The mutual influence of science and values in biology is exhibited in several cases from the biological literature. It is argued in a number of cases, from R. A. Fisher's argument for the optimality of a 50:50 sex ratio to A. Jensen's defense of a genetic basis for intelligence, and including work on the evolution of sexual dimorphism and muted aggression, that the credence accorded the views is disproportionate with their theoretical and empirical warrant. It is, furthermore, suggested that the proper explanation for the attraction and persistence of such views lies in their conformity with ideological norms. There is thus an important, if circumscribed, role for ideological critique in the evaluation of scientific theories; in particular, it lies in the explanation of the acceptance and persistence of scientific views, given independent grounds for questioning their justifiability.

I argue that ductal carcinoma in situ (DCIS), the tumor most commonly diagnosed by breast mammography, cannot be confidently classified as cancer, that is, as pathological. This is because there may not be dysfunction present in DCIS—as I argue based on its high prevalence and the small amount of risk it conveys—and thus DCIS may not count as a disease by dysfunction-requiring approaches, such as Boorse’s biostatistical theory and Wakefield’s harmful dysfunction account. Patients should decide about treatment for DCIS based on the risks it poses and the risks and benefits of treatment, not on its disease status.

In his award-winning contribution to the biannual PSA conference at Pittsburgh in 2008, Christian Wüthrich mounted an argument against structuralism about space-time in the context of the general theory of relativity (GTR), to the effect that structuralists cannot discern space-time points: an “abysmal embarrassment” for the structuralist, Wüthrich judged. Wüthrich's characterization of space-time structuralism is however incorrect. We demonstrate how, on the basis of a correct characterization of space-time structuralism, it is possible to discern space-time points in the GTR structures under consideration. Thus Wüthrich's argument crumbles.

The contingentist/inevitabilist debate contests whether the results of successful science are contingent or inevitable. This article addresses lingering ambiguity in the way contingency is defined in this debate. I argue that contingency in science can be understood as a collection of distinct concepts, distinguished by how they hold science contingent, by what elements of science they hold contingent, and by what those elements are contingent upon. I present a preliminary taxonomy designed to characterize the full-range positions available and illustrate that these constitute a diverse array rather than a spectrum.

Mathematical idealizations are scientific representations that result from assumptions that are believed to be false, and where mathematics plays a crucial role. I propose a two stage account of how to rank mathematical idealizations that is largely inspired by the semantic view of scientific theories. The paper concludes by considering how this approach to idealization allows for a limited form of scientific realism.

In recent years, feminist philosophy of science has been subjected to criticism. The debate has focused on the implications of the underdetermination thesis for accounts of the role of social values in scientific reasoning. My aim here is to offer a different approach. I suggest that feminist philosophers of science contribute to our understanding of science by (1) producing gender-sensitive analyses of the social dimensions of scientific inquiry and (2) examining the relevance of these analyses for normative issues in philosophy of science.

The partial cooperation displayed by subjects in the Centipede Game deviates radically from the predictions of traditional game theory. Even standard, infinite population, evolutionary settings have failed to provide an explanation for this behavior. However, recent work in finite population evolutionary models has shown that such settings can produce radically different results from the standard models. This paper examines the evolution of partial cooperation in finite populations. The results reveal a new possible explanation that is not open to the standard models and gives us reason to be cautious when employing these otherwise helpful idealizations.

The philosophy of quantum mechanics has often been conceived by physicists as a collection of dogmas concerning what can be measured, observed and known. To this branch of dialectics the present paper does not attempt to contribute, chiefly because it is written from the conviction that no part of science, nor any philosophy, can safely predict what may be feasible or knowable. Rather, this brief essay endeavors to expose the epistemology of quantum physics in a way which allows it to be recognized as an extension of the ordinary processes of cognition, as the continuation of a line which starts in sensory perception, leads straight through the methods of classical physics into quantum mechanics and shows no signs of terminating even there.

There is a strong philosophical intuition that direct study of the brain can and will constrain the development of psychological theory. When this intuition is tested against case studies on the neurophysiology and psychology of perception and memory, it turns out that psychology has led the way toward knowledge of neurophysiology. An abstract argument is developed to show that psychology can and must lead the way in neuroscientific study of mental function. The opposing intuition is based on mainly weak arguments about the fundamentality or objectivity of physics or physiology in relation to psychology.

The aim of this paper is twofold: first to sketch a framework for classifying a wide range of conceptions of scientific objectivity and second to present and defend a conception of scientific objectivity that fills a neglected niche in the resulting hierarchy of viewpoints. Roughly speaking, the proposed ideal of scientific objectivity is effectiveness in the informal but technical sense of an effective method. Science progresses when “higher levels of communicative discourse” are reached by transforming subjective judgments regarding the generation and reduction of data or the testing of theories into objective decision procedures that are automatic or mechanical.

The error statistical account of testing uses statistical considerations, not to provide a measure of probability of hypotheses, but to model patterns of irregularity that are useful for controlling, distinguishing, and learning from errors. The aim of this paper is (1) to explain the main points of contrast between the error statistical and the subjective Bayesian approach and (2) to elucidate the key errors that underlie the central objection raised by Colin Howson at our PSA 96 Symposium.

In Philosophical Problems of Statistical Inference, Seidenfeld argues that the Neyman-Pearson (NP) theory of confidence intervals is inadequate for a theory of inductive inference because, for a given situation, the ‘best’ NP confidence interval, [CIλ], sometimes yields intervals which are trivial (i.e., tautologous). I argue that (1) Seidenfeld's criticism of trivial intervals is based upon illegitimately interpreting confidence levels as measures of final precision; (2) for the situation which Seidenfeld considers, the ‘best’ NP confidence interval is not [CIλ] as Seidenfeld suggests, but rather a one-sided interval [CI0]; and since [CI0] never yields trivial intervals, NP theory escapes Seidenfeld's criticism entirely; (3) Seidenfeld's criterion of non-triviality is inadequate, for it leads him to judge an alternative confidence interval, [CIalt.], superior to [CIλ] although [CIalt.] results in counterintuitive inferences. I conclude that Seidenfeld has not shown that the NP theory of confidence intervals is inadequate for a theory of inductive inference.

Critics of Bayesianism often assert that scientists are not Bayesians. The widespread use of Bayesian statistics in the field of radiocarbon calibration is discussed in relation to this charge. This case study illustrates the willingness of scientists to use Bayesian statistics when the approach offers some advantage, while continuing to use orthodox methods in other contexts. The case of radiocarbon calibration, therefore, suggests a picture of statistical practice in science as eclectic and pragmatic rather than rigidly adhering to any one theoretical position.

The notion of synonymy has recently been severely criticized, and its replacement by graded, continuous notions of one or another sort urged on general grounds. At the same time, it has usually been assumed both by critics and defenders of the notion, that synonymy and indirect discourse are in the same boat, that analyzing the latter, for instance, requires no more than an acceptable decision on the former while it requires at least that. Defenders of synonymy have thus thought it sufficient to apply their interpretations of this idea to indirect discourse, while opponents have not thought to attack such application save by way of an attack on synonymy.

Thought experiments are ubiquitous in science and especially prominent in domains in which experimental and observational evidence is scarce. One such domain is the causal analysis of singular events in history. A long-standing tradition that goes back to Max Weber addresses the issue by means of ‘what-if’ counterfactuals. In this paper I give a descriptive account of this widely used method and argue that historians following it examine difference makers rather than causes in the philosopher's sense. While difference making is neither necessary nor sufficient for causation, to establish difference makers is more consistent with the historians’ more ultimate purposes.

In recent work on the foundations of statistical mechanics and the arrow of time, Barry Loewer and David Albert have developed a view that defends both a best system account of laws and a physicalist fundamentalism. I argue that there is a tension between their account of laws, which emphasizes the pragmatic element in assessing the relative strength of different deductive systems, and their reductivism or fundamentalism. If we take the pragmatic dimension in their account seriously, then the laws of the special sciences should be part of our best explanatory system of the world, as well.

A standard requirement on natural kinds is that they be mind independent. However, many kinds in the human and social sciences, even the natural sciences, depend on human thought. This article suggests that the mind independence requirement on natural kinds be replaced with the requirement that natural kind classifications be defeasible. The defeasibility requirement does not require that natural kinds be mind independent, so it does not exclude mind dependent scientific kinds from being natural kinds. Furthermore, the defeasibility requirement captures the idea that natural kind classifications are tools for investigating the empirical world.

This article contributes to the underdeveloped field of experimental philosophy of science. We examine variability in the philosophical views of scientists. Using data from Toolbox Dialogue Initiative, we analyze scientists’ responses to prompts on philosophical issues (methodology, confirmation, values, reality, reductionism, and motivation for scientific research) to assess variance in the philosophical views of physical scientists, life scientists, and social and behavioral scientists. We find six prompts about which differences arose, with several more that look promising for future research. We then evaluate the difference between the natural and social sciences and the challenge of interdisciplinary integration across scientific branches.

Evolutionary game theoretic accounts of justice attempt to explain our willingness to follow certain principles of justice by appealing to robustness properties possessed by those principles. Skyrms (1996) offers one sketch of how such an account might go for divide-the-dollar, the simplest version of the Nash bargaining game, using the replicator dynamics of Taylor and Jonker (1978). In a recent article, D'Arms et al. (1998) criticize his account and describe a model which, they allege, undermines his theory. I sketch a theory of evolutionary explanations of justice which avoids their methodological criticisms, and develop a spatial model of divide-the-dollar with more robust convergence properties than the models of Skyrms (1996) and D'Arms et al. (1998).

Recent discussion of the statistical character of evolutionary theory has centered around two positions: (1) Determinism combined with the claim that the statistical character is eliminable, a subjective interpretation of probability, and instrumentalism; (2) Indeterminism combined with the claim that the statistical character is ineliminable, a propensity interpretation of probability, and realism. I point out some internal problems in these positions and show that the relationship between determinism, eliminability, realism, and the interpretation of probability is more complex than previously assumed in this debate. Furthermore, I take some initial steps towards a more adequate account of the statistical character of evolutionary theory.