Arguments for the effectiveness, and even the indispensability, of mathematics in scientific explanation rely on the claim that mathematics is an effective or even a necessary component in successful scientific predictions and explanations. Well-known accounts of successful mathematical explanation in physical science appeals to scientists’ ability to solve equations directly in key domains. But there are spectacular physical theories, including general relativity and fluid dynamics, in which the equations of the theory cannot be solved directly in target domains, and yet (...) scientists and mathematicians do effective work there (McLarty 2023, Elder 2023). Building on extant accounts of structural scientific explanation (Bokulich 2011, Leng 2021), I argue that philosophical accounts of the role of equations in scientific explanation need not rely on scientists’ ability to solve equations independently of their understanding of the empirical or experimental context. For instance, the process of formulating solutions to equations can involve significant appeal to information about experimental contexts (Curiel 2010) or of physically similar systems (Sterrett 2023). Working from a close analysis of work in fluid mechanics by Martin Bazant and Keith Moffatt (2005), I propose an account of heuristic structural explanation in mathematics (Einstein 1921, Pincock 2021), which explains how physical explanations can be constructed even in domains where basic equations cannot be solved directly. (shrink)

Ever since Hilary Putnam claimed that a realist philosophy is “the only philosophy that doesn’t make the success of science a miracle,” explanations for the success of science have proliferated in the philosophical literature (Putnam 1975, p. 73). Realists argue that the success of science, as exhibited by our ability to accurately predict and explain a wide range of phenomena, indicates that our theories have identified some of the underlying causal structures of the world (e.g., Boyd 1985, Ellis 1985, McMullin (...) 1984, Salmon 1984). Nonrealists counter that success cannot provide a warrant for belief in the truth of scientific theories because there have been successful theories in the past that are now believed to be false (Laudan 1981b). Instead, they offer a naturalized account whereby our theories are designed to be successful predictors and only those which fulfill this goal survive (Laudan 1987, van Fraassen, 1980). (shrink)

Realism is generally assumed as the correct position with regards to psychological research and the measurement of psychological attributes in psychometrics. Borsboom et al., 203–219 2003), for instance, argued that the choice of a reflective measurement model necessarily implies a commitment to the existence of psychological constructs as well as a commitment to the belief that empirical testing of measurement models can justify their correspondence with real causal structures. Hood :739–761 2013) deemphasized Borsboom et al.’s position and argued that the (...) choice of a reflective measurement model does not necessarily require ontological commitments, though, in his view, it does necessitate a commitment to minimal epistemic realism. Although these arguments are formulated with regard to psychological research, they can actually be generalized to other disciplines in social sciences that use similar methodologies and statistical techniques. In Hood’s opinion, empiricism does not suffice to provide an adequate account of the choice of reflective measurement models given that this choice requires an appeal to causal explanations. In this paper, we argue against Hood and answer this challenge, providing epistemic foundations for social science research that do not appeal to realism. (shrink)

Psillos, Kitcher, and Leplin have defended convergent scientific realism against the pessimistic meta-induction by arguing for the divide et impera strategy. I argue that DEI faces a problem more serious than the pessimistic meta-induction: the problem of accretion. When empirically successful theories and principles are combined, they may no longer make successful predictions or allow for accurate calculations, or the combination otherwise may be an empirical failure. The shift from classical mechanics to the new quantum theory does not reflect the (...) discarding of “idle wheels.” Instead, scientists had to contend with new principles that made classical calculations difficult or impossible, and new results that were inconsistent with classical theorems, and that suggested a new way of conceiving of atomic dynamics. In this shift, reference to atoms and to electrons was preserved, but the underlying causal explanations and descriptions of atoms and electrons changed. I propose that the emphasis on accurate description of causal agents as a virtue of background theory be replaced with Ruetsche’s advocacy of pragmatic, modal resourcefulness. (shrink)

The fact that the goals and methods of science, as well as its empirical conclusions, are subject to change, is shown to allow at once for: (a) the objectivity of warrant for knowledge claims; (b) the absence of a priori standards from epistemology; (c) the normative character of epistemology; and (d) the rationality of axiological innovation. In particular, Laudan's attempt to make axiological constraints undercut epistemic realism is confuted.

Within the context of psychological measurement, realist commitments pervade methodology. Further, there are instances where particular scientific practices and decisions are explicable most plausibly against a background assumption of epistemic realism. That psychometrics is a realist enterprise provides a possible toehold for Stephen Jay Gould’s objections to psychometrics in The Mismeasure of Man and Joel Michell’s charges that psychometrics is a “pathological science.” These objections do not withstand scrutiny. There are no fewer than three activities in ongoing psychometric research which (...) presuppose a commitment to a minimal epistemic realism. Those activities include selecting between different models for representing data, estimating ability in the context of item response theory, and the move to make the individual the fundamental unit of analysis in psychometrics thereby calling for a shift in what sorts of data are evidentially relevant. In none of these activities are the commitments and disregard for evidence that Gould and Michell find objectionable or “pathological.”. (shrink)

For as long as realists and instrumentalists have disagreed, partisans of both sides have pointed in argument to the actions and sayings of scientists. Realists in particular have often drawn comfort from the literal understanding given even to very theoretical propositions by many of those who are paid to deploy them. The scientists' realism, according to the realist, is not an idle commitment: a literal understanding of past and present theories and concepts underwrites their employment in the construction of new (...) theories. The theme of this book is philosophy and technology, and here's the connection: new theories point out—and explain—new phenomena. So realism, claim the realists, is at the heart of science's achievement of what Bacon, that early philosopher of technology, identified as science's aim: new knowledge offering new powers. (shrink)

For as long as realists and instrumentalists have disagreed, partisans of both sides have pointed in argument to the actions and sayings of scientists. Realists in particular have often drawn comfort from theliteralunderstanding given even to very theoretical propositions by many of those who are paid to deploy them. The scientists' realism, according to the realist, is not an idle commitment: a literal understanding of past and present theories and concepts underwrites their employment in the construction ofnewtheories. The theme of (...) this book is philosophy and technology, and here's the connection:newtheories point out—and explain—newphenomena. So realism, claim the realists, is at the heart of science's achievement of what Bacon, that early philosopher of technology, identified as science's aim:newknowledge offeringnewpowers. (shrink)

Arthur Fine and André Kukla have argued that realism and instrumentalism are indifferent with respect to scientific practice. I argue that this claim is ambiguous. One interpretation is that for any practice, the fact that that practice yields predictively successful theories is evidentially indifferent between scientific realism and instrumentalism. On the second construal, the claim is that for any practice, adoption of that practice by a scientist is indifferent between their being a realist or instrumentalist. I argue that there are (...) no good arguments for the indifference claim under the second interpretation, and good reasons to think that it is false. (shrink)

It has become apparent that the debate between scientific realists and constructive empiricists has come to a stalemate. Neither view can reasonably claim to be the most rational philosophy of science, exclusively capable of making sense of all scientific activities. On one prominent analysis of the situation, whether we accept a realist or an anti-realist account of science actually seems to depend on which values we antecedently accept, rather than our commitment to “rationality” per se. Accordingly, several philosophers have attempted (...) to argue in favour of scientific realism or constructive empiricism by showing that one set of values is exclusively best, for anyone and everyone, and that the downstream choice of the philosophy of science which best serves those values is therefore best, for anyone and everyone. These efforts, however, seem to have failed. In response, I suggest that philosophers of science should suspend the effort to determine which philosophy of science is best for everyone, and instead begin investigating which philosophy of science is best for specific people, with specific values, in specific contexts. I illustrate how this might be done by briefly sketching a single case study from the history of science, which seems to show that different philosophies of science are better at motivating different forms of scientific practice. (shrink)

Moti Mizrahi has argued that Thomas Kuhn does not have a good argument for the incommensurability of successive scientific paradigms. With Rouse, Andersen, and others, I defend a view on which Kuhn primarily was trying to explain scientific practice in Structure. Kuhn, like Hilary Putnam, incorporated sociological and psychological methods into his history of science. On Kuhn’s account, the education and initiation of scientists into a research tradition is a key element in scientific training and in his explanation of incommensurability (...) between research paradigms. The first part of this paper will explain and defend my reading of Kuhn. The second part will probe the extent to which Kuhn’s account can be supported, and the extent to which it rests on shaky premises. That investigation will center on Moti Mizrahi’s project, which aims to transform the Kuhnian account of science and of its history. While I do defend a modified kind of incommensurability, I agree that the strongest version of Kuhn’s account is steadfastly local and focused on the practice of science. (shrink)