The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...) philosophy of measurement: it is epistemological, coherentist, practice oriented, and model based. (shrink)

Douglas proposes a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, protecting the integrity and objectivity of science.

This is an important book precisely because there is none other quite like it.

This article critically analyses the concept of evidence in evidence‐based policy, arguing that there is a key problem: there is no existing practicable theory of evidence, one which is philosophically‐grounded and yet applicable for evidence‐based policy. The article critically considers both philosophical accounts of evidence and practical treatments of evidence in evidence‐based policy. It argues that both fail in different ways to provide a theory of evidence that is adequate for evidence‐based policy. The article contributes to the debate about how (...) evidence can and should be used to reduce contingency in science and in policy based on science. (shrink)

Patient-reported outcome measures (PROMs) are increasingly used to assess multiple facets of healthcare, including effectiveness, side effects of treatment, symptoms, health care needs, quality of care, and the evaluation of health care options. There are thousands of these measures and yet there is very little discussion of their theoretical underpinnings. In her 2008 Presidential address to the Society for Quality of Life Research (ISOQoL), Professor Donna Lamping challenged researchers to grapple with the theoretical issues that arise from these measures. In (...) this paper, I attempt to do so by arguing for an analogy between PROMs and Hans-Georg Gadamer’s logic of question and answer. While researchers readily admit that the constructs involved in PROMs are imperfectly understood and lack a gold standard, they often ignore the consequences of this fact. Gadamer’s work on questions and their importance to philosophical hermeneutics helps to show that the questions researchers ask about such constructs are also imperfectly understood. I argue that these questions should not be standardized, and I instead propose a theoretical framework that understands PROMs as posing genuine questions to respondents—questions that are open to reinterpretation. (shrink)

Evidence-based psychiatry (EBP) has arisen through the application of evidence-based medicine (EBM) to psychiatry. However, there may be aspects of psychiatric disorders and treatments that do not conform well to the assumptions of EBM. This paper reviews the ongoing debate about evidence-based psychiatry and investigates the applicability, to psychiatry, of two basic methodological features of EBM: prognostic homogeneity of clinical trial groups and quantification of trial outcomes. This paper argues that EBM may not be the best way to pursue psychiatric (...) knowledge given the particular features of psychiatric disorders and their treatments. As a result, psychiatry may have to develop its own standards for rigour and validity. This paper concludes that EBM has had a powerful influence on how psychiatry investigates and understands mental disorders. Psychiatry could influence EBM in return, reshaping it in ways that are more clinically useful and congruent with patients’ needs. (shrink)

The second edition of The Great Psychotherapy Debate has been updated and revised to include a history of healing practices, medicine, and psychotherapy, an expanded theoretical presentation of the contextual model, an examination of therapist effects, and a thorough review of the research on common factors such as the alliance, expectations, and empathy.

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

Well–being, health and freedom are some of the many phenomena of interest to science whose definitions rely on a normative standard. Empirical generalizations about them thus present a special case of value-ladenness. I propose the notion of a ‘mixed claim’ to denote such generalizations. Against the prevailing wisdom, I argue that we should not seek to eliminate them from science. Rather, we need to develop principles for their legitimate use. Philosophers of science have already reconciled values with objectivity in several (...) ways, but none of the existing proposals are suitable for mixed claims. Using the example of the science of well-being, I articulate a conception of objectivity for this science and for mixed claims in general. _1_ Introduction _2_ What Are Mixed Claims? _3_ Mixed Claims Are Different _3.1_ Values as reasons to pursue science _3.2_ Values as agenda-setters _3.3_ Values as ethical constraints on research protocols _3.4_ Values as arbiters between underdetermined theories _3.5_ Values as determinants of standards of confirmation _3.6_ Values as sources of wishful thinking and fraud _4_ Mixed Claims Should Stay _4.1_ Against Nagel _5_ The Dangers of Mixed Claims _6_ The Existing Accounts of Objectivity _6.1_ The perils of impartiality _7_ Objectivity for Mixed Claims _8_ Three Rules _8.1_ Unearth the value presuppositions in methods and measures _8.2_ Check if value presuppositions are invariant to disagreements _8.3_ Consult the relevant parties _9_ Conclusion. (shrink)

Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...) to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

This paper critically analyses the concept of evidence in evidence-based-policy arguing that there is key problem: that there is no existing practicable theory of evidence, one which is philosophically grounded and yet applicable for evidencebased policy. The paper critically considers both philosophical accounts of evidence and practical treatments of evidence in evidence-based-policy. It argues that both fail in different ways to provide a theory of evidence that is adequate for evidence-basedpolicy. The paper is a valuable contribution to the part of (...) the research project that explores how evidence can and should be used to reduce contingency in science, and policy based on science. (shrink)

In Science as Social Knowledge, Helen Longino offers a contextual analysis of evidential relevance. She claims that this "contextual empiricism" reconciles the objectivity of science with the claim that science is socially constructed. I argue that while her account does offer key insights into the role that values play in science, her claim that science is nonetheless objective is problematic.

This paper critically analyses the concept of evidence in evidence-based-policy arguing that there is key problem: that there is no existing practicable theory of evidence, one which is philosophically grounded and yet applicable for evidencebased policy. The paper critically considers both philosophical accounts of evidence and practical treatments of evidence in evidence-based-policy. It argues that both fail in different ways to provide a theory of evidence that is adequate for evidence-basedpolicy. The paper is a valuable contribution to the part of (...) the research project that explores how evidence can and should be used to reduce contingency in science, and policy based on science. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

In Valuing Health, Dan Hausman argues that well-being is not measurable, at least not in the way that science and policy would require. His argument depends on a demanding conception of well-being and on a pessimistic verdict upon the existing measures of subjective well-being. Neither of these reasons, I argue, warrant as much skepticism as Hausman professes.