Ludwik Fleck and “thought styles” in science

Let’s think about the intellectual influences that have shaped philosophers of science over the past one hundred years or so: Vienna Circle empiricism, logical positivism, the deductive-nomological method, the Kuhn-Lakatos revolution, incorporation of the sociology of science into philosophy of science, a surge of interest in scientific realism, and an increasing focus on specific areas of science as objects of philosophy of science investigations. And along these waypoints it would be fairly easy to place a few road signs indicating the major philosophers associated with each phase in the story — Ayer, Carnap, Reichenbach, Hempel, Nagel, Hanson, Hesse, Kuhn, Lakatos, Putnam, Boyd, Quine, Sellars, Bhaskar, Sober, Rosenberg, Hausman, Epstein …

So we might get the idea that we’ve got a pretty good idea of the “space” in which philosophy of science questions should be posed, along with a sense of the direction of change and progress that has occurred in the field since 1930. The philosophy of science is a “tradition” within philosophy, and we who practice in the field have a sense of understanding its geography.

But now I suggest that readers examine Wojciech Sady’s excellent article on Ludwik Fleck in the Stanford Encyclopedia of Philosophy (link). Fleck (1896-1961) was a Polish-Jewish scientist and medical researcher who wrote extensively in the 1930s about “social cognition” and what we would now call the sociology of science. His biography is fascinating and harrowing; he and his family survived life in Lvov under the Soviet Union (1939-1941) after the simultaneous invasion of Poland by Germany and the USSR; occupation, pogroms, and capture by the Germans in Lvov; resettlement in the Lvov ghetto; transport to Auschwitz and later Buchenwald; and survival throughout, largely because of his scientific expertise on typhus vaccination. Fleck survived to serve as a senior academic scientist in Lublin. In 1957 Fleck and his wife emigrated to Israel, where their son had settled.

Fleck is not entirely unknown to philosophers today, but it’s a close call. A search for articles on Fleck in a research university search engine produces about 2,500 academic articles; by comparison, the same search results in 183,000 articles on Thomas Kuhn. And I suspect that virtually no philosopher with a PhD from a US department of philosophy since 1970 and with a concentration in the philosophy of science has ever heard of Fleck. 100% of those philosophers, of course, will have a pretty good idea of Kuhn’s central ideas. And yet Fleck has a great deal in common with Kuhn — some three decades earlier. More importantly, many of Fleck’s lines of thought about the history of concepts of disease in medicine are still enormously stimulating, and they represent potential sources of innovation in the field today. Fleck asked very original and challenging questions about the nature of scientific concepts and knowledge. Thomas Kuhn was one of the few historians of science who were aware of Fleck’s work, and he wrote a very generous introduction to the English translation of Fleck’s major book in the sociology and history of science, Genesis and Development of a Scientific Fact (1979/1935).

Here are Fleck’s central ideas, as summarized by Sady. Understanding the world around us (cognition) is a collective project. Individuals interacting with each other about some aspect of the world constitute a “thought collective” — “a community of persons mutually exchanging ideas or maintaining intellectual interaction” (Sady, sect. 3). A thought collective forms a vocabulary and crafts a set of concepts that are mutually understood within the group, but misunderstood by persons outside the group. A “thought collective” forms a “collective bond” — a set of emotions of loyalty and solidarity which Fleck describes as a “collective mood”. There are no “objective facts”; rather, facts are defined by the terms and constructs of the “thought collective”. And the perceptions, beliefs, and representations of different “thought collectives” concerned with ostensibly the same subject matter are incommensurable.

So it is not possible to compare a theory with “reality in itself”. It is true that those who use a thought style give arguments for their views, but those arguments are of restricted value. Any attempt to legitimize a particular view is inextricably bound to standards developed within a given style, and those who accept those standards accept also the style. (Sady, sect. 7)

And scientific knowledge is entirely conditional upon the background structure of the “thought collective” or conceptual framework of the research community:

As Fleck states in the last sentence of (1935b), “’To see’ means: to recreate, at a suitable moment, a picture created by the mental collective to which one belongs”. (Sady, sect. 5)

Thus, it is impossible to see something radically new “simply and immediately”: first the constrains of an old thought style must be removed and a new style must emerge, a collective’s thought mood must change— and this takes time and work with others. (Sady, sect. 5)

These ideas plainly correspond closely to Imre Lakatos’s idea of a research community and Thomas Kuhn’s idea of a paradigm. They stand in striking contrast to the logical positivism of the Vienna Circle being developed at roughly the same time. (And yet Sady notes that Moritz Schlick offered to recommend publication of Genesis and Development of a Scientific Fact in 1934.)

Upon first exposure to Fleck’s ideas from the Sady article I initially assumed that Fleck was influenced by Communist ideas about science and knowledge (as were Polish sociologists and philosophers in the 1950s). The “collective thoughts” that are central to Fleck’s account of the history of science sound a lot like Engels or Lenin. And yet this turns out not to be the case. Nothing in Sady’s article suggests that Fleck was influenced by Polish Communist theory in the 1920s and 1930s. Instead, his ideas about social cognition seem to develop out of a largely central European tradition of thinking about thinking. According to Sady, Fleck’s own “thought collectives” (research traditions) included: (1) medical research; (2) the emerging field in Poland of history of medicine (Władysław Szumowski, Włodzimierz Sieradzki, and Witold Ziembicki); (3) the Polish “philosophical branch” of mathematical-philosophical school (minor); (4) sociology of knowledge (Levy-Bruhl, Wilhelm Jerusalem; but not Max Scheler or Karl Mannheim; also minor). Sady also emphasizes Fleck’s interest in the debates that were arising in physics around the puzzles of quantum mechanics and relativity theory.

So there is a major irony here: one of Fleck’s central ideas is that individual thinkers can achieve nothing by themselves as individuals. And yet Fleck’s ideas as developed in his history of the medical concept of syphilis appear to be largely self-generated — the results of his own knowledge and reflection. The advocate of the necessity of “thought collectives” was himself not deeply integrated into any coherent thought collective.

This story has an important moral. Most importantly, it confirms to me that there are always important perspectives on a given philosophical topic that have fallen outside the mainstream and may be forever forgotten. This suggests the value, for philosophers and other scholars interested in arriving at valuable insights into difficult problems, of paying attention to the paths not taken in previous generations. There is nothing in the nature of academic research that guarantees that “the best ideas of a generation will become part of the canon for the next generation”; instead, many good and original ideas have been lost to the disciplines through bad luck. This is largely true of Fleck.

But here is another, more singular fact that is of interest. How did Sady’s article, and therefore Fleck himself, come to my attention? The answer is that in the past year I’ve been reading a lot about Polish and Jewish intellectuals from the 1930s with growing fascination because of a growing interest in the Holocaust and the Holodomor. That means a lot of searches on people like Janina Bauman, Leszek Kołakowski, and Vasily Grossman. I’ve searched for the histories of places like Lvov, Galicia, and Berdichev. And in the serendipity of casting a wide net, I’ve arrived at the happy experience of reading Sady’s fascinating article, along with some of Fleck’s important work.

Here is the prologue to Fleck’s Genesis and Development of a Scientific Fact. It expresses very concisely Fleck’s perspective on science, concepts, and facts.

What is a fact?

A fact is supposed to be distinguished from transient theories as something definite, permanent, and independent of any subjective interpretation by the scientist. It is that which the various scientific disciplines aim at. The critique of the methods used to establish it constitutes the subject matter of epistemology.

Epistemology often commits a fundamental error: almost exclusively it regards well-established facts of everyday life, or those of classical physics, as the only ones that are reliable and worthy of investigation. Valuation based upon such an investigation is inherently naive, with the result that only superficial data are obtained.

Moreover, we have even lost any critical insight we may once have had into the organic basis of perception, taking for granted the basic fact that a normal person has two eyes. We have nearly ceased to consider this as even knowledge at all and are no longer conscious of our own participation in perception. Instead, we feel a complete passivity in the face of a power that is independent of us; a power we call “existence” or “reality.” In this respect we behave like someone who daily performs ritual or habitual actions mechanically. These are no longer voluntary activities, but ones which we feel compelled to perform to the exclusion of others. A better analogy perhaps is the behavior of a person taking part in a mass movement. Consider, for instance, a casual visitor to the Stock Exchange, who feels the panic selling in a bear market as only an external force existing in reality. He is completely unaware of his own excitement in the throng and hence does not realize how much he may be contributing to the general state. Long-established facts of everyday life, then, do not lend themselves to epistemological investigation.

As for the facts of classical physics, here too we are handicapped by being accustomed to them in practice and by the facts themselves being well worn theoretically. I therefore believe that a “more recent fact,” discovered not in the remote past and not yet exhausted for epistemological purposes, will conform best to the principles of unbiased investigation. A medical fact, the importance and applicability of which cannot be denied, is particularly suitable, because it also appears to be very rewarding historically and phenomenologically. I have therefore selected one of the best established medical facts: the fact that the so-called Wassermann reaction is related to syphilis.

HOW, THEN, DID THIS EMPIRICAL FACT ORIGINATE AND IN WHAT DOES IT CONSIST?

Lvov, Poland, summer 1934

Decision-making for big physics

Big science is largely dominant in many areas of science — for example, high-energy physics, medical research, the human genome project, and pandemic research. Other areas of science still function well in a “small science” framework — mathematics, evolutionary biology, or social psychology, for example, with a high degree of decentralized decision-making by individual researchers, universities, and laboratories. But in areas where scientific research requires vast investments of public funds over decades, we are forced to ask a hugely important question: Can governmental agencies act rationally and intelligently in planning for investments in “big science”?

Consider the outcome we would like to see: adoption of a well-funded and well-coordinated multi-investigator, multi-institutional, multi-year research effort well designed to achieve important scientific results. This is the ideal result. What is required in order to make it a reality? Here are the key activities of information-gathering and decision-making that are needed in order to arrive at a successful national agenda for an area of big-science research.

  1. selection of one or more research strategies that have the best likelihood of bringing about important scientific results
  2. a budgeting process and series of decisions that make these strategies feasible
  3. implementation of a multi-year plan (often over multiple research sites) implementing the chosen strategy
  4. oversight and management of the scientific research sites and expenditures to ensure that the strategy is faithfully carried out by talented scientists, researchers, and directors

In A New Social Ontology of Government: Consent, Coordination, and Authority I argue that governments, agencies, and large private organizations have a great deal of difficulty in carrying out large, extended plans. There I highlight principal-agent problems, conflicting priorities across sub-groups, faulty information sharing, and loose coupling within a large organization as some of the primary sources of dysfunction within a large organization (including a national government or large governmental agency). And it is apparent that all of these sources of dysfunction are present in the process of designing, funding, and managing a national science agenda.

Consider item 1 above: selection of a research strategy for scientific research. At any given time in the development of a field of research there is a body of theory and experimental findings that constitute what is currently known; there are experts (scientists) who have considered judgments about what the most important unanswered questions are, and what technologies or experimental investments would be most productive in illuminating those questions; and there are influential figures within government and industry who have preferences and beliefs about the direction that future research ought to take. 

Suppose government has created an agency — call it the Office of High Energy Physics — which is charged to arrive at a plan for future directions and funding for research in the field of high energy physics. (There is in fact the Office of High Energy Physics located within the Department of Energy which has approximately this responsibility. But here I am considering a hypothetical agency.) How should the director and senior staff of OHEP proceed? 

They will recognize that they need rigorous and developed analysis from a group of senior physicists. The judgments of the best physicists in the national research and university community are surely the best (though fallible) source of guidance about the direction that future physics research should take. So OHEP constitutes a permanent committee of advisors who are tasked to assess the current state of the field and arrive at a consensus view of the most productive direction for future investments in high-energy physics research.

The Standing Scientific Committee is not a decision-making committee, however; rather, it prepares reports and advice for the senior staff and director of OHEP. And the individuals who make up the senior staff themselves have been selected for having a reasonable level of scientific expertise; further, they have their own “pet” projects and ideas about what topics are likely to be the most important. So the senior staff and the Standing Committee are in a complex relationship with each other. The Standing Scientific Committee collectively has greater intellectual authority in the scientific field; many are Nobel-quality physicists. But the senior staff have greater influence on the decisions that the Office makes about strategies and future plans. The staff are always there, whereas the Standing Committee does its work episodically. Moreover, the senior staff has an ability to influence the deliberations of the Standing Committee in a variety of ways, including setting the agenda of the Standing Committee, giving advice about the likelihood of funding of various possible strategies, and so forth. Finally, it is worth noting that a group of twenty senior physicists from a range of institutions throughout the country are likely to have interests of their own that will find their way into the deliberations, leading to disagreements about priorities. In short, the process of designing a plan for the next ten years of investments in high-energy physics research is not a purely rational and scientific exercise; it is also a process in which interests, influence, and bureaucratic manipulation play crucial roles.

Now turn to item 2 above, the budgeting issue. Decisions about funding of fundamental scientific research result from a political, legislative, and bureaucratic process. Congressional committees will be involved in the decision whether to allocate $5 billion, $10 billion, or $15 billion in high-energy physics research in the coming decade. And Congressional committees have their own sources of bias and dysfunction: legislators’ political interests in their districts, relationships with powerful industries and lobbyists, and ideological beliefs that legislators bring to their work. These political and economic interests may influence the legislative funding process to favor one strategy over another — irrespective of the scientific merits of the alternatives. (If one strategy brings more investment to the home state of a powerful Senator, this may tilt the funding decision accordingly.) Further, the system of Congressional staff work can be further analyzed in terms of the interests and priorities of the senior staffers doing the work — leading once again to the likelihood that funding decisions will be based on considerations other than the scientific merits of various strategies for research. (Recall the debacle of Congressional influence on the Osprey VTOL aircraft development process.) 

Items 3 and 4 introduce a new set of possible dysfunctions into the process, through the likelihood of principal-agent problems across research sites. Directors of the National Laboratories (like Fermilab or Lawrence Berkeley National Laboratory, for example) have their own interests and priorities, and they have a fairly wide range of discretion in decisions about implementation of national research priorities. So securing coordination of research efforts across laboratories and research sites introduces another source of uncertainty in the implementation and execution of a national strategy for physics research. This is an instance of “loose coupling”, a factor that has led organizational theorists to come to expect a fair degree of divergence across the large network of sub-organizations that make up the national research system. Thomas Hughes considers these kinds of problems in Rescuing Prometheus: Four Monumental Projects That Changed the Modern Worldlink

These observations do not imply that rational science policy is impossible; but they do underline the difficulties that arise within normal governmental and private institutions that interfere with the idealized process of selection and implementation of an optimal strategy of scientific research. The colossal failure of the Superconducting Super Collider — a multi-billion dollar project in high-energy physics that was abandoned in 1993 after many years of development and expenditure — illustrates the challenges that national science planning encounters (link). Arguably, one might hold that the focus at Fermilab on neutrino detection is another failure (DUNE) — not because it was not implemented, but because it fails the test of making possible fundamental new discoveries in physics.Several interdisciplinary fields take up questions like these, including Science and Technology Studies and Social Construction of Technology studies. Hackett, Amsterdamska, Lynch, and Wajcman’s Handbook of Science and Technology Studies provides a good exposure to the field. Here is a prior post that attempts to locate big science within an STS framework. And here is a post on STS insights into science policy during the Cold War (link).

Vienna Circle in Emerson Hall

I am enjoying reading David Edmonds’ The Murder of Professor Schlick: The Rise and Fall of the Vienna Circle, which is interesting in equal measures in its treatment of the rise of fascism in Austria and Germany, the development of the Vienna Circle, and — of course — the murder of Schlick. Edmonds’ presentation of the philosophical issues that drove the Vienna Circle is especially good. (Here is a link to an earlier discussion of Schlick’s murder; link.) 

In addition to the narrative, the book contains some very interesting photographs of most of the participants in the Vienna Circle. One of those is this image, captioned “Otto Neurath chatting to Alfred Tarski”. The caption does not include information about date or location.

1939

The photo immediately struck me as familiar. It seemed to be the side entrance to Emerson Hall, home of the philosophy department at Harvard. So I did some searching on the web and found that there was a meeting of the International Congress for the Unity of Science (the descendent of the Vienna Circle), which took place at Harvard September 3-9, 1939. This was the fifth and final congress. And both Neurath and Tarski were in attendance. It seems likely enough, then, that this photo is from the 1939 gathering at Harvard. Here is Gerald Holton’s list of the attendees and presenters at the Congress (Science and Anti-Science):

I located a photo taken of that entrance to Emerson Hall just a few years ago:

2017

Here is a version of that image, cropped to roughly the proportions of the 1939 photo. 

2017

I’m convinced — this certainly looks like the same location to me. Harvard has made some improvements on the entrance since 1939 — the door is modernized, the lamps have been added, the vines have been pruned, and the handrails have been provided. The shape of the brick columns to the sides of the entrance is visible through the vines in the 1939 photo. I seem to remember luxuriant vines from the 1970s on that face of the building. And indeed, that is true. Here is a segment of a photo of the same entrance from 1973, and it shows the vines are more extensive. (Also there are no handrails.)

1973

But one challenge remains: is it possible to identify other people in the 1939 photo? Here is a possibility: I think Quine is one of the people in the photo. Here is Quine as I remember him from 1973:

But his looks changed dramatically from his 30s to his sixties and seventies. Here is Quine as photographed in the Edmonds book from the 1930s:

Finally here is Quine in a book cover photo, evidently taken in the 1940s:

 This looks a lot like the man standing directly behind Tarski in the first photo (above Tarski’s head). The giveaway is the pattern baldness visible in the 1939 photo and the book jacket photo. It is hard to be sure, of course, but the similarity is striking.

Are there any other familiar faces in the photo? Carnap was present at the Congress and was close to Quine, but none of the faces I see in the photo look much like Carnap. I am especially curious about the man standing behind Neurath and talking with the person I take to be Quine.

This is all very interesting to me, for a number of reasons. I was a graduate assistant to Quine in his undergraduate course on “Methods of Logic,” and I took his course on Word and Object in 1973 or so. It is striking today to realize that Quine in 1973 was closer in time to the Vienna Circle in the 1930s (35-40 years) than we are today to Quine and Goodman in the 1970s in Emerson Hall (45-50 years). In a small way this illustrates a meaningful point that Marc Bloch makes about the philosophy of history: we are connected to events in the past through meaningful chains of relationships with other human beings. 

STS and big science

A previous post noted the rapid transition in the twentieth century from small physics (Niels Bohr) to large physics (Ernest Lawrence). How should we understand the development of scientific knowledge in physics during this period of rapid growth and discovery?

One approach is through the familiar methods and narratives of the history of science. Researchers in the history of science generally approach the discipline from the point of view of discovery, intellectual debate, and the progress of scientific knowledge. David Cassidy’s book  Beyond Uncertainty: Heisenberg, Quantum Physics, and The Bomb is sharply focused on the scientific and intellectual debates in which Heisenberg was immersed during the development of quantum theory. His book is fundamentally a narrative of intellectual discovery. Cassidy also takes on the moral-political issue of serving a genocidal state as a scientist; but this discussion has little to do with the history of science that he offers. Peter Galison is a talented and imaginative historian of science, and he asks penetrating questions about how to explain the advent of important new scientific ideas. His treatment of Einstein’s theory of relativity in Einstein’s Clocks and Poincare’s Maps: Empires of Time, for example, draws out the importance of the material technology of clocks and the intellectual influences that flowed through the social networks in which Einstein was engaged for Einstein’s basic intuitions about space and time. But Galison too is primarily interested in telling a story about the origins of intellectual innovation.

It is of course valuable to have careful research studies of the development of science from the point of view of the intellectual context and concepts that influenced discovery. But fundamentally this approach leaves largely unexamined the difficult challenge: how do social, economic, and political institutions shape the direction of science?

The interdisciplinary field of science, technology, and society studies (STS) emerged in the 1970s as a sociological discipline that looked at laboratories, journals, and universities as social institutions, with their own interests, conflicts, and priorities. Hackett, Amsterdamska, Lynch, and Wajcman’s Handbook of Science and Technology Studies provides a good exposure to the field. The editors explain that they consulted widely across researchers in the field, and instead of a unified and orderly “discipline” they found many cross-cutting connections and concerns.

What emerged instead is a multifaceted interest in the changing practices of knowledge production, concern with connections among science, technology, and various social institutions (the state, medicine, law, industry, and economics more generally), and urgent attention to issues of public participation, power, democracy, governance, and the evaluation of scientific knowledge, technology, and expertise. (kl 98)

The guiding idea of STS is that science is a socially situated human activity, embedded within sets of social and political relations and driven by a variety of actors with diverse interests and purposes. Rather than imagining that scientific knowledge is the pristine product of an impersonal and objective “scientific method” pursued by selfless individuals motivated solely by the search for truth, the STS field works on the premise that the institutions and actors within the modern scientific and technological system are unavoidably influenced by non-scientific interests. These include commercial interests (corporate-funded research in the pharmaceutical industry), political interests (funding agencies that embody the political agendas of the governing party), military interests (research on fields of knowledge and technological development that may have military applications), and even ideological interests (Lysenko’s genetics and Soviet ideology). All of these different kinds of influence are evident in Hiltzik’s account in Big Science: Ernest Lawrence and the Invention that Launched the Military-Industrial Complex of the evolution of the Berkeley Rad Lab, described in the earlier post.

In particular, individual scientists must find ways of fitting their talents, imagination, and insight into the institutions through which scientific research proceeds: universities, research laboratories, publication outlets, and sources of funding. And Hiltzik’s book makes it very clear that a laboratory like the Radiation Lab that Lawrence created at the University of California-Berkeley must be crafted and designed in a way that allows it to secure the funds, equipment, and staff that it needs to carry forward the process of fundamental research, discovery, and experimentation that the researchers and the field of high-energy physics wished to conduct.

STS scholars sometimes sum up these complex social processes of institutions, organizations, interests, and powers leading to scientific and technological discovery as the “social construction of technology” (SCOT). And, indeed, both the course of physics and the development of the technologies associated with advanced physics research were socially constructed — or guided, or influenced — throughout this extended period of rapid advancement of knowledge. The investments that went into the Rad Lab did not go into other areas of potential research in physics or chemistry or biology; and of course this means that there were discoveries and advances that were delayed or denied as a result. (Here is a recent post on the topic of social influences on the development of technology; link.)

The question of how decisions are made about major investments in scientific research programs (including laboratories, training, and cultivation of new generations of science) is a critically important one. In an idealized way one would hope for a process in which major multi-billion dollar and multi-decade investments in specific research programs would be made in a rational way, incorporating the best judgments and advice of experts in the relevant fields of science. One of the institutional mechanisms through which national science policy is evaluated and set is the activity of the National Academy of Science, Engineering, and Medicine (NASEM) and similar expert bodies (link). In physics the committees of the American Physical Society are actively engaged in assessing the present and future needs of the fundamental science of the discipline (link). And the National Science Foundation and National Institutes of Health have well-defined protocols for peer assessment of research proposals. So we might say that science investment and policy in the US have a reasonable level of expert governance. (Here is an interesting status report on declining support for young scientists in the life sciences in the 1990s from an expert committee commissioned by NASEM (link). This study illustrates the efforts made by learned societies to assess the progress of research and to recommend policies that will be needed for future scientific progress.)

But what if the institutions through which these decisions are made are decidedly non-expert and bureaucratized — Congress or the Department of Energy, for example, in the case of high-energy physics? What if the considerations that influence decisions about future investments are importantly directed by political or economic interests (say, the economic impact of future expansion of the Fermilab on the Chicago region)? What if companies that provide the technologies underlying super-conductor electromagnets needed for one strategy but not another are able to influence the decision in their favor? What are the implications for the future development of physics and other areas of science of these forms of non-scientific influence? (The decades-long case of the development of the V-22 Osprey aircraft is a case in point, where pressures on members of Congress from corporations in their districts led to the continuation of the costly project long after the service branches concluded it no longer served the needs of the services; link.)

Research within the STS field often addresses these kinds of issues. But so do researchers in organizational studies who would perhaps not identify themselves as part of the STS field. There is a robust tradition within sociology itself on the sociology of science. Robert Merton was a primary contributor with his book The Sociology of Science: Theoretical and Empirical Investigations (link). In organizational sociology Jason Owen-Smith’s recent book Research Universities and the Public Good: Discovery for an Uncertain Future provides an insightful analysis of how research universities function as environments for scientific and technological research (link). And many other areas of research within contemporary organizational studies are relevant as well to the study of science as a socially constituted process. A good example of recent approaches in this field is Richard Scott and Gerald Davis, Organizations and Organizing: Rational, Natural and Open Systems Perspectives.

The big news for big science this week is the decision by CERN’s governing body to take the first steps towards establishment of the successor to the Large Hadron Collider, at an anticipated cost of 21 billion euros (link). The new device would be an electron-positron collider, with a plan to replace it later in the century with a proton-proton collider. Perhaps naively, I am predisposed to think that CERN’s decision-making and priority-setting processes are more fully guided by scientific consensus than is the Department of Energy’s decision-making process. However, it would be very helpful to have in-depth analysis of the workings of CERN, given the key role that it plays in the development of high-energy physics today. Here is an article in Nature reporting efforts by social-science observers like Arpita Roy, Knorr Cetina, and John Krige to arrive at a more nuanced understanding of the decision-making processes at work within CERN (link).

Big physics and small physics

When Niels Bohr traveled to Britain in 1911 to study at the Cavendish Laboratory at Cambridge, the director was J.J. Thompson and the annual budget was minimal. In 1892 the entire budget for supplies, equipment, and laboratory assistants was a little over about £1400 (Dong-Won Kim, Leadership and Creativity: A History of the Cavendish Laboratory, 1871-1919 (Archimedes), p. 81). Funding derived almost entirely from a small allocation from the University (about £250) and student fees deriving from lectures and laboratory use at the Cavendish (about £1179). Kim describes the finances of the laboratory in these terms:

Lack of funds had been a chronic problem of the Cavendish Laboratory ever since its foundation. Although Rayleigh had established a fund for the purchase of necessary apparatus, the Cavendish desperately lacked resources. In the first years of J.J.’s directorship, the University’s annual grant to the laboratory of about £250 did not increase, and it was used mainly to pay the wages of the Laboratory assistants (£214 of this amount, for example, went to salaries in 1892). To pay for the apparatus needed for demonstration classes and research, J.J. relied on student fees. 

Students ordinarily paid a fee of £1.1 to attend a lecture course and a fee of £3.3 to attend a demonstration course or to use space in the Laboratory. As the number of students taking Cavendish courses increased, so did the collected fees. In 1892, these fees totaled £1179; in 1893 the total rose a bit to £1240; and in 1894 rose again to £1409. Table 3.5 indicates that the Cavendish’s expenditures for “Apparatus, Stores, Printing, &c.” (£230 3s 6d in 1892) nearly equaled the University’s entire grant to the Cavendish (£254 7s 6d in 1892). (80)

The Cavendish Laboratory exerted great influence on the progress of physics in the early twentieth century; but it was distinctly organized around a “small science” model of research. (Here is an internal history of the Cavendish Lab; link.) The primary funding for research at the Cavendish came from the university itself, student fees, and occasional private gifts to support expansion of laboratory space, and these funds were very limited. And yet during those decades, there were plenty of brilliant physicists at work at the Cavendish Lab. Much of the future of twentieth century physics was still to be written, and Bohr and many other young physicists who made the same journey completely transformed the face of physics. And they did so in the context of “small science”.

Abraham Pais’s intellectual and scientific biography of Bohr, Niels Bohr’s Times: In Physics, Philosophy, and Polity, provides a detailed account of Bohr’s intellectual and personal development. Here is Pais’s description of Bohr’s arrival at the Cavendish Lab:

At the time of Bohr’s arrival at the Cavendish, it was, along with the Physico-Technical Institute in Berlin, one of the world’s two leading centers in experimental physics research. Thomson, its third illustrious director, successor to Maxwell and Rayleigh, had added to its distinction by his discovery of the electron, work for which he had received the Nobel Prize in 1906. (To date the Cavendish has produced 22 Nobel laureates.) In those days, ‘students from all over the world looked to work with him… Though the master’s suggestions were, of course, most anxiously sought and respected, it is no exaggeration to add that we were all rather afraid he might touch some of our apparatus.’ Thomson himself was well aware that his interaction with experimental equipment was not always felicitous: ‘I believe all the glass in the place is bewitched.’ … Bohr knew of Thomson’s ideas on atomic structure, since these are mentioned in one of the latter’s books which Bohr had quoted several times in his thesis. This problem was not yet uppermost in his mind, however, when he arrived in Cambridge. When asked later why he had gone there for postdoctoral research he replied: ‘First of all I had made this great study of the electron theory. I considered… Cambridge as the center of physics and Thomson as a most wonderful man.’ (117, 119)

On the origins of his theory of the atom:

Bohr’s 1913 paper on α-particles, which he had begun in Manchester, and which had led him to the question of atomic structure, marks the transition to his great work, also of 1913, on that same problem. While still in Manchester, he had already begun an early sketch of these entirely new ideas. The first intimation of this comes from a letter, from Manchester, to Harald: ‘Perhaps I have found out a little about the structure of atoms. Don’t talk about it to anybody… It has grown out of a little information I got from the absorption of α-rays.’ (128)

And his key theoretical innovation:

Bohr knew very well that his two quoted examples had called for the introduction of a new and as yet mysterious kind of physics, quantum physics. (It would become clear later that some oddities found in magnetic phenomena are also due to quantum effects.) Not for nothing had he written in the Rutherford memorandum that his new hypothesis ‘is chosen as the only one which seems to offer a possibility of an explanation of the whole group of experimental results, which gather about and seems to confirm conceptions of the mechanismus [sic] of the radiation as the ones proposed by Planck and Einstein’. His reference in his thesis to the radiation law concerns of course Planck’s law (5d). I have not yet mentioned the ‘calculations of heat capacity’ made by Einstein in 1906, the first occasion on which the quantum was brought to bear on matter rather than radiation. (138)

But here is the critical point: Bohr’s pivotal contributions to physics derived from exposure to the literature in theoretical physics at the time, his own mathematical analysis of theoretical assumptions about the constituents of matter, and exposure to laboratories whose investment involved only a few thousand pounds.

Now move forward a few decades to 1929 when Ernest Lawrence conceived of the idea of the cyclical particle accelerator, the cyclotron, and soon after founded the Radiation Lab at Berkeley. Michael Hiltzik tells this story in Big Science: Ernest Lawrence and the Invention that Launched the Military-Industrial Complex, and it is a very good case study documenting the transition from small science to big science in the United States. The story demonstrates the vertiginous rise of large equipment, large labs, large funding, and big science. And it demonstrates the deeply interwoven careers of fundamental physics and military and security priorities. Here is a short description of Ernest Lawrence:

Ernest Lawrence’s character was a perfect match for the new era he brought into being. He was a scientific impresario of a type that had seldom been seen in the staid world of academic research, a man adept at prying patronage from millionaires, philanthropic foundations, and government agencies. His amiable Midwestern personality was as much a key to his success as his scientific genius, which married an intuitive talent for engineering to an instinctive grasp of physics. He was exceptionally good-natured, rarely given to outbursts of temper and never to expressions of profanity. (“ Oh, sugar!” was his harshest expletive.) Raising large sums of money often depended on positive publicity, which journalists were always happy to deliver, provided that their stories could feature fascinating personalities and intriguing scientific quests. Ernest fulfilled both requirements. By his mid-thirties, he reigned as America’s most famous native-born scientist, his celebrity validated in November 1937 by his appearance on the cover of Time over the cover line, “He creates and destroys.” Not long after that, in 1939, would come the supreme encomium for a living scientist: the Nobel Prize. (kl 118)

And here is Hiltzik’s summary of the essential role that money played in the evolution of physics research in this period:

Money was abundant, but it came with strings. As the size of the grants grew, the strings tautened. During the war, the patronage of the US government naturally had been aimed toward military research and development. But even after the surrenders of Germany and Japan in 1945, the government maintained its rank as the largest single donor to American scientific institutions, and its military goals continued to dictate the efforts of academic scientists, especially in physics. World War II was followed by the Korean War, and then by the endless period of existential tension known as the Cold War. The armed services, moreover, had now become yoked to a powerful partner: industry. In the postwar period, Big Science and the “military-industrial complex” that would so unnerve President Dwight Eisenhower grew up together. The deepening incursion of industry into the academic laboratory brought pressure on scientists to be mindful of the commercial possibilities of their work. Instead of performing basic research, physicists began “spending their time searching for ways to pursue patentable ideas for economic rather than scientific reasons,” observed the historian of science Peter Galison. As a pioneer of Big Science, Ernest Lawrence would confront these pressures sooner than most of his peers, but battles over patents—not merely what was patentable but who on a Big Science team should share in the spoils—would soon become common in academia. So too would those passions that government and industry shared: for secrecy, for regimentation, for big investments to yield even bigger returnsParticle accelerators became the critical tool in experimental physics. A succession of ever-more-powerful accelerators became the laboratory apparatus through which questions and theories being developed in theoretical physics could be pursued by bombarding targets with ever-higher energy particles (protons, electrons, neutrons). Instead of looking for chance encounters with high-energy cosmic rays, it was possible to use controlled processes within particle accelerators to send ever-higher energy particles into collisions with a variety of elements. (kl 185)

What is intriguing about Hiltzik’s story is the fascinating interplay of separate factors the narrative invokes: major developments in theoretical physics (primarily in Europe), Lawrence’s accidental exposure to a relevant research article, the personal qualities and ambition of Lawrence himself, the imperatives and opportunities for big physics created by atomic bomb research in the 1940s, and the institutional constraints and interests of the University of California. This is a story of the advancement of physics that illustrates a huge amount of contingency and path dependency during the 1930s through 1950s. The engineering challenges of building and maintaining a particle accelerator were substantial as well, and if those challenges could not be surmounted the instrument would be impossible. (Maintaining a vacuum in a super-large canister itself proved to be a huge technical challenge.)

Physics changed dramatically between 1905 and 1945, and the balance between theoretical physics and experimental physics was one important indicator of this change. And the requirements of experimental physics went from the lab bench to the cyclotron — from a few hundred dollars (pounds, marks, krone, euros) of investment to hundreds of millions of dollars (and now billions) in investment. This implied, fundamentally, that scientific research evolved from an individual activity taking place in university settings to an activity involving the interests of the state, big business, and the military — in addition to the scientific expertise and imagination of the physicists.

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: linklink. 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).)

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.

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.
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