links) have in addressing topics like climate change, global inequalities, and issues of war and peace.

The final pair of goals -- status, reputation, and well-paid television gigs -- seem a bit antagonistic to the most important academic values. I suppose that Aristotle and Kant both would find these goals obnoxious because they are narrowly self-interested and unrelated to the virtues or duties of an academic -- pursuit of truth and the advancement of knowledge. But, sad to say, it is clear enough how social media can support these goals as well, as Carrigan discusses in several places (136).

I am very glad that Mark has brought a discussion of the "dark side" of social media into the discussion in the second edition. Like all things digital, the hate-based Internet has moved rapidly since the first edition of this book, and it is now a very important part of the rise of right-wing populism in many countries. Likewise, the use of social media to bully and harass people in the most abhorrent ways is a plague that we haven't learned how to control. And the weaponization of social media that has occurred since the first edition of the book is a genuine threat to democratic institutions.

Mark Carrigan is an astute and well-informed follower of the topic of the rising role of social media in the academic world, and the book is well worth a close reading. And it raises an interesting question: what would Socrates' Twitter stream have looked like?

The tempos of capitalism

I've been interested in the economic history of capitalism since the 1970s, and there are a few titles that stand out in my memory. There were the Marxist and neo-Marxist economic historians (Marx's Capital, E.P. Thompson, Eric Hobsbawm, Rodney Hilton, Robert Brenner, Charles Sabel); the debate over the nature of the industrial revolution (Deane and Cole, NFR Crafts, RM Hartwell, EL Jones); and volumes of the Cambridge Economic History of Europe. The history of British capitalism poses important questions for social theory: is there such a thing as "capitalism", or are there many capitalisms? What are the features of the capitalist social order that are most fundamental to its functioning and dynamics of development? Is Marx's intellectual construction of the "capitalist mode of production" a useful one? And does capitalism have a logic or tendency of development, as Marx believed, or is its history fundamentally contingent and path-dependent? Putting the point in concrete terms, was there a probable path of development from the "so-called primitive accumulation" to the establishment of factory production and urbanization to the extension of capitalist property relations throughout much of the world?

Part of the interest of detailed research in economic history in different places -- England, Sweden, Japan, the United States, China -- is the light that economic historians have been able to shed on the particulars of modern economic organization and development, and the range of institutions and "life histories" they have identified for these different historically embodied social-economic systems. For this reason I have found it especially interesting to read and learn about the ways in which the early modern Chinese economy developed, and different theories of why China and Europe diverged in this period. Kenneth Pomeranz, Philip Huang, William Skinner, Mark Elvin, Bozhong Li, James Lee, and Joseph Needham all shed light on different aspects of this set of questions, and once again the Cambridge Economic History of China was a deep and valuable resource.

A  new title that recently caught my eye is Pierre Dockès' Le Capitalisme Et Ses Rythmes, quatre siècles en perspective: Tome I Sous Le Regard Des Géants. Intriguing features of the book include the long sweep of the book (400 years, over 950 pages, with volume II to come), and the question of whether there is something new to say about this topic. After reading large parts of the book, I think the answer to the last question is "yes".

Dockès is interested in both the history of capitalism as an economic system and the history of economic science and political economy during the past four centuries. And he is particularly interested in discovering what we can learn about our current economic challenges from both these stories.

He specifically distances himself from "mainstream" economic theory and couches his own analysis in a less orthodox and more eclectic set of ideas. He defines mainstream economics in terms of five ideas: first, its strong commitment to mathematization and formalization of economic ideas; second, its disciplinary tendency towards hyper-specialization; third, its tendency to take the standpoint of the capitalist and the free market in its analyses; fourth, the propensity to extend these neoliberal biases to the process of selection and hiring of academics; and fifth, its underlying “scientism” and positivism leads its practitioners to devalue the history of the discipline or the historical conditions through which modern institutions came to be (9-12).

 

Dockès holds that the history of the economic facts and the ideas researchers have had about these facts go hand in hand; economic history and the history of economics need to be studied together. Moreover, Dockès believes that mainstream economics has lost sight of insights from the innovators in the history of economics which still have value -- Ricardo, Smith, Keynes, Walras, Sismondi, Hobbes. The solitary focus of the discipline of mainstream economics in the past forty years on formal, mathematical representations of a market economy precludes these economists from "seeing" the economic world through the conceptual lenses of gifted predecessors. They are trapped in a paradigm or an "epistemological framework" from which they cannot escape. (These ideas are explored in the introduction to the volume.)

The substantive foundation of the book is Dockès’ idea that capitalism has long-term rhythms punctuated by crises, and that these fluctuations themselves are amenable to historical-causal and institutional analysis.

En un mot, croissance et crise sont inséparables et inhérents au processus de développement capitaliste laissé à lui-même.

[In a word, growth and crisis are inseparable and inherent in the process of capitalist development left to itself.] (13)

The fluctuations of capitalism over the longterm are linked in a single system of causation — growth, depression, financial crisis, and growth again are linked. Therefore, Dockès believes, it should be possible to discover the systemic causes of the development of various capitalist economies by uncovering the dynamics of crisis. Further, he underlines the serious social and political consequences that have ensued from economic crises in the past, including the rise of the Nazi regime out of the global economic crisis of the 1930s.

Etudier ces rythmes impose une analyse des logiques de fonctionnement du capitalism.

[Studying these rhythms imposes an analysis of the logic of functioning of capitalism.] (12).

Dockès is explicit in saying that economic history does not "repeat" itself, and the crises of capitalism are not replicas of each other over the decades or centuries. Historicity of the time and place is fundamental, and he underlines the path dependency of economic development in some of its aspects as well. But he argues that there are important similarities across various kinds of economic crises, and it is worthwhile discovering these similarities. He takes debt crises as an example: there are great differences among several centuries of experience of debt crisis. But there is something in common as well:

Permanence aussi dans les relations de pouvoir et dans let intérêts des uns (les créanciers partisans de la déflation, des taux élevés) et des autres (les débiteurs inflationnistes), dan les jeux de l'état entre ces deux groupes de pression. On peut tirer deux conséquences des homologies entre le passé et le présent.

[Permanence also in the relations of power and in the interests of some (creditors who favor deflation, high rates) and others (inflationary debtors), in the games of the state between these two pressure groups. We can draw two resulting homologies between the past and the present.] (20)

And failing to consider carefully and critically the economies and crises of the past is a mistake that may lead contemporary economic experts and advisors into ever-deeper economic crises in the future.

L'oubli est dommageable, celui des catastrophes, celui des enseignements qu'elles ont rendu possible, celui des corpus théoriques du passé. Ouvrir la perspective par l'économie historique peut aider à une meilleure compréhension du présent, voire à préparer l'avenir. (21)

[Forgetting is harmful, especially forgetting past catastrophes, forgetting the lessons they have made possible, forgetting the theoretical corpus of the past. Embracing the perspective of the concrete economic history can help lead to a better understanding of the present, or even prepare for the future.] (21)

The scope and content of the book are evident in the list of the book's chapters:

1. Crises et rythmes économiques
2. Périodisation, mutations et rythmes longs
3. Le capitalism d'Ancien Régime, ses crises
4. Le "Haut Capitalism", ses crises et leur théorisation (1800-1870)
5. Karl Marx et les crises
6. Capitalisme "Monopoliste" et grande industrie (1870-1914)
7. Interlude
8. Á l'âge de l'acier, les rythmes de l'investissement et de l'innovation
9. Impulsion monétaire et effets réels
10. La monnaie hégémonique
11. "Le chien dans la mangeoire"
12. La grande crise des années trente
13. Keynes et la "Théorie Générale"La "Haute Théorie", la dynamique, le cycle (1926-1946)
14. En guise de conclusion d'étape

As the chapter titles make evident, Dockès delivers on his promise of treating both the episodes, trends, and facts of economic history as well as the history of the theories through which economists have sought to understand those facts and their dynamics.

Experimental sociology of norms and decision-making

The discipline of experimental economics is now a familiar one. It is a field that attempts to probe and test the behavioral assumptions of the theory of economic rationality, microeconomics, and game theory. How do real human reasoners deliberate and act in classic circumstances of economic decision-making? John Kagel and Alvin Roth provide an excellent overview of the discipline in The Handbook of Experimental Economics, where they identify key areas of research in expected utility theory, game theory, free-riding and public goods theory, bargaining theory, and auction markets.

Behavioral economics is a related field but is generally understood as having a broader definition of subject matter. It is the discipline in which researchers use the findings of psychology, cognitive science, cultural studies, and other areas of behavioral sciences to address issues of economics, without making the heroic assumptions of strict economic rationality concerning the behavior and choices of the agents. The iconoclastic writings of Kahneman and Tversky are foundational contributions to the field (Choices, Values, and Frames), and Richard Thaler's work (Nudge: Improving Decisions About Health and Wealth, and Happiness and Misbehaving: The Making of Behavioral Economics) exemplifies the approach.

Here is a useful description of behavioral and experimental economics offered by Ana Santos:

Behavioural experiments have produced a substantial amount of evidence that shows that human beings are prone to systematic error even in areas of economic relevance where stakes are high (e.g. Thaler, 1992; Camerer, 1995). Rather than grounding individual choice on the calculus of the costs and benefits of alternative options so as to choose the alternative that provides the highest net benefit, individuals have recourse to a variety of decisional rules and are influenced by various contextual factors that jeopardise the pursuit of individuals’ best interests. The increased understanding of how people actually select and apply rules for dealing with particular forms of decision problems and of the influence of contexts on individual choices is the starting point of choice architecture devoted to the study of choice setups that can curb human idiosyncrasies to good result, as judged by individuals themselves, or by society as a whole (Thaler and Sunstein, 2003, 2008).

Researchers in experimental and behavioral economics make use of a variety of empirical and "experimental" methods to probe the nature of real human decision-making. But the experiments in question are generally of a very specialized kind. The goal is often to determine the characteristics of the decision rule that is used by a group of actual human decision-makers. So the subjects are asked to “play” a game in which the payoffs correspond to one of the simple games studied in game theory — e.g. the prisoners’ dilemma — and their behavior is observed from start to finish. This seems to be more a form of controlled observation than experimentation in the classical sense -- isolating an experimental situation and a given variable of interest F, and then running the experiment in the presence and absence of F.

It is intriguing to ask whether a similar empirical approach might be applied to some of the findings and premises of micro-sociology. Sociologists too make assumptions about motivation, choice, and action. Whether we consider the sociology of contention, the sociology of race, or the sociology of the family, we are unavoidably drawn to making provisional assumptions about what makes the actors in these situations tick. What are their motives? How do they evaluate the facts of a situation? How do they measure and weigh risk in the actions they choose? How do ambient social norms influence their action? Whether explicitly or implicitly, sociologists make assumptions about the answers to questions like these. Could some of the theoretical ideas of James Coleman, Erving Goffman, or Mark Granovetter be subjected to experimental investigation? Even more intriguingly, are there supra-individual hypotheses offered by sociologists that might be explored with experimental methods?

Areas where experimental and empirical investigation might be expected to pay dividends in sociology include the motivations underlying cooperation and competition, Granovetter's sociology of social embeddedness, corruption, the theories of conditional altruism and conditional fairness, the dynamics of contention, and the micro-social psychology of race and gender.

So is there an existing field of research that attempts to investigate questions like these using experiments and human subjects placed in artificial circumstances of action?

To begin, there are some famous examples of experiments in the behavioral sciences that are relevant to these questions. These include the Milgram experiment, the Stanford Prison experiment, and a variety of altruism experiments. These empirical research designs aim at probing the modes of behavior, norm observance, and decision-making that characterize real human beings in real circumstances.

Second, it is evident that the broad discipline of social psychology is highly relevant to this topic. For example, the study of "motivated reasoning" has come to play an important role within the discipline of social psychology (link).

Motivated reasoning has become a central theoretical concept in academic discourse across the fields of psychology, political science, and mass communication. Further, it has also entered the popular lexicon as a label for the seemingly limitless power of partisanship and prior beliefs to color and distort perceptions of the political and social world. Since its emergence in the psychological literature in the mid- to late-20th century, motivated reasoning theory has been continuously elaborated but also challenged by researchers working across academic fields. In broad terms, motivated reasoning theory suggests that reasoning processes (information selection and evaluation, memory encoding, attitude formation, judgment, and decision-making) are influenced by motivations or goals. Motivations are desired end-states that individuals want to achieve. The number of these goals that have been theorized is numerous, but political scientists have focused principally on two broad categories of motivations: accuracy motivations (the desire to be “right” or “correct”) and directional or defensive motivations (the desire to protect or bolster a predetermined attitude or identity). While much research documents the effects of motivations for attitudes, beliefs, and knowledge, a growing literature highlights individual-level variables and contexts that moderate motivated reasoning.

See Epley and Gilovich (link) for an interesting application of the "motivated reasoning" approach.

Finally, some of the results of behavioral and experimental economics are relevant to sociology and political science as well.

These ideas are largely organized around testing the behavioral assumptions of various sociological theories. Another line of research that can be treated experimentally is the investigation of locally relevant structural arrangements that some sociologists have argued to be causally relevant to certain kinds of social outcomes. Public schools with health clinics have been hypothesized to have better educational outcomes than those without such clinics. Factory workers are sometimes thought to be more readily mobilized in labor organizations than office workers. Small towns in rural settings are sometimes thought to be especially conducive to nationalist-populist political mobilization. And so forth. Each of these hypotheses about the causal role of social structures can be investigated empirically and experimentally (though often the experiments take the form of quasi-experiments or field experiments rather than randomly assigned subjects divided into treatment and control populations).

It seems, then, that the methods and perspective of behavioral and experimental economics are indeed relevant to sociological research. Some of the premises of key sociological theories can be investigated experimentally, and doing so has the promise of further assessing and deepening the content of those sociological theories. Experiments can help to probe the forms of knowledge-formation, norm acquisition, and decision-making that real social actors experience. And with a little ingenuity, it seems possible to use experimental methods to evaluate some core hypotheses about the causal roles played by various kinds of "micro-" social structures.

The sociology of scientific discipline formation

There was a time in the philosophy of science when it may have been believed that scientific knowledge develops in a logical, linear way from observation and experiment to finished theory. This was something like the view presupposed by the founding logical positivists like Carnap and Reichenbach. But we now understand that the creation of a field of science is a social process with a great deal of contingency and path-dependence. The institutions through which science proceeds -- journals, funding agencies, academic departments, Ph.D. programs -- are all influenced by the particular interests and goals of a variety of actors, with the result that a field of science develops (or fails to develop) with a huge amount of contingency. Researchers in the history of science and the sociology of science and technology approach this problem in fairly different ways.

Scott Frickel's 2004 book Chemical Consequences: Environmental Mutagens, Scientist Activism, and the Rise of Genetic Toxicology represents an effort to trace out the circumstances of the emergence of a new scientific sub-discipline, genetic toxicology. "This book is a historical sociological account of the rise of genetic toxicology and the scientists' social movement that created it" (kl 37).

Frickel identifies two large families of approaches to the study of scientific disciplines: "institutionalist accounts of discipline and specialty formation" and "cultural studies of 'disciplinarity' [that] make few epistemological distinctions between the cognitive core of scientific knowledge and the social structures, practices, and processes that advance and suspend it" (kl 63). He identifies himself primarily with the former approach:

I draw from both modes of analysis, but I am less concerned with what postmodernist science studies call the micropolitics of meaning than I am with the institutional politics of knowledge. This perspective views discipline building as a political process that involves alliance building, role definition, and resource allocation. ... My main focus is on the structures and processes of decision making in science that influence who is authorized to make knowledge, what groups are given access to that knowledge, and how and where that knowledge is implemented (or not). (kl 71)

Crucial for Frickel's study of genetic toxicology is this family of questions: "How is knowledge produced, organized, and made credible 'in-between' existing disciplines? What institutional conditions nurture interdisciplinary work? How are porous boundaries controlled? Genetic toxicology's advocates pondered similar questions. Some complained that disciplinary ethnocentrism prevented many biologists' appreciation for the broader ecological implications of their own investigations.... " (kl 99).

The account Frickel provides involves all of the institutional contingency that we might hope for; at the same time, it is an encouraging account for anyone committed to the importance of scientific research in charting a set of solutions to the enormous problems humanity currently faces.

Led by geneticists, these innovations were also intensely interdisciplinary, reflecting the efforts of scientists working in academic, government, and industry settings whose training was rooted in more than thirty disciplines and departments ranging across the biological, agricultural, environmental, and health sciences. Although falling short of some scientists' personal visions of what this new science could become, their campaign had lasting impacts. Chief among these outcomes have been the emergence of a set of institutions, professional roles, and laboratory practices known collectively as "genetic toxicology." (kl 37)

Frickel gives prominence to the politics of environmental activism in the emergence and directions of the new discipline of genetic toxicology. Activists on campus and in the broader society gave impetus to the need for new scientific research on the various toxic effects of pesticides and industrial chemicals; but they also affected the formation of the scientists themselves.

Also of interest is an edited volume on interdisciplinary research in the sciences edited by Frickel, Mathieu Albert, and Barbara Prainsack, Investigating Interdisciplinary Collaboration: Theory and Practice across Disciplines. The book takes special notice of some of the failures of interdisciplinarity, and calls for a careful assessment of the successes and failures of interdisciplinary research projects.

 We think that these celebratory accounts give insufficient analytical attention to the insistent and sustained push from administrators, policy makers, and funding agencies to engineer new research collaborations across disciplines. In our view, the stakes of these efforts to seed interdisciplinary research and teaching "from above" are sufficiently high to warrant a rigorous empirical examination of the academic and social value of interdisciplinarity. (kl 187)

In their excellent introduction Frickel, Albert, and Prainsack write:

A major problem that one confronts in assuming the superiority of interdisciplinary research is a basic lack of studies that use comparative designs to establish that measurable differences in fact exist and to demonstrate the value of interdisciplinarity relative to disciplinary research. (kl 303)

They believe that the appreciation of "interdisciplinary research projects" for its own sake depends on several uncertain presuppositions: that interdisciplinary knowledge is better knowledge, that disciplines constrain interdisciplinary knowledge, and that interdisciplinary interactions are unconstrained by hierarchies. They believe that each of these assumptions is dubious.

Both books are highly interesting to anyone concerned with the development and growth of scientific knowledge. Once we abandoned the premises of logical positivism, we needed a more sophisticated understanding of how the domain of scientific research, empirical and theoretical, is constituted in actual social institutional settings. How is it that Western biology did better than Lysenko? How can environmental science re-establish its credentials for credibility with an increasingly skeptical public?  How are we to cope with the proliferation of pseudo-science in crucial areas -- health and medicine, climate, the feasibility of human habitation on Mars? Why should we be confident that the institutions of university science, peer review, tier-one journals, and National Academy selection committees succeed in guiding us to better, more veridical understandings of the empirical world around us?

Earlier posts have addressed topics concerning social studies of science; link, link, link.)

A plan for philosophy of social science circa 1976

image: Imre Lakatos

My Ph.D. dissertation in philosophy was written between 1974 and 1977 and was accepted in 1977. The topic was Marx's theory of science as embodied in Capital, and it was one of the early attempts to join an analytical philosophical perspective with careful study of Marx's ideas. The title of the dissertation was Marx's Capital: A Study in the Philosophy of Social Science. The dissertation proposed a different way of attempting to understand Marx, and it also proposed a different approach to developing the philosophy of social science -- an approach that gives greater attention to the details and history of social-science research. This part of the introduction to the dissertation describes the view I then had of the purposes and current deficiencies of the philosophy of science.

Here is an interview published in 2008 in 5 Questions: Philosophy of the Social Sciences, edited by Diego Rios and Christoph Schmidt-Petri, that gives an indication of how this program has developed in my research and writing (link).

The image of Imre Lakatos is used above because his work from the early 1970s was part of the inspiration for the more contextualized and historical view of the philosophy of social science described in this introduction. I found Lakatos much more stimulating than Kuhn in the early 1970s.

The full introduction is posted here. The full dissertation is posted here.

The philosophy of social science

The philosophy of social science is not a particularly strong area within contemporary philosophy. To some degree it suffers from the division between continental and analytic philosophy. Analytic philosophers have stressed the positivist theory of science, and have consequently come to social sciences with some distrust, while continental philosophers have been preoccupied with the relation of social science to philosophy, rather than the more central question of the defining characteristics of social science. Neither approach has been conducive to the project of constructing a viable, systematic, and sympathetic theory of social science. More importantly, however, the philosophy of social science suffers from its proximity to the philosophy of natural science. The analytical theory of science took shape in the hands of philosophers whose primary training was in natural science, and consequently, whose chief examples were drawn from the natural sciences. Philosophers of social science have all too often shown a tendency to merely import into their field the categories and questions formulated with respect to natural science, rather than posing questions and categories more closely tailored to the real outlines of typical social sciences.{6} It may eventually turn out, of course, that all sciences have the same epistemological structure; but that issue ought not be prejudged. The philosophy of social science needs, therefore, to develop a theory of social science which is not parasitic upon theories of natural science.

Ideally, a philosophy of social science ought to contain an analytical theory of social science which directs attention at the particular trouble spots of social knowledge. It ought to include a discussion of the peculiar nature of the subject matter of social science, an account of the characteristics of social explanation, an account of the relation between empirical evidence and theory in social science, and so forth; and more generally, it ought to consist of a set of questions and categories specifically suited to the special problems confronting social explanation and social theory. Contemporary philosophy of social science fails to come forward with such a theory, in large part because it formulates its theory of science in terms of concepts suggested by the philosophy of natural science.

This diagnosis of the weakness of philosophy of social science indicates that the philosophy of natural science bears a large responsibility for that weakness; happily, however, it is now able to provide the beginnings of a method of philosophical inquiry which can begin to undo that damage. For in the past two decades the philosophy of natural science has witnessed an important transformation in its method of inquiry. It has been transformed from an attempt to provide high-level abstractions concerning the basic concepts of explanation, confirmation, empirical significance, theory choice, and the like, to an attempt to provide a more detailed theory of scientific practice through detailed studies of particular examples of scientific inquiry. Historians of science have argued that the philosophy of science will benefit from greater attention to particular scientific theories and programmes of research, and increasingly philosophers have accepted this judgment. And this shift of attention has already begun to pay off in the form of theories of science which correspond more closely to the actual nature of science, and which thereby come closer to explaining science as a form of human knowledge.

I suggest that the philosophy of social science can benefit from the application of this historical method: its theory of social science can be enriched and corrected through closer attention to actual case studies drawn from the history of social science. Such studies have the potential of suggesting new categories and new questions concerning the nature of knowledge about society and history, and they provide the means by which the analytical theory of science itself may be assessed.

We may get a better idea of the logical relations between case studies of that sort and the formulation of a more general theory of science by working out a rough taxonomy of the logical structure of the philosophy of science.{7} The philosophy of science is (at least in part) a meta-level theory of the epistemological, methodological, and structural characteristics of science. If all scientific theories share certain epistemological characteristics in common, these certainly ought to be part of that theory of science; and if there is diversity, the theory of science ought to indicate the dimensions around which such diversity occurs. The theory of science ought to answer questions like: What is scientific explanation? How are scientific theories organized? How are scientific hypotheses given empirical justification? The theory of science, in other words, attempts to codify the most general characteristics of scientific knowledge.

On this account the theory of science stands at the greatest degree of abstraction: it attempts to make assertions which are true of all or most sciences. At the opposite end of the spectrum stands the particular scientific hypothesis or system: Darwinian evolutionary theory, Newtonian mechanics, Piaget’s psychological theory, and so forth. Each such theory is an attempt to apply empirical rationality to the problem of explaining some complex domain of phenomena; and each advances a theory to the scientific community for some form of evaluation or acceptance. The crucial point to note, however, is that each such theory is an extended and complex argument, in which the principles of inference are almost always left unstated. The scientist engages in a complex form of empirical reasoning, but he does not codify that process of reasoning. For each such example of an empirical hypothesis and explanation, therefore, it is possible to attempt to unravel the implicit standards of empirical rationality, or the implicit conceptions of scientific explanation, inference, evidence, and so forth. This process is in large part the domain of the history of science; however, its results are of plain importance to the general theory of science described above. For if we suppose that any scientific theory rests upon a complex and unstated "grammar" of scientific inference and argument, we may sensibly ask whether there are any regularities among those implicit. theories of science. These particular theories of science embody the set of standards of empirical rationality which guide and regulate the particular scientist, and they constitute part of the raw material for the analytical theory of science. They are what the analytical theory of science is a theory of.

Using this basic taxonomy of the philosophy of science, it is possible to restate the innovation in the practice of the philosophy of science which was described above as having occurred of late: historically minded philosophers of science have argued that we ought to make more explicit the relationship between the two levels of theories of science, and ought to pay more attention to the concrete theories of science implicit in particular scientific systems when formulating and criticizing the analytical theory of science. We ought, that is, to formulate an analytical theory of science which is more sensitive to the particular details of the actual practice of scientific explanation and justification, rather than relying on a priori and unsystematic arguments about science in general.

Notes

1. Consider social theorists like Louis Althusser, Nicos Poulantzas, Lucio Coletti, and Maurice Godelier; empirical sociologists like Tom Bottomore, Ralph Miliband, and J. H. Westergaard; economists like Paul Sweezy, Maurice Dobb, and Ernest Mandel; and historians like E. P. Thompson, Eugene Genovese, Eric Hobsbawm, and Albert Soboul.

2. For a description of a similar project in the biological sciences, consult David Hull, Philosophy of Biological Science (Englewood Cliffs, N.J.: Prentice-Hall, 1974), pp. 5-7. Consider also Norwood Hanson, Patterns of Discovery, An Inquiry into the Conceptual Foundations of Science (Cambridge: Cambridge University Press, 1965, p. 2.

3. Louis Althusser and Etienne Balibar, Reading Capital, trans. Ben Brewster (London: New Left Books, 1970), pp. 30-1; Louis Althusser, For Marx, trans. Ben Brewster (London: New Left Books, 1969), pp. 34-5.

4. David McLellan, Karl Marx (New York: Viking Press, 1975), pp. 303-305; Albrecht Wellmer, Critical Theory of Society (New York: Herder & Herder, 1971), Chap. 2; Carl Boggs, Gramsci's Marxism (London: Pluto Press,·1976) Chap. 1.

5. Thomas Kuhn, The Structure of Scientific Revolutions, 2nd ed. ·(Chicago: University of Chicago Press, 1970); Norwood Hanson, Patterns of Discovery; Imre Lakatos, “Methodology of Scientific Research Programmes," Criticism and the Growth of Knowledge, ed. Imre Lakatos & Alan Musgrave (Cambridge: Cambridge University Press, 1970); David Hull, Philosophy of Biological Science. These works share a commitment to constructing a theory of science based on a close reading of some specific scientific theory.

6. Cf. Richard Rudner, Philosophy of Social Science (Englewood Cliffs., N.J.: Prentice-Hall, 1966). This is a good example of such studies.

7. Consider Israel Scheffler, The Anatomy of Inquiry (Indianapolis: Bobbs-Merrill, 1963), pp. 3-15, for a similar discussion and taxonomy of the philosophy of science.