Subjective measures of well-being—measures based on answers to questions such as ‘Taking things all together, how would you say things are these days—would you say you're very happy, pretty happy, or not too happy these days?’—are often presented as superior to more traditional economic welfare measures, e.g., for public policy purposes. This paper aims to spell out and assess what I will call the argument from directness: the notion that subjective measures of well-being better represent well-being than economic measures do (...) because subjective measures (and subjective measures alone) are direct measures of well-being. My main thesis is that the argument begs the question against proponents of economic measures: it is based on a premise that they reject and that is no less in need of justification than the conclusion of the argument, namely, the proposition that well-being is constituted by subjectively experienced mental states. If subjective measures can be defended as valid measures of well-being at all, I will maintain, it is because they are (imperfect) indirect measures of well-being. (shrink)

What makes a measure of well-being valid? The dominant approach today, construct validation, uses psychometrics to ensure that questionnaires behave in accordance with background knowledge. Our first claim is interpretive—construct validation obeys a coherentist logic that seeks to balance diverse sources of evidence about the construct in question. Our second claim is critical—while in theory this logic is defensible, in practice it does not secure valid measures. We argue that the practice of construct validation in well-being research is theory avoidant, (...) favoring a narrow focus on statistical tests while largely ignoring relevant philosophical considerations. (shrink)

Medical nihilism is the view that we should have little confidence in the effectiveness of medical interventions. Jacob Stegenga argues persuasively that this is how we should see modern medicine, and suggests that medical research must be modified, clinical practice should be less aggressive, and regulatory standards should be enhanced.

Do the new sciences of well-being provide knowledge that respects the nature of well-being? This book written from the perspective of philosophy of science articulates how this field can speak to well-being proper and can do so in a way that respects the demands of objectivity and measurement.

Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.

Erik Angner has argued that simultaneous endorsement of the representational theory of measurement and psychometrics leads to inconsistency. His claim rests on an implicit assumption: RTM and psychometrics are full-fledged approaches to measurement. I argue that RTM and psychometrics are only partial approaches that deal with different aspects of measurement, and that therefore simultaneous endorsement of the two is not inconsistent. The argument has implications for the improvement of measurement practices.

Psychometrics is one of the main approaches to social scientific measurement. It is relied upon in drug testing, economic policymaking, recruitment, and other decision-making contexts. The first aim of this article is to introduce philosophers to key aspects of psychometrics, namely, classical test theory, item response theory, and construct validity. The second aim is to show how a debate on the nature of psychological attributes manifests in psychometrics. In this debate, realists claim that psychometric measures are indicators of independently existing (...) qualities, while operationalists argue that a measure defines its target attribute. The third and final aim is to argue that despite its poor reputation among philosophers, operationalism is a viable approach to psychometrics. (shrink)

Psychologists say a measure has construct validity when it, in fact, measures the construct it is intended to measure. Construct validity is both an important notion in psychological research methods and the source of much confusion and debate among psychologists. I argue that this confusion arises, in part, because of a failure to distinguish between construct validity, a feature of measures relative to a construct, and construct legitimacy, a feature of the construct itself. I propose a prescriptive account of construct (...) validity on the basis of this distinction, then provide evidence for my account through two examples from research psychology. (shrink)

This paper develops axiomatic foundations for a probabilistic-interventionist theory of causal strength. Transferring methods from Bayesian confirmation theory, I proceed in three steps: I develop a framework for defining and comparing measures of causal strength; I argue that no single measure can satisfy all natural constraints; I prove two representation theorems for popular measures of causal strength: Pearl's causal effect measure and Eells' difference measure. In other words, I demonstrate these two measures can be derived from a set of plausible (...) adequacy conditions. The paper concludes by sketching future research avenues. (shrink)

I present a new definition of verisimilitude, framed in terms of causes. Roughly speaking, according to it a scientific model is approximately true if it captures accurately the strengths of the causes present in any given situation. Against much of the literature, I argue that any satisfactory account of verisimilitude must inevitably restrict its judgments to context-specific models rather than general theories. We may still endorse—and only need—a relativized notion of scientific progress, understood now not as global advance but rather (...) as the mastering of particular problems. This also sheds new light on longstanding difficulties surrounding language-dependence and models committed to false ontologies. (shrink)

As for most measurement procedures in the course of their development, measures of consciousness face the problem of coordination, i.e., the problem of knowing whether a measurement procedure actually measures what it is intended to measure. I focus on the case of the Perceptual Awareness Scale to illustrate how ignoring this problem leads to ambiguous interpretations of subjective reports in consciousness science. In turn, I show that empirical results based on this measurement procedure might be systematically misinterpreted.

Is it possible to measure psychological attributes like intelligence, personality and attitudes and if so, how does that work? What does the term 'measurement' mean in a psychological context? This fascinating and timely book discusses these questions and investigates the possible answers that can be given response. Denny Borsboom provides an in-depth treatment of the philosophical foundations of widely used measurement models in psychology. The theoretical status of classical test theory, latent variable theory and positioned in terms of the underlying (...) philosophy of science. Special attention is devoted to the central concept of test validity and future directions to improve the theory and practice of psychological measurement are outlined. (shrink)

Within the context of psychological measurement, realist commitments pervade methodology. Further, there are instances where particular scientific practices and decisions are explicable most plausibly against a background assumption of epistemic realism. That psychometrics is a realist enterprise provides a possible toehold for Stephen Jay Gould’s objections to psychometrics in The Mismeasure of Man and Joel Michell’s charges that psychometrics is a “pathological science.” These objections do not withstand scrutiny. There are no fewer than three activities in ongoing psychometric research which (...) presuppose a commitment to a minimal epistemic realism. Those activities include selecting between different models for representing data, estimating ability in the context of item response theory, and the move to make the individual the fundamental unit of analysis in psychometrics thereby calling for a shift in what sorts of data are evidentially relevant. In none of these activities are the commitments and disregard for evidence that Gould and Michell find objectionable or “pathological.”. (shrink)

It is widely believed that many of the competing accounts of scientific explanation have ramifications which are relevant to the scientific realism debate. I claim that the two issues are orthogonal. For definiteness, I consider Cartwright's argument that causal explanations secure belief in theoretical entities. In Section I, van Fraassen's anti-realism is reviewed; I argue that this anti-realism is, prima facie, consistent with a causal account of explanation. Section II reviews Cartwright's arguments. In Section III, it is argued that causal (...) explanations do not license the sort of inferences to theoretical entities that would embarass the anti-realist. Section IV examines the epistemic commitments involved in accepting a causal explanation. Section V presents my conclusions: contra Cartwright, the anti-realist may incorporate a causal account of explanation into his vision of science in an entirely natural way. (shrink)

It is always awkward when someone asks me informally what I’m working on and I answer that I’m trying to figure out what gender is. For outside a rather narrow segment of the academic world, the term ‘gender’ has come to function as the polite way to talk about the sexes. And one thing people feel pretty confident about is their knowledge of the difference between males and females. Males are those human beings with a range of familiar primary and (...) secondary sex characteristics, most important being the penis; females are those with a different set, most important being the vagina or, perhaps, the uterus. Enough said. Against this background, it isn’t clear what could be the point of an inquiry, especially a philosophical inquiry, into “what gender is”. (shrink)

Causation is at once familiar and mysterious. Neither common sense nor extensive philosophical debate has led us to anything like agreement on the correct analysis of the concept of causation, or an account of the metaphysical nature of the causal relation. Causation: A User's Guide cuts a clear path through this confusing but vital landscape. L. A. Paul and Ned Hall guide the reader through the most important philosophical treatments of causation, negotiating the terrain by taking a set of examples (...) as landmarks. They clarify the central themes of the debate about causation, and cover questions about causation involving omissions or absences, preemption and other species of redundant causation, and the possibility that causation is not transitive. Along the way, Paul and Hall examine several contemporary proposals for analyzing the nature of causation and assess their merits and overall methodological cogency.The book is designed to be of value both to trained specialists and those coming to the problem of causation for the first time. It provides the reader with a broad and sophisticated view of the metaphysics of the causal relation. (shrink)

This book presents the concept of “complementary science” which contributes to scientific knowledge through historical and philosophical investigations. It emphasizes the fact that many simple items of knowledge that we take for granted were actually spectacular achievements obtained only after a great deal of innovative thinking, painstaking experiments, bold conjectures, and serious controversies. Each chapter in the book consists of two parts: a narrative part that states the philosophical puzzle and gives a problem-centred narrative on the historical attempts to solve (...) the puzzle; and the analysis part which provides in-depth analyses of certain scientific, historical, and philosophical aspects of the story. (shrink)

There is a widely held view on measurement inferences, that goes back to Stevens’s ([1946]) theory of measurement scales and ‘permissible statistics’. This view defends the following prohibition: you should not make inferences from averages taken with ordinal scales (versus quantitative scales: interval or ratio). This prohibition is general—it applies to all ordinal scales—and it is sometimes endorsed without qualification. Adhering to it dramatically limits the research that the social and biomedical sciences can conduct. I provide a Bayesian analysis of (...) this inferential problem, determining when measurements from ordinal scales can be used to confirm hypotheses about relative group averages. The prohibition, I conclude, cannot be upheld, even in a qualified sense. The beliefs needed to make average comparisons are less demanding than those appropriate for quantitative scales. I illustrate with the alleged paradigm ordinal scale, Mohs’ scale of mineral hardness, arguing that the literature has mischaracterized it. (shrink)