(Web Exclusive) On the Subject of Science and the Humanities in Anthropology

ON THE SUBJECT OF SCIENCE AND THE HUMANITIES IN ANTHROPOLOGY1

Lars Fogelin School of Anthropology University of Arizona

[email protected]

Unpublished Manuscript: 2015 For more than a century, philosophers of science, scientists, and humanist critics of science have viewed methods of reasoning as the defining element of science. Debate occurs because scientists believe they follow methods of reasoning that are distinct from the humanities, while many humanists believe that scientific methods are just as historically contingent and subject to the vagaries of bias as any humanistic methods. Thus, the entire debate concerning science is fought within the domain of methods. Contrary to this methodological understanding of science, I propose that scientists study phenomena governed by regular or largely regular processes, while humanists study human phenomena governed by somewhat regular processes. As for the methods, they are of secondary importance to subject matter and should be determined based upon the regularity of processes being studied. In this formulation, the sciences and humanities can be brought together under a larger rubric that accommodates the reasoning systems of each.

Original Wording The purposes of the Association shall be to advance anthropology as the science that studies humankind in all its aspects, … Revised Wording (November 2010) The purposes of the Association shall be to advance public understanding of humankind in all its aspects.

American Anthropology Association Long-Range Plan: Mission Statement

In 2010, a dustup erupted among anthropologists over the role of science in the discipline. At the

American Anthropology Association (AAA) Meetings in New Orleans, the Executive Board adopted a new mission statement for its Long-Range Plan (Dominguez et al. 2010). The Board changed the purpose of the Association from “advanc[ing] anthropology as the science that studies humankind” to “advanc[ing] public understanding of humankind.” Subsequently, the Society for Anthropological Sciences passed a resolution condemning the change (Peregrine 2010), and the new mission statement became to subject to criticism and debate on anthropology blogs and even in the New York Times (Wade 2010).

1 Despite my best efforts, I have been unable to find a venue to publish this paper. I am making it available on Academia.edu because I believe it has value in understanding current debates over science in anthropology. If you find the arguments interesting, please feel free to pass the manuscript along. I thank the many colleagues, students and friends who have helped me with this paper over the years. They remain nameless to protect the innocent.

2 Fogelin: On the Subject of Science and the Humanities in Anthropology

Anthropological scientists’ criticisms of the changes to the mission statement by followed two paths. The first objection was shifting the goal of the organization from “study[ing] humankind” to “advance[ing] public understanding of humankind.” While interesting, this issue does not concern the arguments presented here. The second objection concerned the deletion of the word “science” from the mission statement and the implication that the AAA no longer welcomed anthropological scientists.

In my view, the original version of the mission statement was factually wrong. Anthropology is not, and never was, solely a scientific discipline. Since the inception of the discipline in the 19th century, anthropologists have employed both scientific and humanistic approaches. As such, the old mission statement denied a significant portion of the membership of the AAA their anthropological bona fides. The new mission statement, on the other hand, does not specify how to study humankind, allowing any humanistic, scientific, or other approach as long it allows for the “understanding of humankind.” In that sense, the revised mission statement is more inclusive. Subsequent statements by those involved in crafting the mission statement confirm that they intended the new definition to encompass science, and did not view the statement as problematic (Dominguez 2010; Dominguez et al. 2010).2

Given the history of contestation over science within anthropology, however, many anthropological scientists initially saw the revision of the mission statement as yet another maneuver by radical humanists to force scientists out of anthropology. For example, in a comment on the AAA blog addressing the change, Jerry Moore (2010) stated that:

The AAA Executive Board’s actions are widely perceived as an act of domination by one branch of socio-cultural anthropology, an action that implicitly excludes archaeology, biological anthropology, and other scientific branches of anthropology.

There is a wide body of theory that could be applied to an examination of Moore’s claims. Ironically,

this contested history would be best examined through questions of historical contingency, social memory, identity, and power—all approaches developed and used by more humanistic anthropologists. But it is not my goal to examine the debates over science in this way. Rather, I am more interested in why scientists believe it is necessary to include the word “science” in the mission statement in the first place.

The debate over the omission of science in anthropological blogs throws into high relief common assumptions that scientists and humanists bring to their investigations, assumptions that are rarely explicitly stated in anthropological articles and books. I suggest that the Sturm and Drang over the mission statement arose partly from a fundamental misunderstanding of science by scientists themselves—that science is a method, a system of reasoning, and an overarching approach to the study of empirical phenomena. Evidence of this misunderstanding can be found in the reactions of scientists to the changes in the AAA mission statement.

[Science] refers to a careful research methodology, a questioning of one’s assumptions (including assumptions of objectivity), and providing supporting evidence for conclusions or insights developed during research. The term does not limit the content of research. (Adra 2010)

2 The intent of the AAA executive board is shown by a new statement on “What is Anthropology,” amended and approved on the same day as the Long-Range Plan (AAA 2010).

Anthropology is the study of humans, past and present. To understand the full sweep and complexity of cultures across all of human history, anthropology draws and builds upon knowledge from the social and biological sciences as well as the humanities and physical sciences.


Through science we produce a particular body of knowledge about phenomena we observe or infer from observations and this body of knowledge can be distinguished from other bodies of knowledge by the requirement that it be subjected to unconstrained challenge as to its veracity and to its claims. (Read 2010)

For scientists, science is not primarily defined by what it studies, but rather by the way that scientists

go about studying it. In this light, anthropological scientists’ concern over the removal of science from the mission statement becomes understandable. The most important elements of science for anthropological scientists—scientific methods—were removed.

In an attempt to produce a more inclusive mission statement, many anthropologists proposed modifying the definition to read “the scientific and humanistic study of humankind.” In truth, however, many anthropological scientists only grudgingly accept that humanists employ rigorous methods of reasoning. They accept that many anthropologists are humanists, but they are not entirely happy with the way that humanists go about their research.

Rather than trying to eliminate science from the field of anthropology…, it would be much better if [sociocultural anthropologists] would work on developing their own clear meaningful criteria that could be used to judge the quality of their work, rather than referring to some vague ideas of public acceptance. (Dow 2010)

Most scientists have no clear idea what methods of reasoning humanist anthropologists employ, most

likely because these days few humanists really know either. This is not to say that humanist anthropologists don’t have methods. They do. Humanistic anthropologists employ participant observation and linguistic content analysis, for example. But humanist methods are not equivalent to the methods of reasoning scientists define themselves by, but rather are similar to the day-to-day scientific methods of microscopy or principle component analysis. Rather than rely on strict methods of reasoning, humanistic anthropologists employ a wide-range of looser approaches to investigate and interpret the people they study. This methodological fluidity irks many scientists. Without common, effective, and accepted methods of reasoning, how, scientists wonder, can anyone rely on the conclusions of humanists?

All of this can explain why many anthropological scientists were angered by the omission of science in the mission statement, and the seeming confusion of anthropological humanists as to what the big deal was. What is surprising, however, is how rarely debates over science create genuine ruptures among practicing anthropologists. While scientists may privilege methods of reasoning and humanists may not, judging by the frequency of comments in the subsequent debate, most anthropologists are happy to combine both within an overarching holistic discipline. From this view, anthropology is a large, dysfunctional family. I suggest, however, that like many family squabbles, the arguments over science are based on a long-forgotten misunderstanding.

The Subject Matter of Science and the Humanities

But in all our speculations concerning nature, what we have to consider is the general rule; for that is natural which applies either universally or for the most part.

Aristotle (2001[Parts of Animals III, 663b28-30]) I propose that more than a century ago, philosophers of science made a fundamental mistake, a

mistake that has bedeviled debates over science ever since. In an attempt to isolate the critical elements


that led to the success of science, philosophers of science identified methods of reasoning as the critical and defining elements of science. Further, I suggest that this methodological conception of science has been damaging to the practice of both the sciences and the humanities ever since.

Today humanists and scientists have become locked into interminable debates by a methodological conception of science that both share. That is, almost all anthropologists accept that the key attribute of science is its commitment to methods of reasoning. The fault line occurs because scientists believe they follow methods of reasoning that are distinct from the humanities, while humanists believe that scientific methods are just as historically contingent and subject to the vagaries of bias as any humanistic methods. Thus, the entire debate concerning science is fought within the domain of methods. But if methods are not the defining element of science, the current debate is beside the point.

Contrary to the prevailing methodological conception of science, I suggest that science is best defined by what it studies. Drawing from Aristotle, I identify the subject of science as phenomena governed by regular or largely regular processes. The subject matter of the humanities, in contrast, is human phenomena governed by somewhat regular processes. As for the methods of science and the humanities, they are of secondary importance to the subject matter, and should be determined based upon the regularity of processes being studied. By restoring the primacy of subject matter, I propose that the sciences and humanities can be brought under a larger rubric that accommodates the reasoning systems of each.

A critical element of this definition of science is that it refers to the regularity of the processes governing phenomena, not just the phenomena themselves. I use this phraseology to avoid the pitfall that all phenomena are, in some sense, unique. For example, while no two objects have the exact same mass, they are equally subject to the force of gravity. The same can be said of human processes. The incest taboo is a process implicated in the specific occurrences of incest, the sanctions against those who engage in incest, and exceptions to the incest taboo. By emphasizing the underlying processes rather than the phenomena being studied, this definition avoids the mistake of saying that scientists and humanists cannot study unique phenomena.3 Following the approach advocated in this paper, scientists and humanists can study unique phenomena, precisely because they can discover the processes that govern those phenomena.

While philosophers of science have not, to the best of my knowledge, previously suggested privileging subject matter over method, the ideas presented here are clearly drawn from the insights of pragmatic philosophers like Peirce (1931), Dewey (1929) and Rorty (1982). Like most pragmatic philosophers, I begin with the assumption that all knowledge claims are potentially false and that all who make them are fallible. As there is no way to be certain of the truth of a knowledge claim, I seek instead to identify the systems of reasoning that are most effective for investigating and understanding the world.

The characteristic idea of philosophical pragmatism is that efficacy in practical application—the issue of ‘which works out most effectively’—somehow provides the standard for the determination of truth in the case of statements, rightness in the case of actions, and value in the case of appraisals. (Rescher 1995:710)

I also lean toward realism (Putnam 1983). That is, my knowledge claims about the world could not be

wrong unless, to some degree, there are independent phenomena for me to be wrong about. Pragmatists never assert that their knowledge claims concerning the real world are unalterably true, only that they most effectively explain phenomena given current knowledge. In essence, pragmatism is a form of humility in the face of a world that makes a mockery of even the most brilliant attempts to understand it.

3 While helping with the problem of unique phenomena, this definition does lead to instrumentalist objections (see Cartwright 1983).


This perspective, one that emphasizes subject matter rather than reasoning, works against the grain of many Western philosophical traditions. For centuries, Western philosophers have often devalued the world external to the individual. As a result, both scientists and humanists devalue the subject matter of their studies, focusing instead on the people or methods doing the research. At a basic level, either perspective is narcissistic. In the sciences, it has resulted in the celebration of the method of discovery over discovery itself. In the humanities, it has resulted in the elevation of the interpreter over those who created that which is being interpreted. In attempting to overcome the fear of fallibility, we assumed that the world bends to our will, when it is more effective to bend our will to the world. None of this is to say that methods used to study something or the people doing the studying are unimportant. They are. But in both science and the humanities, the balance seems off.

Scientific Method(s) Philosophers of science elevated scientific methods over scientific subject matter in the late-19th and

early 20th centuries, a period that coincided with the valorization of science in Europe and America. During this time, scientists discovered germ theory and created the first vaccines. Insights by physicists started to illuminate the origins of the universe and the workings of the atom. Governments and private foundations began lavishly supporting the sciences as discoveries continued to mount. The rewards of such accomplishments are still with us today. In 2010, the National Endowment for the Humanities and the National Endowment for the Arts each had a budget of $167.5 million, while the National Science Foundation (NSF) had a budget of $6.9 billion. In 2009-10, full professors in the sciences and social sciences made roughly $10,000 more a year than full professors in the arts and humanities (Chronicle 2010).

Witnessing the triumphs and rewards of science from the outside, late 19th and 20th century philosophers of science sought to discover the secret alchemy that underwrote scientific achievements. While methods of reasoning were potentially transferable to other disciplines, for the most part, subject matter was not. If anthropologists adopted the subject matter of chemistry (e.g., the properties of matter), they would simply become chemists. The hope of philosophers of science, then, was to identify systems of reasoning that could be appropriated by researchers outside the existing boundaries of what was then considered science (e.g., by social scientists), and thereby extend the success of the sciences into ever-greater domains of scholarship. While it is tempting to say that philosophers of science and social scientists were merely aping real scientists for purely pecuniary purposes, this would be overly cynical. The attempts by philosophers of science to identify the methodological underpinnings of science could have been revolutionary, had they worked. This is not to say that the monetary rewards of science were unimportant. Even in the recent debate in the AAA, numerous anthropologists were concerned that the removal of the science from the mission statement would affect funding from the NSF and other granting agencies. If the elevation of scientific methods was an honest mistake, it was still a mistake that was handsomely rewarded. However, saying that academics were economically predisposed to assert themselves as scientists does not, by itself, demonstrate that the emphasis on scientific methods rather than scientific subject matter was mistaken. Rather, to demonstrate that scientists were mistaken in their emphasis on methods, we need to examine the history and logic of the philosophy of science.

Over the course of the 19th and 20th centuries, the study of science became institutionalized in universities and research foundations. With the institutionalization of science came a formalization of science education. While scientists had long discussed the nature and value of science (e.g., Aristotle, Newton, Bacon), by the late 19th century philosophers of science sought to codify a wide-range of more intuitive practices into a more limited set of explicit practices. Initially, philosophers of science came up with practical methods for improving scientific reasoning. Recognizing the problem of confirmation bias, for example, Chamberlain (1965[1890]) proposed the method of multiple working hypotheses to avoid


scientists’ habit of seeking to confirm their favored hypotheses. For some philosophers of science, however, better results were simply not good enough; they wanted to be certain about their conclusions.

Unfortunately, as scientists began asking how they could be sure of their conclusions, they rapidly realized they couldn’t. That is, a well-established body of philosophy demonstrated that the two most basic forms of logical reasoning, induction and deduction, were unable to provide conclusive proof of any empirical claim (see Fogelin 2007). When using induction, a scientist cannot be certain that either the premises or conclusions of the argument are true. In deduction, even a positive test result does not affirm the premises. There was, however, one chink in the armor. Deduction, used in specific and rigorous ways, can be used to show that one or more of the premises of a deductive argument are false.

In the mid-20th century philosophers Carl Hempel (1965, 1966) and Karl Popper (1959, 1976) developed the core elements of modern scientific methods. While there is significant variation between the two, in general their methods start with observation and hypothesis creation, proceed with deductive testing, and conclude with the evaluation of test results. Neither was overly concerned with the process of creating hypotheses. This was assumed to be a creative act, and thus provisional. The critical element for both was testing—the attempt by scientists to disprove hypotheses by deducing test implications that could be evaluated through experimentation or field observation. For both Hempel and Popper, those hypotheses that failed tests were rejected. The key difference between Hempel and Popper lay in the significance of positive test results. For Hempel (1965), hypotheses that survived multiple rounds of testing were tentatively accepted. For Popper (1959), hypotheses were never confirmed, only rejected. It should be noted that the negation strategy was not Hempel’s primary contribution to the philosophy of science. Rather, Hempel was primarily concerned with explaining empirical phenomena through reference to universal and/or statistical laws, what Hempel called the Deductive-Nomological approach (1965, 1966). Taken together, the methods proposed by Hempel and Popper became known as the negation strategy. These methods lie, often unexamined, at the core of the scientific method to this day.

In philosophy, Hempel and Popper’s proposals were heavily critiqued from the start. Some philosophers found Hempel and Popper’s proposals to be too heavily based on the methods of the physical sciences, with too little attention paid to the statistical methods of the biological and social sciences (Mayr 1982; Salmon 1984, 1989; but see Hempel 1942; Popper 1976). Others suggested that the negation strategy was impractical—that a list of potential false hypotheses was infinite and scratching off a few did not make those that remained any more likely (Quine and Ullian 1978). By the end of the 20th century, most philosophers of science had abandoned the idea that any single method could or should characterize science. Some philosophers even abandoned prescriptive approaches all together, focusing instead on a more descriptive approach to the philosophy of science (e.g., Hacking 1983; Pickering 1992; Wylie 2002). Rather than a single scientific method, science was reconceived as having multiple methods of reasoning—some for physical sciences, others for historical sciences, and others for the social sciences. Yet, common to almost all of these understandings were the views that: (1) science is a method, 2) science is concerned with empirical phenomena, and (3) scientists should attempt to critically evaluate all claims about empirical phenomena.

The ubiquity of this implicit view of science by anthropological scientists can be shown in the ways anthropological scientists justified their perspective in the debate over the changes to the mission statement. In each of quotations that began this paper, anthropological scientists justified the value of anthropological science by reference to one or more of these criteria. While the focus in this paper is on the inability of methodological approaches to define science, it is also important to refute the idea that science is defined by the study of empirical phenomena. This turns out to be fairly easy. With even a cursory examination, empiricism fails to differentiate science from other disciplines. As used by scientists, empirical variously is understood to mean real, observable, or perhaps measurable—none of which exclude the phenomena studied by humanists. It should not be necessary to explain to anthropologists the reality of social facts. The idea that social phenomena are real—and have real consequences—is foundational to the discipline. Similarly, social phenomena can be observed. This would be the minimal requirement for participant observation to work. Finally, social phenomena can be


measured, even if they are not phenomena typically within the purview of scientific disciplines. I could, for example, measure the length of sermons by religious leaders of different faiths, but nobody would argue that doing so was scientific. In sum, while empiricism may separate science from the arts, it fails to separate science from the humanities. Given all of this, it is not surprising that philosophers and scientists have focused most of their attention on methodological definitions of science, with the negation strategy front and center.

With this focus on the negation strategy by scientists have come numerous other scientific practices that, while not strictly following from the work of Hempel and Popper, extend and operationalize their work. Today, practicing scientists rely on null hypotheses, 95% confidence intervals, double-blind testing, and independent replicability. All of these practices serve a simple function; they make it more likely that a hypothesis will be rejected. Despite Popper’s objections, scientists continue to make empirical claims about the world, but are more certain of their conclusions given the effort made to disprove them. Today, skepticism is no longer a dreary necessity of science, but rather its defining element. The negation strategy has become an overarching ethic of modern science—divorced from the philosophical foundation its earliest proponents worked so hard to build. With scientific practice unmoored from philosophy, few practicing scientists recognize that their methods are simplified derivatives of the work of earlier generations of philosophers of science. Scientists like Richard Feynman have even argued that, “the philosophy of science is about as useful to practicing scientists as ornithology is to the birds.”4 While there is some truth to this, by forgetting the origins of modern scientific methods, scientists opened themselves to attack by a new generation of humanists following alternative philosophical traditions.

The Humanist Critique of Science In 1962, Thomas Kuhn published The Structure of Scientific Revolutions (Kuhn 1962). Kuhn’s

central claim was that science develops in fits and starts, that revolutionary ideas periodically transform or create new scientific disciplines and that the resulting scientific knowledge is largely or entirely incommensurate with what came before. Kuhn’s argument was an important corrective to the common belief that science consists of the gradual accumulation of knowledge, though anyone with even a glancing familiarity with the history of science should have been aware of the revolutionary contributions of Darwin, Einstein, Newton, Pasteur, and others. The critical element of Kuhn’s analysis, then, is not that scientific revolutions occurred, but rather that “revolutionary science” succeeds without conforming to the standard methodological practices of what Kuhn refers to as “normal science.” For Kuhn, most scientists engage in normal science most of the time. Rather than seeking transformative, revolutionary new ideas, they seek to flesh out the implications of established paradigms in ever more sophisticated and ingenious ways using rigorous standards of logical and mathematical proof. In practicing normal science, however, scientists periodically come up with anomalous test results. In normal science, these anomalous results are typically seen as experimental errors and set aside. But, in time and with sufficient repetition, anomalous results begin to call into question the accepted paradigm in which normal scientists operate. It is here, Kuhn argues, that revolutionary science occurs.

Revolutionary science addresses the anomalies produced in normal science through the creation of a new paradigm. Since earlier and later paradigms use different concepts, or the same concepts differently, and address different problems, the selection of one paradigm over another cannot be accomplished by the strict logical methods of normal science. The two paradigms address different things. Thus, new paradigms are championed and accepted through calls to epistemological standards that are not employed

4 This quote by Feynman may be apocryphal, as I have never been able to trace it back to its source. Nevertheless, it is commonly referenced by scientists and, I think, accurately reflects how many scientists view the philosophy of science. A Google search of the quote yielded 62,500 results.


in normal science. This is not to say that no epistemological standards are employed in revolutionary science. In the postscript to the second edition of The Structure of Scientific Revolutions, Kuhn (1970:199) states:

Debates over theory choice cannot be cast in a form that fully resembles logical or mathematical proof. … Nothing about that relatively familiar thesis implies either that there are no good reasons for being persuaded or that those reasons are not ultimately decisive for the group. Nor does it even imply that the reasons for choice are different from those usually listed by philosophers of science: accuracy, simplicity, fruitfulness, and the like.

For Kuhn, new paradigms were evaluated through commonly accepted standards of reasoning, but not

the conservative standards of normal science. As will be discussed at greater length below, scientists engaged in normal science employ reasoning systems unavailable to humanists, but scientists engaged revolutionary science employ the same systems of reasoning that humanists use every day.

The publication of The Structure of Scientific Revolutions marks the first crack in the levy through which poured increasing volumes of increasingly vehement critiques of science. Where Kuhn explicitly rejected the claim that “in a debate over theory-choice there can be no recourse to good reasons” (Kuhn 1970:199), later critics argued just that. These critiques generally followed two related paths. The first path challenged the value or even existence of scientific methods. The second path challenged the idea that science was objective, arguing instead that science was a social construct—though it should be noted that few serious philosophers of science had ever really claimed that science was objective. By the 1980s and 1990s, the constructivist critique of science became the more dominant strand, and continues to inform studies of science to the present day.

Perhaps the most explicit critique of the scientific method was Paul Feyerabend’s Against Method (Feyerabend 1975). In this work, Feyerabend argued against the possibility that scientific methods could achieve the results ascribed to them, that a full examination of the history of science showed that no single method—or even a limited suite of methods—could explain or underwrite scientific progress. Feyerabend’s argument was complex and multifaceted, but two of the most important elements were his critique of the scientific demands for consistency and falsification. On the issue of falsification, Feyerabend argued that since no theory ever accounts for all known facts, any honest attempt at falsification would necessarily result in all scientific knowledge, new or old, being rejected. On consistency, Feyerabend argued that the demand that hypotheses must be consistent with older facts and theories necessarily eliminated the possibility of scientific progress, since facts themselves are theory dependent. New theories do not only explain the same facts in new ways. Rather, new theories often discard previous facts, at least in part, in favor of new facts. Taken together, Feyerabend argued that if scientists actually relied on the principles of continuity and falsification, science could not progress, since all new ideas would be killed in their infancy. Since science has progressed, that scientists have learned new things and rejected older understandings, Feyerabend argued that scientists must not follow the methods they claim to. Rather, Feyerabend argued that scientific knowledge is the product of more anarchic processes.

It is clear, then, that the idea of a fixed method, or of a fixed theory or rationality, rests on too naive a view of man and his social surroundings. To those who look at the rich material provided by history, and who are not intent on impoverishing it in order to please their lower instincts, their craving for intellectual security in the form of clarity, precision, ‘objectivity’, ‘truth’, it will become clear that there is only one principle that


can be defended under all circumstances and in all stages of human development. It is the principle: anything goes. (Feyerabend 2010:11-12)5

This wholesale rejection of scientific methods of reasoning is the point of departure between Kuhn

and Feyerabend. Where Kuhn argued that paradigm shifts still employed common philosophical, if not necessarily scientific, forms of reasoning, Feyerabend (1975:306-307) argued that “the separation of science and non-science is not only artificial but also detrimental to the advancement of knowledge. If we want to understand nature, if we want to master our physical surroundings, then we must use all ideas, all methods, and not just a small selection of them.” Thus, Feyerabend saw no significant difference between scientific explanations, on the one hand, and voodoo or Polynesian astronomy on the other. It was this last element of Feyerabend’s argument that was carried forward by others in the 1980s and 1990s. But where Feyerabend held onto the promise of scientific progress, however loosely defined (Feyerabend 2010:11), later humanist critics viewed science as only one of many ways of knowing the world, none any better or worse than others, and all understood as social constructs.

About the same time that Feyerabend published Against Method, Bruno Latour began an ethnographic study of a laboratory at the Salk Institute in California, which he later analyzed and published in collaboration with Steve Woolgar (Latour and Woolgar 1986[1979]. Like Feyerabend, Latour and Woolgar rejected the idea that any logical method could explain the actions of the scientists they observed. Rather, Latour and Woolgar were interested in how scientists working in laboratories socially constructed facts, how scientists constructed order from disorder. In the terms of Latour and Woolgar (1986[1979]:243), “Scientific activity is not ‘about nature,’ it is a fierce fight to construct reality.” To a large degree, Latour and Woolgar ascribed this construction to literary inscription, beginning with the daily record keeping, moving through the distillation of experiments into charts and graphs, and eventually into the production of scholarly articles. Throughout this process, scientists relied on their own authority to promote their own facts over those of other scientists. Based on all of this, Latour and Woolgar concluded that “scientific activity comprises the construction and sustenance of fictional accounts which are sometimes transformed into stabilized objects” (Latour and Woolgar 1986[1979]: 235). To be clear, Latour and Woolgar also explicitly argued that their own accounts of scientific activity were no less fictional than scientific accounts. In some sense, this was the entire point. For Latour and Woolgar, all facts—whether scientific, humanistic, or whatever—were accorded identical epistemological standing. Science was not special except in the way scientists succeeded in asserting their specialness.

By 1980s and 1990s, humanist critics of science increasingly followed the constructivist perspective of Latour and Woolgar. Where scientists saw themselves as discovering real processes, humanists saw scientists as constructing them. With this shift the debate over science became significantly more acrimonious and public as scientists began to forcefully challenge their critics. It was one thing to say that scientific methods were a hodge-podge of ad hoc practices that led to real discoveries, as Kuhn and even Feyerabend had argued. It was another thing to say that scientific discoveries were no more than social constructs—fictions—with no greater empirical reality than any other claim. It did not matter that only a few of the most ardent humanist critics of science had actually argued that. Scientists often treated even 5 Feyerabend’s “anything goes” quote is likely his most famous and problematic. In his preface to the 4th edition of Against Method, Ian Hacking (Feyerabend 2010: xii-xiii) argues that:

Feyerabend will forever be cursed by a statement of his own making, and for which he is fully responsible, the notorious aphorism ‘anything goes’… Since the aphorism is often taken to be anti-science, a sort of New Age waffle, we must emphasize that Feyerabend never meant for one minute that anything except the scientific method (whatever that is) ‘goes’.

While I accept that Feyerabend was hyperbolic in his characterization of the science, the focus of this article is precisely on what he was criticizing—the scientific method.


the most sympathetic humanists as naïve postmodernists with no real knowledge of how science was actually practiced.

Since the start of the new millennium, most humanists have retreated from the more extreme forms of constructivism. In part, this retreat is due to the appropriation of constructivism by groups that deny evolution, climate change, and other scientific theories critical to modern life. Even earlier champions of constructivism like Latour (2004:231; italics in original) have begun to recognize that:

that a certain form of critical spirit has sent us down the wrong path, encouraging us to fight the wrong enemies and, worst of all, to be considered as friends by the wrong sort of allies because of a little mistake in the definition of its main target. The question was never to get away from facts but closer to them, not fighting empiricism but, on the contrary, renewing empiricism.

Despite the recent disavowals of extreme constructivism, the humanist study of science continues in

what is now commonly called Science and Technology Studies (STS). Rather than focus on the product of scientific research, STS researchers have returned to the examination of the practice of science—focusing on issues like scientific ethics, what scientists choose to study, what is funded, and how scientific authority is earned and deployed. This is not to say that constructivism has been completely abandoned. Rather, like the shift from the more explicit negation strategy of Hempel and Popper to a more implicit negation ethic by practicing scientists, STS researchers have shifted from a more active and explicit reliance on constructivism to a more guarded and implicit use of constructivism. As argued by Sismodo (2008:14, italics in original):

The metaphor of ‘construction,’ or ‘social construction,’ was so ubiquitous in the 1980s and 1990s that now authors in STS bend over backward to avoid using the term: other terms, like ‘framing,’ ‘constitution,’ ‘organization,’ ‘production,’ and ‘manufacture,’ fill similar roles, attached to parts of the construction of facts and artifacts. The construction metaphor has been applied in a wide variety of ways in STS; attention to that variety shows us that the majority of these applications are reasonable or unobjectionable.

With the science wars mostly over, the humanistic study of science has become institutionally

established and legitimized, in part through the creation of academic programs in STS. In subsequent portions of this paper I employ many of the insights of STS studies. In some sense, however, this paper is a return to the challenge posed by Kuhn and Feyerabend. That is, if science is not defined by its methods, what makes science different from other academic pursuits? What makes science special? Humanists might answer these questions by saying science is not particularly special, and the difference between science and other disciplines is mostly due people’s perception of science rather than any special methods of reasoning that scientists employ. In contrast, I argue that while science cannot be distinguished from the humanities by its methods of reasoning alone—though they matter—science is special because of its subject matter. The rest of this paper is intended to establish this point and to show how this understanding can be operationalized to improve both scientific and humanistic research.

Incipient Science and Pseudoscience If we seek to identify the core elements of science, those elements that identify and separate science

from other non-scientific disciplines, we must identify those elements that are ubiquitous in the sciences


and mostly absent in the non-sciences. Based on the previous discussions, specific scientific methods do not distinguish science from other disciplines for the simple reason that practicing scientists don’t consistently use them. Worse still, most of the proposed methods that are used to define science, like the negation ethic, are not exclusive to the sciences. It is easy to imagine a Shakespeare scholar, for example, coming up with a new understanding of Macbeth and searching the text for counterexamples to check if that understanding is viable. Far from being a rare event, this sort of critical appraisal is a normal part of any humanist’s research for the simple reason that if he or she doesn’t critically evaluate his or her own ideas, upon publication, somebody else certainly will. So, the negation ethic fails to define science on two counts—the negation ethic is not ubiquitous to the sciences and is not even limited to the sciences. The same can be said of the method of multiple working hypotheses (Chamberlain 1965[1890]), where researchers evaluate and consider multiple explanations in order to resist the tendency to confirm their favored hypothesis. Rather than a specifically scientific process, considering and evaluating multiple explanations is beneficial for any researcher, and is common in both the sciences and the humanities. The question remains, however, if specific methods or methods of reasoning do not define science, what does? The answer to this question begins to emerge through studies of the history of science and the problem of defining pseudoscience.

In contrast to the negation strategy of the 20th century, early scientists relied on a greater variety of scientific methods (see McMullin 1992). Here I will discuss two: (1) measurement and extrapolation (2) the confirmation strategy.6 The methods used by Galileo and Mendel are instructive for understanding both. Galileo repeatedly timed falling objects and swinging pendulums. Mendel planted thousands of pea plants and recorded their phenotypic variation over several generations. In sum, Galileo and Mendel combined repeated measurement of empirical phenomena with the conviction of a mechanistic or law-abiding universe. Both were fully aware that extraneous factors (e.g., friction, chance, experimental error) would make their measurements mere approximations of the regularities they hoped to identify. Critically, Mendel and Galileo did not simply take the mean of their measurements as the conclusion of their studies. In both cases, they extrapolated—inferred—from their imperfect data to an idealized mathematical or statistical process that they assumed governed the phenomena they were studying. Neither Galileo nor Mendel employed the negation strategy, deduction, or other modern scientific methods. Yet, by any reasonable standard, Galileo and Mendel successfully discovered regular or largely regular processes in the natural world.

A modern controversy over Mendel’s research is particularly useful in illuminating the differences between 19th and 20th century science. In 1936, Fisher re-examined Mendel’s data and concluded that it was closer to Mendel’s expectations than could be reasonably accounted for by chance (Fisher 1936; Mendel 1965[1866]). Since Fisher’s original critique, geneticists have debated whether Mendel deliberately falsified his data (C. Novitski 1995) or if Mendel was merely engaged in confirmation bias (Edwards 1986). Most recently, Hartl and Fairbanks (2007:975) argued that:

Much of the discrepancy results from the absence of extreme deviates, and this can largely be explained by unconscious bias in classifying ambiguous phenotypes, stopping the counts when satisfied with the results, recounting when the results seem suspicious, and repeating experiments whose outcome is mistrusted.

While agreeing with Hartl and Fairbank’s argument, I suggest that debates over the veracity of

Mendel’s data also illustrate a fundamental confusion about 19th century science. While similar to 20th century experiments, 19th century scientists performed experiments to demonstrate the accuracy of their proposed explanations, not to disprove them. Where modern scientists have explicitly chosen to be

6 Measurement and extrapolation can be more formally labeled induction and inference to the best explanation, both of which are discussed in greater detail in later portions of the paper.


conservative in order to avoid affirming the wrong conclusions about known regularities, 19th century scientists were liberal in order to discover new regularities. The modern reliance on the negation strategy decreases the chance that scientists will accept a false regularity as true while increasing the chance that a true regularity will be rejected due to chance or experimental error. A confirmation strategy does exactly the opposite. In this sense, it makes no more sense to critique Mendel for confirmation bias than it would to critique modern scientists for having a negation bias.

By examining the history of science it is possible to say that modern scientific methods are not necessary for the successful discovery of universal or statistical laws. But what about the opposite—are scientific methods at least limited to scientific endeavors? The answer to that would be an unqualified no. Throughout the 20th century numerous pseudoscientists have claimed to apply scientific methods to processes that are not amenable to scientific study. Perhaps the best example of this would be the work of Biblical creationists. Interestingly, scientists typically dismiss creationists through reference to the negation strategy rather than directly rebutting their empirical claims. Creationists, scientists argue, claim that about 6,000 years ago God created the world that scientists study, placing fossils in the ground and setting in motion natural processes that suggest an antiquity older than creation itself. If an omnipotent God is trying to fool us, scientists say, God will always win. Creationism, then, is not a science because mere mortals cannot employ the negation strategy to disprove its claims. Yet, modern science is itself the beneficiary of research that precedes the creation of the negation strategy and continues to regularly employ systems of reasoning that violate the negation strategy. If scientists wish to dismiss creationists through calls to the negation strategy, they will also need to dismiss Galileo and Mendel. That would seem an unacceptable loss.

To be clear, I am not suggesting that creationism is a science. It isn’t. However, the reason creationism is not a science is not because of the negation strategy, and not because of the inaccuracy of creation scientists’ empirical claims, but rather because of creationism’s subject matter. Creationism is not a science because the Bible does not report on regular or largely regular processes. The Bible is a record of miracles—the miracle of resurrection, the miracle of virgin birth, and the miracle of creation. Following Hume (1956[1777]), a miracle is an event that is inexplicable by the laws of nature. If regular or largely regular processes governed miracles, miracles wouldn’t be miraculous. Since the miracle of creation is, by its very definition, irregular, Biblical creation cannot be studied scientifically and it never will. To be clear, this argument has nothing to do with the uniqueness of creation. All phenomena are, to some degree, unique. Creationism would be just as non-scientific if creationists argued that God created five, ten, or one hundred worlds, because miracles, by definition, are irregular. By focusing on the degree of regularity of the processes governing phenomena rather than the methods used to study the phenomena, it is possible to preserve the scientific credentials of Mendel and Galileo while denying them to creationists.

Studying Regularities

In examining the history of science and the pseudoscience, it becomes clear that most scientific

methods, particularly the negation strategy, do not serve to distinguish scientific disciplines from non-scientific disciplines. Galileo and Mendel engaged in science without modern scientific methods, and many pseudoscientists have employed scientific methods—to no effect—in non-scientific endeavors. Given all this, how can I explain the obvious successes of Galileo and Mendel? I suggest that their successes were primarily the result of the phenomena being studied. Through either astute choices or luck, Galileo and Mendel investigated phenomena that were governed by regular or largely regular processes. Had they chosen to study irregular phenomena, Galileo and Mendel would have failed


whatever method they employed.7 The same can be said of modern scientists working in any discipline. The common, unifying attributes of science, then, are not the methods, but rather the regularity of the processes governing the phenomena being studied. That said, there are critical differences in the degree of regularity of different phenomena. These differences in regularity have profound effects on the way in which phenomena can be studied and explained. The types of explanation proposed by Galileo and Mendel, for instance, are importantly different. Where Galileo’s explanations of the motion of objects took a more universal form, Mendel’s explanations of genetic inheritance took a more statistical form. Rather than a difference in approach, these differences were the product of the degree of regularity in the phenomena that Mendel and Galileo studied. Where the motion of objects is governed by regular processes, the inheritance of what have come to be known as Mendelian traits is governed by largely regular processes. Rather than differing methods and reasoning employed by Galileo and Mendel producing different types of explanations, the differing types of explanations created by Galileo and Mendel are ultimately the product of the degree of regularity being studied and the application of the best methods for studying those regularities. As will be discussed below, the same can be said of successful research in the humanities that examines somewhat regular processes.

Human Phenomena Non-Human Phenomena Regular Processes Physical Sciences Physical Sciences Largely Regular Processes Historical Sciences Historical Sciences Somewhat Regular Processes Humanities ? Irregular Processes - -

Table 1: The types of processes and phenomena scientists and humanists study.

As used here regular, largely regular, somewhat regular and irregular processes are ordinal types, with

only heuristic value. Regular processes are invariant or nearly so. Irregular processes are completely variable or nearly so. Largely regular and somewhat regular processes lie between these two extremes. By using these terms, I am not suggesting that these types are discrete. I expect that the degree of regularity is continuous, with some processes falling between the seams of this classification. Similarly, my decision to identify four types of regularity is, at some level, arbitrary. The existing variability in the regularity of processes could just as easily be divided into two, five, or twenty types. I have chosen four types due to their correspondence with pre-existing understandings of science and the humanities. That is, these four types of regularity loosely correspond with the common division of academic disciplines into the physical sciences, historical sciences, and humanities (see Table 1).

Studying Irregular Phenomena

Neither scientific nor humanist approaches have much to say about irregular phenomena. Without some identified degree of regularity or patterning, all that can be said is that irregular phenomena are random or that no underlying processes have yet to be identified. That said, every modern discipline examines phenomena that were once considered random, chaotic, and irregular. The history of science and the humanities consists of the identification of regularity in domains of phenomena where previously no regularities were known. It would be foolish to state that new sciences or humanities will never again be developed, that people will never discover regularities governing phenomena that we currently see as irregular. The mistake made by philosophers and social scientists was assuming the methods of the normal sciences could serve to identify new regularities, when what is really needed is induction. Before

7 It is important to note that the reverse is not true. Galileo and Mendel would not necessarily have succeeded using any random method simply because they studied regular and largely regular phenomena.


different techniques can be deployed to study regularities, it must first be established that some degree of regularity exists to be studied. The most straightforward method of doing this is statistical induction—inferring the characteristics of a larger population based upon observations of a sub-sample of that population. The use of the term “statistical induction” does not mean that the results of the induction must be phrased in statistical probabilities. Rather, the phrases “all phenomena do X,” “95% of phenomena do X,” and “most phenomena do X” are all statistical inductions, and all are appropriate to the types of regularity to which they refer. The key point is that statistical induction can be used to identify whether regular, largely regular, or somewhat regular processes govern a particular phenomena, or even if any regularity can be identified at all.

Within the sciences and humanities, the value of induction has often been minimized. For scientists, the idea of blindly going out and measuring stuff in the hopes of discovering something is often seen as far too risky, since there is no way to asses the chances of success. In the humanities, the constructivist ethic impels scholars to believe that induction merely amplifies observer biases. If observed facts are theory dependent, induction only serves to expand the domain that facts apply and empower the scholars who champion those facts. In contrast, I believe that statistical induction remains one of the most powerful tools that all scholars have at their disposal, as no other method of reasoning allows for the initial identification of regularities that scholars can subsequently study using other, more powerful, methods of reasoning. I return to this issue below. First, however, I examine the methods of reasoning that can be applied to the study of processes exhibiting different degrees of regularity.

Studying Somewhat Regular Processes

By switching the definition of science from method to subject matter, it is possible to bring the humanities into a larger, overarching conception of reasoning (see table 1). If the sciences are those disciplines that study phenomena governed by regular or largely regular processes, the humanities study human phenomena governed by somewhat regular processes. Literature and the arts, for example, do follow conventions and tropes. Heroines in 19th century British literature tend to have their desires thwarted or delayed by social convention. Hollywood movies tend to have happy endings. Many human processes are predictable, but not to the same degree or in the same way that largely regular processes are predictable. The somewhat regular processes of the humanities are not consistent enough to have any significance in a modern statistical sense. But, contrary to the claims of many scientists and even some humanists, systems of reasoning do exist in the humanities, most notably inference to the best explanation and analogical inference. Like statistical induction, both inference to the best explanation and analogical arguments are inductive. Like statistical induction, their conclusions can be wrong even if all of the premises are true. On the plus side, induction is ampliative—the conclusions of an induction contain more information than is contained within their premises.

Analogical inference assumes that if A is composed of a set of traits (A1, A2, A3...), and B shares those traits (B1, B2, B3...), plus others (B4 and B5), it follows that A might also have those traits (A4 and A5). Thus, an ethnographer, relying on analogy, might argue that the treatment of indigenous people by the state in Australia is similar to the way indigenous people are treated by the state in Canada. In an excellent review of the use of analogy in archaeology, Allison Wylie (2002:chapter 9) notes the general philosophical understanding that good analogical arguments also note points of dissimilarity. Further, Wylie argues that strong "analogical comparisons generally incorporate considerations of relevance that bring into play knowledge about underlying 'principles of connection' that structure the association of properties in the source and the subject" (Wylie 2002:147-48). For example, the similar colonial histories of Australia and Canada might serve as the “principle of connection” that allow for that analogy to be productively employed, despite the numerous differences in the treatment of indigenous people by the Australian and Canadian governments. Analogy is common form of reasoning for the study of somewhat regular phenomena, allowing insights from somewhat similar phenomena to inform the study of other phenomena.


Inference to the best explanation is a form of reasoning in which it is inferred that the best explanation—the explanation that accounts for the greatest quantity and diversity of information in the simplest way—is also most likely to be true (Fogelin 2007; Harman 1965; Lipton 1991; Peirce 1931). Inference to the best explanation is part of the pragmatic tradition in philosophy that examines the actual practices of reasoning that seem to work rather than proscribing systems of reasoning alien to most people’s day-to-day experiences. Inference to best explanation was first identified by Charles Sanders Peirce (1931) as a way to understand the initial creation of hypotheses worth testing using more traditional scientific methods, and later extended by Gil Harmon (1965) as method for evaluating explanations. Perhaps the best examples of inference to the best explanation are classic detective novels, where one of several people is identified as the culprit by tying together several strands of evidence into one coherent explanation. The key attribute of inference to the best explanation is its attention to the diversity of evidence. Where statistical induction focuses on the frequency of a single trait within a population, inference to the best explanation seeks to unite diverse strands of evidence within one over-arching explanation, with the ability of the explanation to explain this diverse evidence prima facia evidence of its truth.

Humanists make regular use of statistical induction, analogy, and inference to best explanation, whether or not they realize it. Every time humanists generalize from the specific group they are studying to any larger group, they are employing statistical induction. Any time they compare two groups to gain insight about one or both of them, they are employing analogy. Any time they attempt to combine the disparate threads of their research to develop an overarching explanation or interpretation of human phenomena, they are employing inference to the best explanation. This is good, since all of these types of inductive reasoning are well-suited to the somewhat regular processes that humanists study. Neither analogy nor inference to the best explanation can be systematized in the same way as other forms of reasoning, but rather than a weakness, this looseness in application is a strength. This looseness allows humanists to employ the ampliative qualities of inductions to generate plausible explanations of the somewhat regular processes they study. As will be discussed below, the power of these forms of inductive reasoning also explains why scientists use them when engaged in revolutionary science. But before moving on to the sciences, it is important to address an odd gap between the sciences and humanities.

As shown in Table 1, the study of non-human, somewhat regular phenomena have been neglected in existing scholarly research. In part, this is due to the framing of the debate over science. Scientists have limited themselves to the study of regular and largely regular processes because these processes fit more easily within what scientists implicitly consider science. To the degree scientists study somewhat regular phenomena, they either attempt to identify greater regularity in the underlying processes—thus converting somewhat regular phenomena to regular or largely regular phenomena more amenable to scientific study—or, more problematically, study somewhat regular processes using scientific methods only appropriate to regular and largely regular processes. Humanists, in contrast, ignore somewhat regular, non-human phenomena because they are non-human. Few researchers seem to study non-human somewhat regular phenomena in-and-of-themselves. One possible exception to this would be zoologists and others (e.g., anthropological primatologists) who study animal behavior. In some sense, these scholars live between two worlds. While well outside my area of expertise, I suggest that researchers studying animal behavior might benefit from more explicitly borrowing the methods of reasoning used in the humanities. Rather than using scientific methods inappropriate to the study somewhat regular processes, animal behaviorists might benefit from the use of analogy and inference to the best explanation. The same would be true of any researchers studying somewhat regular, non-human processes.

Studying regular and largely regular processes

Philosophers of science (e.g., Mayr 1982) have long recognized a difference in the methods of the historical sciences (e.g., evolutionary biology) and what are variously referred to as the physical or experimental sciences (e.g., physics and chemistry). This distinction is best explained by the degree of


regularity within the processes they study. Historical sciences are not defined by studying things in the past, but rather by the study of largely regular processes that only allow post-hoc explanations and limited, less-certain predictions of the near future. For example, an evolutionary biologist can explain why a particular phenotypic trait increased in frequency in the past, but can make only limited predictions about future evolutionary paths. In contrast, the physical sciences are not temporally bounded since regular processes can be applied to explanations of the past, present, and future without restriction. Astronomers have no more difficulty predicting the location of Mars one thousand years in the future than they do determining Mars’s location one thousand years in the past. From this perspective the differences in methods between the historical and physical sciences make perfect sense—they study processes exhibiting different degrees of regularity. Geneticists make extensive use of statistical laws and statistical testing because the processes they study (recombination, mutation, etc.) are largely regular. In contrast, physicists can often employ universal laws and deductive testing because the processes they study are regular. Thus, in the practice of normal science, those studying regular processes can use deductive methods like those described by Hempel (1965, 1966) and Popper (1959), while those studying largely regular processes can employ statistical laws (Salmon 1984, 1989). But it should be remembered that science is not simply the practice of normal science, but also, following Kuhn (1970), the practice of revolutionary science.

Regular Processes (Physical Sciences)

Largely Regular Processes

(Historical Sciences)

Somewhat Regular Processes

(Humanities)

Irregular Processes

Deduction, Hypothetico-Deductive Method, and Universal Laws

●

Statistical Syllogisms, Statistical Testing, and Statistical Laws

● ●

Inference to the Best Explanation ● ● ●

Analogical Inference ● ● ● Induction ● ● ●

Table 2: The applicability of select philosophies of science and reasoning to phenomena governed by processes with

varying degrees of regularity.

In revolutionary science, the science that leads to paradigm shifts, the typical standards of normal science are relaxed. That is, work in revolutionary and incipient sciences often begins with statistical induction, with inference to the best explanation employed to elucidate regular or largely regular processes. This is exactly how Galileo and Mendel began. Both started with statistical induction, but both employed inference to the best explanation to infer more general—in a sense, more perfect—processes than they ever observed in their actual experiments. Based on Kuhn’s insights in paradigm shifts, the same can be said of all revolutionary scientists when they create new paradigms. Thus, physical and historical scientists can, and do, employ all of the methods that humanists use to study somewhat regular phenomena while using several others that are exclusive to the sciences.

As shown in Table 2, when subject is privileged over method, several interesting patterns emerge. First, as the processes being studied become increasingly regular, more methods of reasoning are available to study those processes. Historical sciences employ methods unavailable to the humanities (e.g., statistical testing), and the physical sciences employ methods of reasoning unavailable to both (e.g., hypothetico-deductive method). Second, the humanities, historical sciences, and physical sciences share


many systems of reasoning. In fact, all of the systems of reasoning in the humanities are also used in the sciences, though it might also be the case that more universal methods of reasoning may become less productive when applied to the scientific subject matter. For example, statistical methods can be used to investigate regular processes, though the results would be uninteresting because the statistical significance of the results would always be either 1 or 0 (ignoring the problem of experimental error). Likewise, gravity can be understood as analogous to magnetism (they both relate to an attractive force between two objects), though really, physicists have moved well beyond the point where this analogy is particularly fruitful. By saying that scientists can employ more universal methods of reasoning, I am not saying they always should. Following Kuhn (1970), there are times when the application of more universal systems of reasoning are appropriate in the sciences—they underwrite paradigm shifts between periods of normal science. The systems of reasoning employed by scientists during scientific revolutions are the same as the systems of reasoning used by humanists as a matter of course. This alone should put to rest any claim that the most restricted methods of modern science are the most powerful.

When applied to the appropriate subject matter, the methods of science can be extremely effective, but the application of scientific methods (of whatever sort) will do nothing to make aspiring sciences or the humanities more scientific. The only thing that transforms a non-science into a science is the discovery and demonstration of regularities within the processes being studied. Further, based on the history of science, it seems unlikely that modern scientific methods will help aspiring scientists identify those regularities. Most of the recognized sciences became that way through long periods of statistical induction, inference to the best explanation, and the conviction that regularities existed to be discovered. Perhaps aspiring scientists should give statistical induction and inference to the best explanation a try. That said, there is no guarantee of success. If the processes are not regular or largely regular, aspiring scientists will fail no matter what methods they employ. The proof is in the pudding, not the type of spoon used to eat the pudding. Like Galileo and Mendel, aspiring scientists have no more than the conviction that one day they will successfully identify regularities of sufficient breadth as to be appropriate for scientific inquiry. There is another option. Aspiring scientists could opt to study somewhat regular processes in-and-of-themselves—they could choose to study phenomena like humanists already do.

Given the regularity of the processes they study, scientists do have methods available to them that are unavailable to humanists, but scientists are wrong to believe that all of their methods are distinct from the humanities. Science is not the study of real phenomena, nor is science the study of real phenomena following a particular method or suite of methods. Science is merely the study of the limited subset of real phenomena governed by regular or largely regular processes. Scientists need to recognize that those real human phenomena not known to be governed by regular or largely regular processes—religion, literature, culture—are still valid areas of inquiry, and that the people studying them employ systems of reasoning common to the sciences.

But humanists must recognize that they have made their own mistakes. Humanists must recognize that scientists do study different types of regularities than humanists do and can thus employ a greater number of methods of reasoning in their research. But choosing to be a humanist should not entail the abandonment of methods of reasoning. While humanists are no longer as infatuated with constructivism as they were in the 1980s and 1990s, humanists often persist in avoiding clear articulations of their methods of reasoning. Rather, humanists have increasingly elevated concerns with interpretive biases, embedded assumptions, and definitions over the subject matter of their research. This is not to say that bias is unimportant, or that scientific methods of reasoning avoid problems with bias. Questioning biases matters, but it is not the be-all-end-all of research. It is time for humanists to ratchet back their reliance on constructivism and return to the subject matter of their studies. This will require humanists to be more cognizant of the systems of reasoning they employ and accept that there is much to learn from the sciences about how best to employ them.


Returning to the Subject Anthropologists study phenomena currently understood as governed by regular, largely regular, and

somewhat regular processes. They also attempt to identify regularity in phenomena that are currently understood as irregular. As for the methods used to study these regularities, they are of secondary importance and should be determined by the nature of the regularities in question. In many cases, the degree of regularity being studied has already been established through earlier periods of inductive research. In those areas, the appropriate methods of research are fairly clear. But despite a century of attempts to make anthropology a science, there are many domains of anthropological research that remain aspiring sciences, if that. That is, the degree of regularity underlying the phenomena is either unclear or reasonably debated. In general, the parts of anthropology that are most scientific are the areas in which the subject matter has been most borrowed from other, scientific, disciplines (e.g., archaeometry or molecular anthropology). There are far fewer examples of anthropologists identifying regular and largely regular processes and establishing new domains of scientific research themselves. This failure may partially rest on the mistaken acceptance of the methodological conception of science by anthropologists.

Without the inductive demonstration that processes governing anthropological phenomena are regular or largely regular, the application of the methods of normal science to those phenomena are inappropriate. More-so, the application of the methods of normal science by anthropological scientists will not—and cannot—lead to the identification of regular or largely regular processes. Just as in the case of creationism, the study of irregular phenomena or somewhat regular processes through the methods of normal science is nothing more than pseudoscience. There is no doubt that some anthropological scientists have, at least in some instances, been guilty of that. Conversely, the study of phenomena governed by regular or largely regular processes as if they were somewhat regular processes could fairly be called pseudohumanities. There is no doubt that some anthropological humanists have, at least in some instances, been guilty of that. This is not to say that the practice of science by scientists is regular or largely regular and not fit for humanistic study. Since people practice science, it seems likely that the processes governing the practice of science are somewhat regular—though it would be good for STS scholars to more explicitly demonstrate that before proceeding to their research.

Returning to the debate that began this article, how should the AAA define the mission of anthropology? If disciplines are best defined by what they study, anthropology is the study of human phenomena governed by regular, largely regular, and somewhat regular processes. There is no good reason to assume a priori that regular or largely regular processes govern all phenomena in biological anthropology or archaeology. Nor is there any good reason to assume that somewhat regular processes govern all the phenomena in sociocultural anthropology or linguistics. Anthropologists should stop being methodological and interpretive narcissists. Anthropologists’ first allegiance should never be to the methods of humanities or the sciences, but rather to subject matter of their studies. There should not be scientific or humanistic sub-disciplines in anthropology; nor should there be scientific or humanistic anthropologists. All anthropologists study humans. The different approaches anthropologists take in their research should have more to do with the regularity of the processes they study at any given time than with sub-disciplinary boundaries. The promise of anthropology lies in its commitment to holism. With the recognition of the primacy of subject matter, the usefulness of the dichotomy between science and the humanities begins to dissolve. Rather than letting the methods of science or the humanities guide our research, we must let the regularity of the specific processes and phenomena being studied guide our research. Individual anthropologists must be trained to use multiple methods of reasoning and be prepared to use them as appropriate, whatever sub-discipline they call home. Whatever else, anthropologists must stop engaging in crippling debates over science and the humanities that neither inform nor enlighten.


References Cited Adra, N. 2010. “Comment to Revision to AAA Long-Range Plan.”

http://blog.aaanet.org/2010/12/03/revision-to-aaa-long-range-plan/, accessed January 15, 2011. American Anthropological Association 2010. “What is Anthropology?

http://www.aaanet.org/about/WhatisAnthropology.cfm, accessed January 15, 2011. Aristotle. 2001. On the Parts of Animals. Translated by J.G. Lennox. Oxford: Oxford University Press. Cartwright, N. 1983. How the Laws of Physics Lie. Oxford: Oxford University Press. Chamberlain, T. C. 1965[1890]. The Method of Multiple Working Hypotheses. Science 148:754-759. Chronicle of Higher Education 2010. “Average Faculty Salaries by Field and Rank at 4-Year Colleges

and Universities, 2009-10.” http://chronicle.com/article/Chart-Average-Faculty/64500/, accessed January 15, 2011.

Dewey, J. 1929. The Quest for Certainty. New York: Minton, Balch. Dominguez, V.R., et al. 2010 “Long-Range Plan.”

http://www.aaanet.org/about/Governance/Long_range_plan.cfm, accessed January 15, 2011. Dow, J.W. 2010. “Comment to Anthropology, Science, and the AAA Long-Range Plan.”

http://blogs.plos.org/neuroanthropology/2010/12/10/anthropology-science-and-the-aaa-long-range-plan-what-really-happened/, accessed December 24, 2010.

Edwards, A. W. F. 1986. Are Mendel's Results Really Too Close? Biological Review 61:295-312. Feyerabend, P. 2010[1975]. Against Method. London: Verso. Fisher, R. A. 1936. Has Mendel's Work been Rediscovered? Annals of Science 1. Fogelin, L. 2007. Inference to the Best Explanation: A Common and Effective Form of Archaeological

Reasoning. American Antiquity 72:603-625. Hacking, I. 1983. Representing and Intervening: Introductory Topics in the Philosophy of Natural

Science. Cambridge: Cambridge University Press. Harman, G. H. 1965. The Inference to the Best Explanation. The Philosophical Review 74:88-95. Hartl, D. L., and D. J. Fairbanks. 2007. Mud Sticks: On the Alleged Falsification of Mendel's Data.

Genetics 175:975-979. Hempel, C. G. 1942. The Function of General Laws in History. Journal of Philosophy 39:35-48. —. 1965. Aspects of Scientific Explanation. New York: The Free Press. —. 1966. Philosophy of Natural Science. Boston: MIT Press. Hume, D. 1956[1777]. An Enquiry Concerning Human Understanding. Chicago: Gateway Editions. Kuhn, T. S. 1970[1962]. The Structure of Scientific Revolutions: Second Edition. Chicago: University of

Chicago Press. Latour, B. 2004. Why has Critique Run Out of Steam? From Matters of Fact to Matters of Concern.

Critical Inquiry 30:225-248. Latour, B., and S. Woolgar. 1986[1979]. Laboratory Life: The Social Construction of Scientific Facts.

Princeton: Princeton University Press. Lipton, P. 1991. Inference to the Best Explanation. London: Routledge. Mayr, E. 1982. The Growth of Biological Thought. Cambridge: Belknap Press. McMullin, E. 1992. The Inference that Makes Science. Milwaukee: Marquette University Press. Mendel, G. 1965. Experiments in Plant Domestication. Cambridge: Harvard University Press. Moore, J. 2010. “Comment to Revision to AAA Long-Range Plan.”

http://blog.aaanet.org/2010/12/03/revision-to-aaa-long-range-plan/, accessed January 15, 2010.


Novitski, C. E. 1995. Another Look at some of Mendel's Results. Journal of Heredity 86:62-66. Peirce, C. S. 1931. Collected Papers. Cambridge: Harvard University Press. Peregrine, P. 2010. “AAA takes science (and solving human problems) out of its mission statement.”

https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1011D&L=ANTHRO-SCIENCES&D=0&P=69, accessed January 15, 2011.

Pickering, A. Editor. 1992. Science as Practice and Culture. Chicago: University of Chicago Press. Popper, K. R. 1959. The Logic of Scientific Discovery. London: Hutchinson. —. 1976. "Logic of the Social Sciences," in The Positivist Dispute in German Sociology. Edited by T. W.

Adorno, H. Albert, R. Dahrendorf, J. Habermas, H. Pilot, and K. R. Popper. London: Heineman. Putnam, H. 1983. Realism and Reason. Cambridge: Cambridge University Press. Quine, W. V., and J. S. Ullian. 1978. The Web of Belief, 2nd edition. New York: Random House. Read, D. 2010. “Re: AAA drops science from its mission.” https://www.jiscmail.ac.uk/cgi-

bin/webadmin?A2=ind1011D&L=ANTHRO-SCIENCES&D=0&P=26154, accessed December 24, 2010.

Rescher, N. 1995. "Pragmatism," in The Oxford Companion to Philosophy. Edited by T. Honderich, pp. 710-713. Oxford: Oxford University Press.

Rorty, R. 1982. Consequences of Pragmatism: Essays, 1972-1980. Minneapolis: University of Minnesota Press.

Salmon, W. C. 1984. Scientific Explanation and the Causal Structure of the World. Princeton: Princeton University Press.

—. 1989. Four Decades of Scientific Explanation. Minneapolis: University of Minnesota Press. Sismodo, S. 2008. "Science and Technology Studies and an Engaged Paradigm," in Handbook of Science

and Technology Studies. Edited by E. J. Hackett, O. Amsterdamska, M. Lynch, and J. Wajcman, pp. 13-31. Cambridge: The MIT Press.

Wade, N. 2010. "Anthropology a Science? Statement Deepens a Rift," December 9, in New York Times. New York.

Wylie, A. 2002. Thinking from Things. Berkeley: University of California Press.

(Web Exclusive) On the Subject of Science and the Humanities in Anthropology

Documents

Transcript of (Web Exclusive) On the Subject of Science and the Humanities in Anthropology