Philosophy of science is expanding via the introduction of new digital data and tools for their analysis. The data comprise digitized published books and journal articles, as well as heretofore unpublished material such as images, archival text, notebooks, meeting notes, and programs. The growth in available data is matched by the extensive development of automated analysis tools. The variety of data sources and tools can be overwhelming. In this article, we survey the state of digital work in the philosophy of science, showing what kinds of questions can be answered and how one can go about answering them.

Comparative process tracing is the best analysis of extrapolation inferences in the philosophical and scientific literature so far. In this essay I examine some similarities and differences between comparative process tracing and former attempts to capture the logic of extrapolation, such as the analogical approach. I show that these accounts are not different in spirit, although comparative process tracing supersedes previous proposals in terms of analytical detail. I also examine some qualms about the possibility of drawing extrapolation inferences in the social sciences and conclude by suggesting that there may be cases of extrapolation without process tracing.

Previous claims that psychology is propaedeutic to the other sciences have been met with enthusiastic indifference. Contributing to this indifference has been the fact that psychology, a young and unproved discipline which habitually borrowed the methods of the older sciences, has too frequently revised its notion as to its own nature and subject-matter. More important, however, has been the faith of the physical sciences in the absolute character of their own basic concepts: in the reality of Absolute Space and Absolute Time and in the universality of deterministic principles, for, as long as physics presumed to deal with entities which are what they are regardless of the nature of man, nothing other than these entities appeared to demand prior consideration. The problem of the nature of the observer in the physical experiment became important to physics only as a consequence of the recent ‘subjective’ revolution. It is this revolution which has revitalized the problem of the propaedeutic science and has accentuated the distinction which we must make between the behavioral phenomenon of individuals creating formal arrays of words or symbols which are without operational meaning and the discriminatory responses, or operations, by which the empirical meaning of such arrays is determined.

Contrary to the Empiricist model of science, successful sufficiently fundamental theories not only fit and unify their data fields but also prescribe the general terms in which relevantly to describe observation; specify what is and is not observable; specify the conditions under which what is observable, is observable; specify the instrumental means and reliability by which what is measurable is measured; specify what is causally, statistically, and merely accidentally connected. Moreover, such theories typically require all or most of the entire remainder of science to be properly applied in any given situation and theoreticians' models play a crucial role in such applications. (I call these respectively the internal and external globalnesses of theories.) A discussion of the consequences of these global features of theories for philosophy of science is offered in the context of specific examples and a structural model for science.

Bertrand's random-chord paradox purports to illustrate the inconsistency of the principle of indifference when applied to problems in which the number of possible cases is infinite. This paper shows that Bertrand's original problem is vaguely posed, but demonstrates that clearly stated variations lead to different, but theoretically and empirically self-consistent solutions. The resolution of the paradox lies in appreciating how different geometric entities, represented by uniformly distributed random variables, give rise to respectively different nonuniform distributions of random chords, and hence to different probabilities. The principle of indifference appears consistently applicable to infinite sets provided that problems can be formulated unambiguously.

Much of the literature on values in science is limited in its perspective because it focuses on the role of values in individual scientists’ decision making, thereby ignoring the context of scientific collaboration. I examine the epistemic structure of scientific collaboration and argue that it gives rise to two arguments showing that moral and social values can legitimately play a role in scientists’ decision to accept something as scientific knowledge. In the case of scientific collaboration some moral and social values are properly understood to be extrinsic epistemic values, that is, values that promote the attainment of scientific knowledge.

In a number of publications, John Earman has advocated a tertium quid to the usual dichotomy between substantivalism and relationism concerning the nature of spacetime. The idea is that the structure common to the members of an equivalence class of substantival models is captured by a Leibniz algebra which can then be taken to directly characterize the intrinsic reality only indirectly represented by the substantival models. An alleged virtue of this is that, while a substantival interpretation of spacetime theories falls prey to radical local indeterminism, the Leibniz algebras do not.

I argue that the program of Leibniz algebras is subject to radical local indeterminism to the same extent as substantivalism. In fact, for the category of topological spaces of interest in spacetime physics, the program is equivalent to the original spacetime approach. Moreover, the motivation for the program—that isomorphic substantival models should be regarded as representing the same physical situation—is misguided.

Ontic structural realism (OSR) is crucially motivated by empirical discoveries of fundamental physics. To this extent its potential to furnish a general metaphysics for science may appear limited. However, OSR also provides a good account of the progress that has been achieved over the decades in a formalized special science, economics. Furthermore, this has a basis in the ontology presupposed by economic theory, and is not just an artifact of formalization.

According to some cosmologists, the big bang cosmogony and even the (now largely defunct) steady-state theory pose a scientifically insoluble problem of matter-energy creation. But I argue that the genuine problem of the origin of matter-energy or of the universe has been fallaciously transmuted into the pseudo-problem of creation by an external cause. A fortiori, it emerges that the initial “true” and “false” vacuum states of quantum cosmology do not vindicate biblical divine creation ex nihilo at all.

Ecologists have proposed several incompatible definitions of ecological stability. Emulating physicists, mathematical ecologists commonly define it as Lyapunov stability. This formalizes the problematic concept by integrating it into a well-developed mathematical theory. The formalization also seems to capture the intuition that ecological stability depends on how ecological systems respond to perturbation. Despite these advantages, this definition is flawed. Although Lyapunov stability adequately characterizes perturbation responses of many systems studied in physics, it does not for ecological systems. This failure reveals a limitation of its underlying mathematical theory, and an important difference between dynamic systems modeling in physics and ecology.

This article proposes to explicate theoretical equivalence by supplementing formal equivalence criteria with preservation conditions concerning interpretation. I argue that both the internal structure of models and choices of morphisms are aspects of formalisms that are relevant when it comes to their interpretation. Hence, a formal criterion suitable for being supplemented with preservation conditions concerning interpretation should take these two aspects into account. The two currently most important criteria—generalized definitional equivalence (Morita equivalence) and categorical equivalence—are not optimal in this respect. I put forward a criterion that takes both aspects into account: the criterion of definable categorical equivalence.

What must laypersons understand about science to allow them to make sound decisions on science-related issues? Relying on recent developments in social epistemology, this article argues that scientific education should have the goal not of bringing laypersons’ understanding of science closer to that of expert insiders but rather of cultivating the kind of competence characteristic of “competent outsiders.” Moreover, it argues that philosophers of science have an important role to play in attempts to promote this kind of understanding but that, to successfully fulfill this role, they will have to approach central questions in the field differently.

Psychometrically oriented researchers construe low interrater reliability measures for expert peer reviewers as damning for the practice of peer review. I argue that this perspective overlooks different forms of normatively appropriate disagreement among reviewers. Of special interest are Kuhnian questions about the extent to which variance in reviewer ratings can be accounted for by normatively appropriate disagreements about how to interpret and apply evaluative criteria within disciplines during times of normal science. Until these empirical-cum-philosophical analyses are done, it will remain unclear the extent to which low interrater reliability measures represent reasonable disagreement rather than arbitrary differences between reviewers.

We argue that the analysis of cognitive attitudes should play a central role in developing more sophisticated accounts of the proper roles for values in science. First, we show that the major recent efforts to delineate appropriate roles for values in science would be strengthened by making clearer distinctions among cognitive attitudes. Next, we turn to a specific example and argue that a more careful account of the distinction between the attitudes of belief and acceptance can contribute to a better understanding of the proper roles for values in a case study from paleoanthropology.

Diagrams have distinctive characteristics that make them an effective medium for communicating research findings, but they are even more impressive as tools for scientific reasoning. To explore this role, we examine diagrammatic formats that have been devised by biologists to (a) identify and illuminate phenomena involving circadian rhythms and (b) develop and modify mechanistic explanations of these phenomena.

Many philosophers of science have argued that social and ethical values have a significant role to play in core parts of the scientific process. This naturally suggests the following question: when such value choices need to be made, which or whose values should be used? A common answer to this question turns to democratic values—the values of the public or its representatives. I argue that this imposes a morally significant burden on certain scientists, effectively requiring them to advocate for policy positions they strongly disagree with. I conclude by discussing under what conditions this burden might be justified.

In previous publications I have argued that much scientific activity should be thought of as involving the operation of distributed cognitive systems. Since these contributions to the cognitive study of science appear in venues not necessarily frequented by philosophers of science, I begin with a brief introduction to the notion of a distributed cognitive system. I then describe what I take to be an exemplary case of a scientific distributed cognitive system, the Hubble Space Telescope (HST). I do not here reargue the case for conceiving of systems like the HST as distributed cognitive systems. Rather, I examine a question that arises once one has adopted the perspective of distributed cognitive systems, namely, the role of agency in a distributed cognitive system. Here I argue, contrary to several advocates of distributed cognitive systems, that we should regard the human components of distributed cognitive systems as the only sources of agency within such systems. In particular, we should not extend notions of agency to such systems as a whole.

Axiomatizations of measurement systems usually require an axiom—called an Archimedean axiom—that allows quantities to be compared. This type of axiom has a different form from the other measurement axioms, and cannot—except in the most trivial cases—be empirically verified. In this paper, representation theorems for extensive measurement structures without Archimedean axioms are given. Such structures are represented in measurement spaces that are generalizations of the real number system. Furthermore, a precise description of “Archimedean axioms” is given and it is shown that in all interesting cases “Archimedean axioms” are independent of other measurement axioms.

Kripke and Putnam have proposed that terms may be introduced to refer to theoretical entities by means of causal descriptions such as 'whatever causes observable effects O'. It is argued that such a reference-fixing definition is ill-formed and that theoretical beliefs must be involved in fixing the reference of a theoretical term. Some examples of reference-fixing are discussed e.g., the term 'electricity'. The Kripke-Putnam theory can not give an account of how terms may be introduced into science and then subsequently be discovered to be non-referring. A modified account of reference-fixing is suggested in which terms such as Gilbert's ‘electric effluvia’ and ‘phlogiston’ can be introduced into science and then be found to lack a reference.

A high heritability estimate usually corresponds to a situation in which trait variation is largely caused by genetic variation. However, in some cases of gene-environment covariance, causal intuitions about the sources of trait difference can vary, leading experts to disagree as to how the heritability estimate should be interpreted. We argue that the source of contention for these cases is an inconsistency in the interpretation of the concepts ‘genotype’, ‘phenotype’, and ‘environment’. We propose an interpretation of these terms under which trait variance initially caused by genetic variance is subsumed into a heritability for all cases of gene-environment covariance.