This paper presents two interpretations of the fiber bundle fonnalism that is applicable to all gauge field theories. The constructionist interpretation yields a substantival spacetime. The analytic interpretation yields a structural spacetime, a third option besides the familiar substantivalism and relationalism. That the same mathematical fonnalism can be derived in two different ways leading to two different ontological interpretations reveals the inadequacy of pure fonnal arguments.

Recent writings of Professor Frank raise basic questions concerning the nature of science and its relations to social, political, theological and metaphysical issues.

This paper concentrates on several of these questions. What determines the acceptance of an hypothesis in the sciences? Is it explanation of the facts and confirmation by experimentation or is it the capacity of a theory to guide human conduct? Professor Frank's espousal of the latter criterion raises the question of whether this criterion can clearly be applied. Equally important: it places on the scientist the responsibility of (a) reliably predicting the effects of a theory on human conduct and (b), deciding which effects ought to be achieved, assuming we could reliably achieve them. Another set of problems arises concerning the relation between scientific views and metaphysical, political and religious beliefs. Are the former relevant to the latter? If so, how? Does not scientific method at least involve the rejection of certain political and religious philosophies? We conclude that each and all of these difficulties could be relieved if not resolved by accepting a thoroughgoing empiricism.

In this paper, it is argued that selection and drift might be distinct. This contradicts recent arguments by Brandon (2005) and Matthen and Ariew (2002) that such a distinction “violates sound probabilistic thinking” (Matthen and Ariew 2002, 62). While their arguments might be valid under certain assumptions, they overlook a possible way to make sense of the distinction. Whether selection and drift can be thought of as causally distinct, I argue, depends on the source of probabilities in natural selection. In particular, if the probabilities used in defining fitness values are at least partly a result of abstracting from or ignoring certain features of the environment, then selection and drift might in fact be causally distinct.

Philosophical discussions of systems biology have enriched the notion of mechanistic explanation by pointing to the role of mathematical modeling. However, such accounts still focus on explanation in terms of tracking a mechanism’s operation across time (by means of mental or computational simulation). My contention is that there are explanations of molecular systems in which the explanatory understanding does not consist in tracking a mechanism’s operation and productive continuity. I make this case by a discussion of bifurcation analysis in dynamical systems, articulating the distinctive way in which explanatory understanding is provided, especially about the reversibility or irreversibility of molecular processes.

Studies in the social and biomedical sciences of racial differences in socioeconomic status or health within a population view the race of members as fixed and look for a difference in the frequency of a trait like average income or disease risk between racial subgroups. But, as I explain in this paper, there are good reasons to allow the race of members to vary with the trait whose variation within the population is to be described or explained. According to such a view of race, racial categories are more scientifically significant if membership in the categories is allowed to vary with differences in scientific interest rather than held constant across a variety of interests.

We consider the mind-dependence or independence of the “now,” of “becoming,” and of “time's arrow,” by considering the various senses in which these notions might be mind-dependent or not. These matters cannot be sensibly discussed without taking a stand regarding criteria of “reality.” Proceeding from a basically phenomenalist position we conclude that merely to differentiate between appearance and reality is implicitly to assume a directed flow of time. We discuss the relationship between phenomenological and physical time and their possible asymmetries. We find that physical time acquires meaning only through phenomenological time, and that phenomenological time is fundamentally asymmetric. This still leaves room for the question: Is there anything in physical time which reflects the fact that it, to be meaningful, must be applied asymmetrically? The relevance of relativity theory to this question is discussed.

One of the major puzzles in evolutionary theory is how communication and information transfer are possible when the interests of those involved conflict. Perfect information transfer seems inevitable if there are physical constraints, which limit the signal repertoire of an individual, effectively making bluffing an impossibility. This, I argue, is incorrect. Unfakeable signals by no means guarantee information transfer. I demonstrate the existence of a so-called pooling equilibrium and discuss why the traditional argument for perfect information transfer (Frank’s full disclosure principle) does not hold in all cases. Additionally, I demonstrate that deception is possible at equilibrium despite the fact that signals are impossible to fake.

Sewall Wright's is a mathematical test used to characterize differences between biological populations and identify causes of those differences. I discuss Cockerham and Weir's popular, empirically successful approach to statistical estimation of , arguing that their assumption that actual populations are sampled from an infinite set of counterfactual populations (with a common ancestral population) supports a view of natural selection and genetic drift as distinct causes. I also argue that the way in which F-statistics and other statistical tests are applied to computer simulations in empirical research shows that selection and drift correspond to differences in objective, causal probabilities.

There is a received view on measurement scales. It includes both a classification of scales (nominal, ordinal, interval, and ratio) and a set of prescriptions regarding measurement inferences. This article casts doubt on the adequacy of this received view. To do this, I propose an epistemic characterization of the ordinal/interval distinction, that is, one in terms of researchers’ beliefs. This novel characterization reveals the ordinal/interval distinction as too coarse grained and thus the received view as too restrictive of a framework for measurement research.

Transparency has been proposed as a way of handling value-ladenness in machine learning (ML). This article highlights limits to this strategy. I distinguish three kinds of transparency: epistemic transparency, retrospective value transparency, and prospective value transparency. This corresponds to different approaches to transparency in ML, including so-called explainable artificial intelligence and governance based on disclosing information about the design process. I discuss three sources of value-ladenness in ML—problem formulation, inductive risk, and specification gaming—and argue that retrospective value transparency is only well-suited for dealing with the first, while the third raises serious challenges even for prospective value transparency.

Recent science funding policy scholars and practitioners have advocated for the use of lotteries, or elements of random chance, as supplementations of traditional peer review for evaluating grant applications. One of the primary motivations for lotteries is their purported openness to innovative research. The purpose of this article is to argue that current proponents of funding science by lottery overestimate the viability of peer review and thus unduly restrict the scope of lotteries in science funding practice. I further show how this analysis suggests a different way of introducing lotteries into science funding policy.

Developing tools is a crucial aspect of experimental practice, yet most discussions of scientific change traditionally emphasize theoretical over technological change. To elaborate on the role of tools in scientific change, I offer an account that shows how scientists use tools in exploratory experiments to form novel concepts. I apply this account to two cases in neuroscience and show how tool development and concept formation are often intertwined in episodes of tool-driven change. I support this view by proposing common normative principles that specify when exploratory concept formation and tool development succeed (rather than fail) to initiate scientific change.

Children acquire complex concepts like dog earlier than simple concepts like brown, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it is easier to infer the meaning of complex concepts than that of simple concepts.

The idea that science aspires to and routinely achieves truths about the world has been challenged in recent writings. Rather than beginning with a theory of scientific development, or of scientific explanation, we begin with a consideration of truth claims in ordinary discourse, particularly with Davidson's truth-functional semantics. Next we consider the way in which some framework features of ordinary language discourse are extended to and modified in scientific discourse. Two areas are treated in more detail: quantum theory, and the peculiar problem of semantic entailment it involves; and quantum field theory. These supply a basis for criticizing some historicist and logicist treatments of the truth of scientific claims.

In Dynamics of Reason, Michael Friedman uses the example of Galilean rectilinear inertia to support his defense of scientific rationality against postpositivist skepticism. However, Friedman's treatment of the case is flawed, such that his model of scientific change fails to fit the historical evidence. I present the case of Galileo, showing how it supports Friedman's view of scientific knowledge but undermines his view of scientific change. I then suggest reciprocal iteration as an amendment of Friedman's view that better accounts for scientific change.

Models that fail to satisfy the Markov condition are unstable because changes in state variable values may cause changes in the values of background variables, and these changes in background lead to predictive error. Such error arises because non-Markovian models fail to track the causal relations generating the values of response variables. This has implications for discussions of the level of selection: under certain plausible conditoins most standard models of group selection will not satisfy the Markov condition when fit to data from real populations. These models neither correctly represent the causal structure generating nor correctly explain the phenomena of interest.

Constitutional schemata have been of continuing interest in medicine and psychology ever since the time of Hippocrates. With the work of Sheldon, Stevens and Tucker (5, 6), biotypology has been placed on a new basis. The reader who wishes to orient himself quickly and without too much detail, to the subject matter of typology, will find an interesting and substantial review by Anastasi (1). Wertheimer and Hesketh (7) have produced a comprehensive, but brief, historical and analytic treatment of the constitutional approach in their rather short monograph on the subject. Hempel and Oppenehim (2) have examined the concept of psychological type in a novel fashion from the standpoint of modern logic and positivist philosophy. Typology has been of more interest to continental writers than to American writers. Numerous medical school dissertations at European universities attest to this fact. Medical and psychological literature on the subject is also more frequently of European or Latin American origin, than of United States origin, as a cursory glance at the Index Medicus (4) or the Surgeon General's Catalogue (3) will quickly reveal. The work of Sheldon has raised fresh theoretical considerations which we propose to outline to some extent in this paper and the above sources, we feel certain, will furnish sufficient orientation to those readers who come to this subject with little or no previous acquaintance with it. Before going any further the reader is urged to read Chapter V of the “Varieties of Human Physique” (5).

A publication by Professor Margenau is always of interest to persons concerned with philosophy of science. This is especially true, however, of his recently published book, The Nature of Physical Reality; for this book, dealing with basic epistemological problems arising from the development of modern quantum mechanics, is the most comprehensive and most systematic formulation of its author's philosophical position and is at the same time conceived as a “challenge” to “uncritical realism, unadorned operationalism, and radical empiricism”—to points of view, that is, which Professor Margenau regards as “outmoded and in disharmony with the successful phases of contemporary physics” (v).

Through an analysis of conditions under which the question of spatial anisotropy can be raised, the present paper brings out intimate conceptual relationships between the scientific concept of space and the concepts of entities, behavior, and explanation specified by scientific theories. Thus scientific departures from ordinary usage (or from usage in other scientific theories) of the term “space” entail corresponding shifts in the use of other terms not generally seen to be connected. As a case study of the relations between these terms, and of the refusal to allow the possibility of spatial anisotropy, Newtonian mechanics is examined.