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In earlier work, I criticized de Regt’s contextual theory of understanding, and advertised the advantages of my own, knowledge-based account. Using the early history of the standard model in particle physics as an illustration, I instead consider the benefits of unifying these two accounts of understanding. I argue that de Regt’s account substantially improves my own account of explanatory consideration, and that my account of explanatory comparison substantially improves upon his account of explanatory evaluation. De Regt and my apparent disagreement about the so-called factivity of understanding is defused through a voluntaristic approach to the scientific realism debates.

We present a novel kind of “socio-functional” foundationalism rooted in the division of scientific labor. Our foundationalism is social in that it involves a socio-epistemic phenomenon we dub epistemic outsourcing, whereby claims from one group of scientists provide epistemological foundations for another group of scientists. We argue that: (1) epistemic outsourcing results in a legitimate form of epistemic foundationalism, (2) this sort of foundationalism can be used to shed light on the epistemology of measurement; and (3) epistemic outsourcing is a distinctively collective epistemic phenomenon.

This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.

Recent debates concern the question of whether topological or “network” explanations are a species of mechanistic explanation. In this paper, we provide a more principled framework for the purposes of advancing these discussions. Our innovations on this front are threefold. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations, and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. We conclude from this that topological explanations are autonomous from their mechanistic counterparts.

Criticism is a staple of the scientific enterprise and of the social epistemology of science. Philosophical discussions of criticism have traditionally focused on its roles in relation to objectivity, confirmation, and theory choice. However, attention to criticism and to criticizability should also inform our thinking about scientific pursuits: the allocation of resources with the aim of developing scientific tools and ideas. In this paper, we offer an account of scientific pursuitworthiness which takes criticizability as its starting point. We call this the apokritic model of pursuit. Its core ideas are that pursuits are practices governed by norms for asking and answering questions, and that criticism arises from the breach of these norms. We illustrate and advertise our approach using examples from institutional grant review, neuroscience, and sociology. We show that the apokritic model can unify several indices of criticizability, that it can account for the importance of criticizing pursuits in scientific practice, and that it can offer ameliorative advice to erstwhile pursuers.

Because idealizations frequently advance scientific understanding, many claim that falsehoods play an epistemic role. In this paper, we argue that these positions greatly overstate idealizations’ import for understanding. We introduce work on epistemic value to the debate surrounding idealizations and understanding, arguing that idealizations qua falsehoods confer only non-epistemic value to understanding. We argue for this claim by criticizing the leading accounts of how idealizations provide understanding. For each of these approaches, we show that: (a) idealizations’ false components promote only convenience instead of understanding and (b) only the true components of idealizations have epistemic value., Ethics & Philosophy of Technology

We offer a new account of the role of values in theory choice that captures a temporal dimension to the values themselves. We argue that non-epistemic values sometimes serve as “inquiry tickets,” justifying scientists’ pursuit of certain questions in the short run, while the answers to those questions mitigate transient underdetermination in the long run. Our account of inquiry tickets shows that the role of non-epistemic values need not be restricted to belief or acceptance in order to be relevant to hypothesis choice: the relevance of non-epistemic values to a particular cognitive attitude with respect to h vary over time.

Many have argued that the human sciences feature a unique form of understanding (Verstehen) that is absent from the natural sciences. However, in the last decade or so, epistemologists and philosophers of natural science have been proffering analyses of a kind of natural-scientific understanding. Using examples from educational psychology and anthropology, I argue that there are prima facie reasons to think these recent accounts of natural-scientific understanding impose necessary conditions on Verstehen. This suggests that any claim about Verstehen’s distinctiveness faces hitherto-unappreciated burdens of proof.

Because idealizations frequently advance scientific understanding, many claim that falsehoods play an epistemic role. In this paper, we argue that these positions greatly overstate idealizations’ import for understanding. We introduce work on epistemic value to the debate surrounding idealizations and understanding, arguing that idealizations qua falsehoods only confer non-epistemic value to understanding. We argue for this claim by criticizing the leading accounts of how idealizations provide understanding. For each of these approaches, we show that: (a) idealizations’ false components only promote convenience instead of understanding and (b) only the true components of idealizations have epistemic value.