A recent article (Leeds and Healey 1996) argues that the modal interpretation (Copenhagen variant) of quantum mechanics does not do justice to immediately repeated non-disturbing measurements. This objection has been raised before, but the article presents it in a new, detailed, precise form. I show that the objection is mistaken.

John Greenwood (this issue) claims that neglect of an important methodological distinction has contributed directly to the “epistemic impoverishment” of empirical studies of all forms of professional psychotherapy. I challenge this claim, as well as other important claims he makes about the efficacy of psychoanalysis and other forms of psychotherapy.

Evolutionary models can explain the dynamics of populations, how genetic, genotypic, or phenotypic frequencies change with time. Models incorporating chance, or drift, predict specific patterns of change. These are illustrated using classic work on blood types by Cavalli-Sforza and his collaborators in the Parma Valley of Italy, in which the theoretically predicted patterns are exhibited in human populations. These data and the models display properties of ensembles of populations. The explanatory problem needs to be understood in terms of how likely an observed change, in either a population or an ensemble, would be under drift alone; this is fundamentally a matter of chance. Understood in this way, issues of drift and chance undercut most recent philosophical, but not biological, discussions of the role of “genetic drift.”

In 1932, John von Neumann argued for the equivalence of the thermodynamic entropy and −Trρlnρ, since known as the von Neumann entropy. Meir Hemmo and Orly R. Shenker recently challenged this argument by pointing out an alleged discrepancy between the two entropies in the single-particle case, concluding that they must be distinct. In this article, their argument is shown to be problematic as it (a) allows for a violation of the second law of thermodynamics and (b) is based on an incorrect calculation of the von Neumann entropy.

Simple random-sampling resolutions of the raven paradox relevantly diverge from scientific practice. We develop a stratified random-sampling model, yielding a better fit and apparently rehabilitating simple random sampling as a legitimate idealization. However, neither accommodates a second concern, the objection from potential bias. We develop a third model that crucially invokes causal considerations, yielding a novel resolution that handles both concerns. This approach resembles Inference to the Best Explanation (IBE) and relates the generalization’s confirmation to confirmation of an associated law. We give it an objective Bayesian formalization and discuss the compatibility of Bayesianism and IBE.

A minimal essentialism (“intrinsic biological essentialism”) about natural kinds is required to explain the projectability of human science terms. Human classifications that yield robust and ampliative projectable inferences refer to biological kinds. I articulate this argument with reference to an intrinsic essentialist account of homeostatic property cluster kinds. This account implies that human sciences (e.g., medicine, psychiatry) that aim to formulate predictive kind categories should classify biological kinds. Issues concerning psychiatric classification and pluralism are examined.

A serious problem for covering law explanation is raised and its consequences for the Hempelian theory of explanation are discussed. The problem concerns an intensional feature of explanations, involving the manner in which theoretical law statements are related to the events explained. The basic problem arises because explanations are not of events but of events under descriptions ; moreover, in a sense, our linguistic descriptions outrun laws. One form of the problem, termed the problem of weak intensionality, is apparently solved by a simple logical move, but in fact the problem arises in a new, strong form. It is found that Hempel's model for deductive explanation (to which this discussion is confined) requires modification to handle the weak intensionality problem but then is faced with the problem of strong intensionality. In consequence, it is suggested that Hempel's important concept of explanation sketch is not as widely applicable as usually claimed, especially for explanations in the behavioral and social sciences and history. Reason is found to reject the covering law thesis that every scientific explanation must contain at least one law statement. An important feature of the discussion is that some of the main reasons given for altering the deductive model and for considering other forms of explanation are internal to the covering law theory.

To make sense of large data sets, we often look for patterns in how data points are “shaped” in the space of possible measurement outcomes. The emerging field of topological data analysis (TDA) offers a toolkit for formalizing the process of identifying such shapes. This article aims to discover why and how the resulting analysis should be understood as reflecting significant features of the systems that generated the data. I argue that a particular feature of TDA—its functoriality—is what enables TDA to translate visual intuitions about structure in data into precise, computationally tractable descriptions of real-world systems.

I pose problems for the views that human nature should be the object of study in the social and behavioral sciences and that a concept of human nature is needed to guide research in these sciences. I proceed by outlining three research programs in the social sciences, each of which confronts aspects of human variation. Next, I present Elizabeth Cashdan and Grant Ramsey’s related characterizations of human nature. I go on to argue that the research methodologies they each draw on are more productive resources for social scientists than their competing characterizations of human nature.

This article discusses Kevin Kelly’s recent attempt to justify Ockham’s Razor in terms of truth-finding efficiency. It is argued that Kelly’s justification fails to warrant confidence in the empirical content of theories recommended by Ockham’s Razor. This is a significant problem if, as Kelly and many others believe, considerations of simplicity play a pervasive role in scientific reasoning, underlying even our best tested theories, for the proposal will fail to warrant the use of these theories in practical prediction.

Most philosophers of science nowadays hold a network or postulational view of the meaning of theoretical words. However, there are many nuances to this view, and after explicitly separating them, we show what we take to be wrong with each one. While we reject the postulational view we do not defend its traditional alternatives either; rather we show the pointlessness of insisting on a single source for the meaning of theoretical words. We also point out the shortcomings of Carnap's newest meaning criterion which depends upon a network view. But, again, we suggest not only that this new rendition of the criterion is faulty but also that there is something misguided about any search at all for such a criterion.

We describe two anomalies in Bohm’s quantum theory that shed light on the notion of probability zero in quantum mechanics. In one anomaly the preferred reference frame may be discovered.

Randomized controlled trials are currently the gold standard within evidence-based medicine. Usually they are monitored for early signs of effectiveness or harm. However, evidence from trials stopped early is often charged with bias toward implausibly large effects. To our mind, this skeptical attitude is unfounded and caused by the failure to perform appropriate conditioning in the statistical analysis of the evidence. We contend that conditional hypothesis tests give a superior appreciation of the obtained evidence and significantly improve the practice of sequential medical trials, while staying firmly rooted in frequentist methodology.

In this essay I argue that there are strong reasons for preserving the concept of race in both medical and sociological contexts. While I argue that there are important reasons to conceive of race as picking out distinctions among populations that are both legitimate and important, the notion of race that I advocate in this essay differs in fundamental ways from traditional folk notions of race. As a result, I believe that the folk understanding of race needs to be either revised or eliminated altogether.

When we consider closely any highly integrated vital process, like embryonic development, or animal behavior of the end-subserving or purposive type, we are inevitably impressed with the importance of those special controlling factors, collectively termed “regulative,” which appear chiefly responsible for the unified and finalistic character of the whole sequence of events. These factors are persistent in their influence although they may act intermittently. Without their presence the sequence would soon lose coördination and “run wild,” just as an automobile runs off the road unless occasional compensating touches are given to the steering wheel. They are the factors which give unity and direction to the total process. Generalizing, we may say that in any complex unified process, especially a synthetic one—where the progress is from less to greater complexity—integration seems always to imply or presuppose the operation of regulative factors having the character which we call directive. These keep the sequence of events to a definite course which in the living organism usually terminates in some outcome having special biological significance, or survival value.

Von Mises defined a “physical” probability as a strict limit of the relative frequency of occurrence of an event in repeated trials. As a result of a number of criticisms of von Mises's approach, the more favored approach became the “propensity” interpretation. It is argued here that this interpretation is not compelling and that the only problem in von Mises's approach is the assumption that the relative frequency converges in a strict sense. This problem is then remedied by deducing the axioms of probability theory from the assumption that the relative frequency converges only in the sense of the weak law of large numbers.