The social and behavioral sciences endeavor to describe, explain, and interpret the range of the social and behavioral facts that surround us. To refer to this body of findings as “science” is to claim a set of epistemic values about the nature of the methods of inquiry and evaluation that are used to arrive at and assess the conclusions offered about this domain. The label “science” brings with it a set of presuppositions about rigor, evidence, generalizability, logical analysis, objectivity, cumulativeness, and the likelihood that the assertions that are made are true.
Consider a few assumptions that are often made about scientific knowledge—some valid and some not. Science is based on a set of rationally justified methods of inquiry and testing. Scientific knowledge progresses, in scope, in detail of understanding, and in reliability. Science is performed by specialists, working within equally exacting communities of peers and competitors and subject to a demanding set of standards of evaluation—peer-reviewed journals, university review processes, national laboratories, and international associations and conferences. The result of these processes of testing and evaluation, we expect, is an expanding body of hypotheses, experimental findings, observations, theories, and explanations that have substantial credibility—and substantially higher credibility than the writings of casual observers of a given range of phenomena. We come to know the nature of the world better through the institutions and methods of science.
In addition to these reasonably valid assumptions about scientific knowledge, there is another group of more questionable ideas that derive from assumptions drawn from the natural sciences. Science permits generalizations; it permits us to systematize otherwise apparently separate domains of phenomena (planetary motion, the tides; rational choice theory, behavior of the family) and to demonstrate that apparently heterogeneous sets of phenomena are in fact governed by the same general laws. Science permits predictions; if the fundamentals are thus-and-so, then the compounds will behave thusly. Science aims at unification: the discovery of unitary systems of forces and entities whose aggregate properties represent the whole of nature.
Notice that these latter expectations are derived from the successes and specific characteristics of certain of the natural sciences. And this marks the first of many opportunities for error in the philosophy of social science. There is no reason to expect that the social domain possesses the underlying nature and orderliness that would make it possible to achieve some of these characteristics (in particular, uniformity, generalizability, unification, simplicity). Consider some other areas of possible empirical research—for example, animal behavior. We should not expect there to be comprehensive theories of animal behavior. Instead, we should expect many threads of research, corresponding to many dimensions of animal behavior: cognition, memory, instinct, social behaviors, migratory behavior. And these many strands of research would reach out to different kinds of causal backgrounds: evolutionary biology, neurophysiology, intra-group learning. Likewise with the domain of social behavior. There is no single unified “theory of human motivation”—whether rational choice theory, social psychology, or any other unified theory. And this is so, because there is no unified reality of motivation and action; rather, there is a heterogeneous range of motives, errors, impulses, commitments, and habits that together constitute “dispositions to behave.”
What underwrites the claim of truthfulness for scientific knowledge? What gives us a rational basis for believing that the results of the socially constructed activities of science lead to true hypotheses about the nature and workings of the phenomena that scientific inquiry considers? There is, first, the basic argument of empiricism: we can observe some features of the world and establish certain statements as being probable. And we can use a collection of tools of inference to establish credibility of other non-observational statements (deductive and inductive logic, statistics, the experimental method, causal modeling).
This simple empiricist epistemology underwrites the strongest claims for veridicality and justification for the social sciences. The discovery of empirical facts about the social world is possible but challenging; this is what much of social science methodology attempts to under-gird. And hypotheses about the causal relationships that exist among social entities and processes can be tested using a variety of methods of inference that themselves possess strong epistemic justification. We have learned from the writings of philosophers of science since the 1960s to emphasize corrigibility and anti-foundationalism in our interpretation of scientific knowledge; but a coherentist epistemology and a perspective of causal realism provides a philosophically powerful grounding for social science knowledge. (See articles in the Stanford Encyclopedia of Philosophy on coherence epistemology and scientific realism by Kvanvig and Boyd).
In addition, in some areas of the natural sciences, there is the fact that cumulative scientific research leads to the invention of technologies that work as they were designed to do: new materials are invented in the electronics industry, new designs are created for large structures (buildings, aircraft, electron microscopes), and these materials and artifacts perform as expected on the basis of the underlying theories. So scientific theories of materials, structures, and natural systems are supported by the effectiveness of the technologies that they give rise to. If the theories and hypotheses were fundamentally untrue about the parts of the natural world that they describe, then we would expect the technologies to fail; the technologies do not fail; so we have some additional reason to believe the scientific theories that underlay these technologies. (This is a version of Richard Boyd’s argument of methodological realism.)
Is there anything analogous to the relationship between the natural sciences and technology, for the social and behavioral sciences? On the whole, there is not. Social predictions are notoriously unreliable; public policies based on social-science theory commonly give rise to unanticipated consequences; and the twists and turns of deliberate social processes (war, alliance, efforts to address global warming) continue to surprise us. This unpredictability in the social world derives from the nature of social action. Human behavior and social processes are plainly subject to an open-ended range of causes, motives, and influences. The construction of various areas of science with the goal of understanding and explaining this multiplicity is therefore a profoundly challenging task.
Here, then, is a very elliptical description of a plausible interpretation of social science epistemology: There are empirical foundations for knowledge in the form of social observation (empiricism); there are social causes that influence social behavior, processes, and outcomes (causal realism); there is no a priori reason to expect strong generalizations across social phenomena, “regulating” the social world; and there is no reason to expect unified master theories of social phenomena, suggesting instead a preference for theories of the middle range.