Measurement in Science

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation (in astrophysics, ecology, economics, climatology, etc.). But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim (...) that, in experimentation, no less than in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results. (shrink)

Many studies find reflective thinking predicts less belief in God or less religiosity — so-called analytic atheism. However, the most widely used tests of reflection confound reflection with ancillary abilities such as numeracy, some studies do not detect analytic atheism in every country, experimentally encouraging reflection makes some non-believers more open to believing in God, and one of the most common sources of online research participants seems to produce lower data quality. So analytic atheism may be less than universal or (...) partially explained by confounding factors. To test this, we developed better measures, controlled for more confounds, and employed more recruitment methods. All four studies detected signs of analytic atheism above and beyond confounds (N > 70,000 people from five of six continental regions). We also discovered analytic apostasy: the better a person performed on reflection tests, the greater their odds of losing their religion since childhood — even when controlling for confounds. Analytic apostasy even seemed to explain analytic atheism: apostates were more reflective than others and analytic atheism was undetected after excluding apostates. Religious conversion was rare and unrelated to reflection, suggesting reflection’s relationships to conversion and deconversion are asymmetric. Detected relationships were usually small, indicating reflective thinking is a reliable albeit marginal predictor of apostasy. (shrink)

Psychological measurement has received strong criticism throughout the history of psychological science. Nevertheless, measurements of attributes such as emotions or intelligence continue to be widely used in research and society. I address this puzzle by presenting a new causal perspective to psychological measurement. I start with assumptions that both critics and proponents of psychological measurement are likely to accept: a minimal causal condition and the observation that most psychological concepts are ill-defined or ambiguous. Based on this, I argue that psychological (...) measurement is fundamentally different from measurement in the physical sciences but can nevertheless be useful. (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)

Psychiatric research is in crisis because of repeated failures to discover new drugs for mental disorders. Lack of measurement validity could partly account for these failures. If researchers do not actually measure the effects of drugs on the disorders they aim to investigate, one should expect suboptimal treatment outcomes. I argue that this is the case, focusing on depression, and fear & anxiety disorders. In doing so, I show how psychiatric research illustrates a more general phenomenon that I call “validity (...) drift.” A validity drift occurs when, in the course of developing new measurement procedures, researchers end up studying something different from what they originally aimed to study. I analyze the different ways in which scientists attempt to validate procedures for measuring mental disorders for the purpose of testing drugs in animal models. I show how those validation efforts might fail, thereby leading to validity drifts. Overall, this analysis highlights the complex interplay between the development of new measurement procedures, their calibration, and scientific theories of the target phenomena. (shrink)

‘Visualisations play an important role in science’, this seems to be an uncontroversial statement today. Scientists not only use visual representations as means to communicate their research results in publications or talks, but also often as surrogates for their objects of interest during the process of research. Thus, we can make a distinction between two contexts of usage here, namely the explanatory and the exploratory context. The focus of this paper is on the latter one. Obviously, using visualisations as surrogates (...) for their objects of depiction presupposes the assumption that the former can tell us something relevant about the latter. Thus, a particular referential relation between object and image has to be assumed that can transfer the relevant information. Furthermore, as science is a collaborative enterprise – a social activity – this information has to be intersubjectively accessible and stable. Nonetheless, philosophers of science still quarrel about the epistemic and ontological status of such visualisations. After all, they are means to visualise theoretical entities, such as the Higgs Boson, i.e. entities that are principally not observable with the unaided eye. Especially the significant reliance on information technology devices to access this world of the unobservable provokes a lot of suspicion with regard to the referential status of such visualisations. In this sense, quite a few philosophers adopt social constructivism as an explanatory hypothesis. A particular image is constructed with the aid of instruments and theoretical assumptions; hence it does not refer to an entity outside this system. In this paper, I will critically analyse this assumption and try to argue for an alternative point of view. (shrink)

Are widely used measurements in the human sciences (say happiness surveys or depression scales) quantitative or merely ordinal? If they are merely ordinal, could they be developed into quantitative measurements, just like in the progression from thermoscopes to thermometers? Taking inspiration from recent philosophy of measurement, some practitioners express optimism about future human science measurements. The so-called quantity objection stands out for having the only chance of settling the debate in favour of the pessimists. It claims that the problem lies (...) not with current, or likely future, measurement practices in the human sciences, but with human science attributes themselves—they just are not quantitative, but merely ordinal. Hence, they cannot not (thus will not) be measured quantitatively. The argument has a long and distinguished pedigree. This paper assesses old and recent versions of it, namely: the objection made originally to Fechner’s psychophysics by von Kries (among others) and Michell’s recent version of this objection. To do so, the paper first draws important distinctions between different versions of the argument that have been overlooked. Then, it argues that none of the versions of the quantity objection provide a good reason for the optimists to give up their optimism. In particular, Michell’s argument characterizes the measurand (that is, the attribute to be measured) in a way that optimists do not and need not accept. Yet the optimists’ defence articulated here brings with it serious burdens to discharge. The ball is in their court. (shrink)

Recent trends in psychiatry involve a transition from categorical to dimensional frameworks, in which the boundary between health and pathology is understood as a difference in degree rather than as a difference in kind. A major tenet of dimensional approaches is that no qualitative distinction can be made between health and pathology. As a consequence, these approaches tend to characterize such a threshold as pragmatic or conventional in nature. However, dimensional approaches to psychopathology raise several epistemological and ontological issues. First, (...) we review major sources of evidence usually recruited in support of the dimensional trend (focusing on clinical observation and biological data), and we show that these are connected to different conceptualizations of how dimensional traits extend across health and pathology. Second, we criticize two unquestioned assumptions that stand at the core of the dimensional trend: a) that there is continuity from health to pathology at the symptomatic level; b) that such continuity reflects an underlying continuity in the genetic liability for pathological conditions. Third, we argue against the idea of a conventional threshold by showing that such a view implies a linear relationship between the genotype and the phenotype. Fourth, drawing on epigenetics and developmental biology, we offer a characterization of mental disorders as stable and dynamic constellations of multi-level variables that differ qualitatively from ‘healthy states’. We conclude by showing that our account has several theoretical advantages over both categorical and dimensional approaches. Notably, it provides crucial insights into psychological development over time and individual differences, with major implications in terms of intervention and clinical decision-making. (shrink)

Racial discrimination is a multidimensional concept. Yet, subjective measures of racial discrimination focus on particular dimensions (interpersonal over institutional, attributable over ambiguously attributable). I argue that there is path dependence in the development and validation of subjective measures, such that existing scales prevent the development of scales that are better for some purpose. Path dependence can occur when researchers: (1) adopt a coherentist view of measurement, namely, in iteratively refining constructs and measures and (2) employ current psychometric validation practices. The (...) main takeaway is that norms are needed to evaluate the initial refinement of the construct rather than taking it for granted. (shrink)

When it originated in the late 19th century, psychometrics was a field with both a scientific and a social mission: psychometrics provided new methods for research into individual differences, and at the same time, these psychometric instruments were considered a means to create a new social order. In contrast, contemporary psychometrics - due to its highly technical nature and its limited involvement in substantive psychological research - has created the impression of being a value-free discipline. In this article, we develop (...) a contrasting characterization of contemporary psychometrics as a value-laden discipline. We expose four such values: that individual differences are quantitative (rather than qualitative), that measurement should be objective in a specific sense, that test items should be fair, and that utility of a model is more important than its truth. Our goal is not to criticize psychometrics for employing these values, but rather to bring them into the open and to show that these values are not inevitable and are in need of systematic evaluation. (shrink)

It is widely held that under ordinal utility, utility differences are ill-defined. Allegedly, for these to be well-defined (without turning to choice under risk or the like), one should adopt as a new kind of primitive quaternary relations, instead of the traditional binary relations underlying ordinal utility functions. Correlatively, it is also widely held that the key structural properties of quaternary relations are entirely arbitrary from an ordinal point of view. These properties would be, in a nutshell, the hallmark of (...) cardinal utility. While much is obviously true in these two tenets, this note explains why, as stated, they should be abandoned. Any ordinal utility function induces a rich quaternary relation. There is such a thing as ordinal utility differences. Furthermore, this induced quaternary relation respects, apart from completeness, the most standard structural properties of quaternary relations. These properties are, from an ordinal point of view, anything but arbitrary; from a quaternary perspective only completeness should be considered the hallmark—if any—of cardinal utility. These facts are explained to be especially relevant to the critical appreciation of the ordinalist methodology. (shrink)

This paper examines one aspect of the legacy of the Value-Free Ideal in conservation science: the view that measurements and metrics are value-free epistemic tools detached from ideological, ethical, social, and, generally, non-epistemic considerations. Contrary to this view, I will argue that traditional measurement practices entrenched in conservation are in fact permeated with non-epistemic values. I challenge the received view by revealing three non-epistemic assumptions underlying traditional metrics: (1) a human-environment demarcation, (2) the desirability of a people-free landscape, and (3) (...) the exclusion of cultural diversity from biodiversity. I also draw a connection between arguments for retaining traditional metrics to “scientific colonialism,” exemplified by a fortress conservation model. I conclude by advocating for abandoning the myth of the intrinsic value-freedom of measurement practices and embracing metrics aligned with societal and scientific goals. (shrink)

The validity of psychological measurement is crucially connected to a peculiar form of epistemic circularity. This circularity can be a threat when there are no independent ways to assess whether a certain procedure is actually measuring the intended target of measurement. This paper focuses on how Gustav Theodor Fechner addressed the measurement circularity that emerged in his psychophysical research. First, I show that Fechner's approach to the problem of circular measurement involved a core idealizing assumption of a shared human physiology. (...) Second, I assess Fechner's approach to this issue against the backdrop of his own epistemology of measurement and the measurement context of his time. Third, I claim that, from a coherentist and historicallysituated perspective, Fechner's quantification can be regarded as a first successful step of a longer-term quantification process. To conclude, I draw from these insights some general epistemological reflections that are relevant to current quantitative psychology. (shrink)

"Assim, este é o objetivo deste texto: mostrar como a literatura recente em torno de valores nas ciências pode nos ajudar a compreender melhor algumas das discussões em torno da mensuração da pobreza que foram suscitadas pelo trabalho de Peter Townsend. Apresentaremos primeiro o ideal da ausência de valor (seção 2), o que Townsend entendia por medidas objetivas e subjetivas (seção 3) e então poderemos compreender melhor o que é e quem não concorda com a posição de que a pobreza (...) é um juízo de valor (seção 4). Terminamos com as maneiras pelas quais é possível rejeitar essa posição (seção 5).". (shrink)

The development of the science of poverty has largely been driven by the need to define more precisely what poverty is, as well as to provide theoretical and empirical criteria for identifying those who suffer from it. This thesis focuses on a notable response to these and related questions: the conception and measure of poverty by the British sociologist Peter Townsend. Townsend defines poverty as relative deprivation caused by lack of resources. This conception, along with his corresponding cut-off measure, constitutes (...) some of the key components of his theory of poverty. The theory discusses what poverty is, its causes, and how it can be eradicated, and is detailed in Poverty in the United Kingdom: A Survey of Household Resources and Standards of Living (1979), his magnum opus. The primary aim of this thesis is to interpret the theory from Townsend’s adherence to the value-free ideal. He pursued this ideal in response to what he perceived as the pervasive and deleterious influence of moral and political values on measures, theories, and policies on poverty throughout its scientific and political history. I argue that to be free from such influence, Townsend aimed to be as guided by epistemic values as possible, which resulted in a systematic theory of poverty. -/- The thesis is structured as follows: In Chapter 1, I situate Townsend’s conception and measurement of poverty within the context of both the recent history of scientific poverty lines and the most important approaches to measuring the phenomenon. Chapter 2 discusses the systematic nature of the theory, including its role as a middle-range theory that bridges broad-range theories with empirical data. This connection is achieved through several elements: a conception of poverty; hypotheses and anthropological observations related to the elements of the conception; measures to test these hypotheses; an explanation of poverty; and reports on how the research was conducted. Furthermore, Townsend’s theory aligns with Bradburn et al.’s (2017) measurement theory, which asserts that a good measure must include a conception of the relevant phenomenon, a representation, and procedures to gather data. Additionally, all three components must be supported by arguments showing that they fit together properly. -/- In the remaining chapters, I present and discuss the main elements of the theory: his conception of poverty as relative deprivation caused by lack of resources, along with the related hypotheses and observations (Chapter 3); the representations of this conception and the procedures for data collection, processing, as well as ensuring their reliability (Chapter 4); and the explanation of poverty (Chapter 5). I conclude by presenting what Townsend considered the “policy prescriptions” of his theory. Despite its potential shortcomings, I also argue that Townsend’s theory fulfills an important epistemic value: fruitfulness. (shrink)

According to the orthodox view, one can appeal to the symmetries of a theory in order to show that it is impossible to measure the properties that are not invariant under such symmetries. For example, it is widely believed that the fact that boosts are symmetries of Newtonian mechanics entails that it is impossible to measure states of absolute motion in a Newtonian world (these states vary under boosts). This paper offers an overview of the various ways by which philosophers (...) have spelled out the connection between the symmetries of a theory and the alleged impossibility of measuring some properties (the variant ones). The paper will use the case of absolute motion as a case study, and will discuss a recent unorthodox view according to which this kind of motion can actually be measured in Newtonian mechanics. The paper ends by considering some avenues by which the discussion can be further developed. (shrink)

Thomas Kuhn's The Structure of Scientific Revolutions has sold more than one million copies since its publication in 1962, is one of the most cited academic books of all time, and continues to be read and studied today. This volume of new essays evaluates the significance of Kuhn's classic book in its changing historical context, including its initial reception and its lasting effects. The essays explore the range of ideas which Kuhn made popular with his influential philosophy of science, including (...) paradigms, normal science, paradigm changes, scientific revolutions, and incommensurability; and they also look at less-studied themes in his work, including scientific measurement, science education, and science textbooks. Drawing on the latest scholarship as well as unpublished material in the Thomas Kuhn Archives at MIT, this volume offers a comprehensive way into Kuhn's philosophy and demonstrates the continuing relevance of his ideas for our understanding of science. (shrink)

The standard interpretation of cognitive reflection tests assumes that correct responses are reflective and lured responses are unreflective. However, prior process-tracing of mathematical reflection tests has cast doubt on this interpretation. In two studies (N = 201), we deployed a validated think-aloud protocol in-person and online to test how this assumption is satisfied by the new, validated, less familiar, and less mathematical verbal Cognitive Reflection Test (vCRT). Importantly, thinking aloud did not disrupt test performance compared to a control group. Moreover, (...) verbalized thoughts in both studies revealed that most (but not all) correct responses involved reflection and that most (but not all) lured responses lacked reflection. These data suggest that the vCRT usually satisfies the standard interpretation of the reflection tests (albeit not without exceptions) and that the vCRT can be a good measure of the construct theorized by the two-factor explication of ‘reflection’ (as deliberate and conscious). (shrink)

This note contains a corrective and a generalization of results by Borsboom et al. (2008), based on Heesen and Romeijn (2019). It highlights the relevance of insights from psychometrics beyond the context of psychological testing.

Gignac and Zajenkowski (2020) find that “the degree to which people mispredicted their objectively measured intelligence was equal across the whole spectrum of objectively measured intelligence”. This Comment shows that Gignac and Zajenkowski’s (2020) finding of homoscedasticity is likely the result of a recoding choice by the experimenters and does not in fact indicate that the Dunning-Kruger Effect is a mere statistical artifact. Specifically, Gignac and Zajenkowski (2020) recoded test subjects’ responses to a question regarding self-assessed comparative IQ onto a (...) linear IQ scale when a normal IQ scale would likely have been more appropriate. More generally, researchers studying self-assessed intelligence should be aware of potential measurement problems that may arise when transforming an ordinal scale onto an interval scale. (shrink)

It is often claimed that one can avoid the kind of underdetermination that is a typical consequence of symmetries in physics by stipulating that symmetry-related models represent the same state of affairs (Leibniz Equivalence). But recent commentators (Dasgupta 2011; Pooley 2021; Pooley and Read 2021; Teitel 2021a) have responded that claims about the representational capacities of models are irrelevant to the issue of underdetermination, which concerns possible worlds themselves. In this paper I distinguish two versions of this objection: (1) that (...) a theory’s formalism does not (fully) determine the space of physical possibilities, and (2) that the relevant notion of possibility is not physical possibility. I offer a refutation of each. (shrink)

Agriculture is defined normatively and, as such, is an area of research and practice where values are an inextricable constituent of research, where facts and values elide, and normative constraints generate new ethical categories. While discussions of normativity are part and parcel within agricultural ethics and play a prominent role in ethical discussions, I suggest that other areas of agricultural philosophy such as agricultural metaphysics or ontologies present valuable case studies for philosophical discussion. A series of case studies focusing on (...) how products are classified, graded, and measured illustrate conceptions of existence, causal relationships, and practice-oriented notions of category-making distinctive of agricultural practice. The first of these case studies shines a light on the process of knowledge integration in agriculture. I show how innovative integration, a process discussed within socially sustainable egg production, is an ineliminably normative process. The second case study, and the main focus of the chapter, concerns the normative role of agricultural standards. I discuss how standards and classes in use within egg production systems and the development and measuring techniques make AA eggs and transformed a highly toxic oilseed rape (used as a machine lubricant) into the non-toxic food-grade agricultural commodity, canola. I contend agricultural products like eggs, peanut butter, and canola oil are constituted by prescribed standards (like AA eggs and double-zero canola) that define not only the product, but also the activities related to its production and the practices that producers perform. Because standards and standardization define the categories of not only agricultural products but also agricultural practices, I suggest standards and standardization are best understood as “ontologizing activities.”. (shrink)

The ontology of race is often seen as answering two central questions. First, do races exist? Second, if races do exist, then what are they? Consequently, determining the best methods for answering these questions falls within the metaontology of race. Within the ontology of race, it is common to select a privileged representation of race in order to draw ontological lessons. While ontological lessons are direct answers to the ontological questions raised above, privileged representations are the basis for inferring those (...) lessons. Using the Office of Management and Budget’s racial classification as an illustration, we argue that certain social-scientific methods are better than mainstream methods at ruling out just-so stories about race, and therefore outperform more mainstream philosophical methods in determining which representations of race should be privileged. In defending this position, we also argue that the widespread philosophical practice of sharply distinguishing social-scientific from ordinary-language conceptions of race is unmotivated. (shrink)

Precise measurements of well-being would be of profound societal importance. Yet, the sceptical worry that we cannot use social science instruments and tests to measure well-being is widely discussed by philosophers and scientists. A recent and interesting philosophical argument has pointed to the psychometric procedures of construct validation to address this sceptical worry. The argument has proposed that these procedures could warrant confidence in our ability to measure well-being. The present paper evaluates whether this type of argument succeeds. The answer (...) is that it depends on which methodological background assumptions are motivating the sceptical worry to begin with. We show this by doing two things. First, we clarify (a) the different types of well-being theories involved in the science of well-being, and (b) the general methodological dimensions of well-being theorising. Second, we apply these distinctions and argue that construct validation is an unsuccessful response to measurement scepticism if this scepticism is motivated by a form of methodological non-naturalism. In the light of this, the overall point of the paper is that philosophers and scientists, when discussing measurement of well-being, should explicate their deeper methodological commitments. We further suggest that making such explicit commitments might present philosophers with a dilemma. (shrink)

Measurement practices are central to most sciences. In the human sciences, however, it remains controversial whether the measurement of human attributes—depression, happiness, intelligence, etc.—has been successful. Are, say, widely used depression questionnaires valid measuring instruments? Can we trust self-reported happiness scales to deliver quantitative measurements as it is sometimes claimed? These and related questions are till today hotly disputed. There are two main frameworks under which human measurements are studied and criticized. One is the so-called construct validity framework. Here, criticisms (...) to human measurements are typically of the form “this instrument is not valid: it does not actually measure the attribute we set out to measure”. The second framework is the standard typology of measurement scales (nominal, ordinal, interval, and ratio). Human measurements are commonly challenged for being merely ordinal—not quantitative: interval or ratio—despite the fact that many researchers use measurement results as if they were quantitative. The first part of the dissertation studies how adequate these frameworks are for evaluating measuring instruments and the inferences they afford. Regarding the concept of validity, it is commonly understood unconditionally, that is, without restricting validity judgments about measuring instruments to context-specific situations. Instruments are said to be (in)valid simpliciter. In Chapter 2, I argue against this conception of validity and in favor of a contextual one. Regarding the second main framework, the standard typology of scales is typically linked to a set of prescriptions regarding (un)justified measurement inferences. I call this classification-cum-prescriptions the “received view” on measurement scales. In chapters 3 and 4, I question the idea that the received view is an impeccable guide for clarifying the kinds of inferences we are licensed to make from measurement results in human science contexts. I motivate general doubts about the adequacy of the received view in Chapter 3, and I articulate these doubts in detail for the specific case of average group comparisons in Chapter 4. The upshot of this first part of the dissertation is a deeper awareness of the complexity surrounding which inferences can legitimately be made from measuring instruments. The first part of the dissertation is largely framed under the assumption that some human attributes are indeed quantitative, even if they are not currently being measured quantitatively. The second part addresses two important issues raised by that assumption. Chapter 5 tackles the so-called “quantity objection”: that human science attributes are themselves not quantitative, thus they cannot be quantitatively measured. This objection has been deployed to argue against optimistic positions regarding human quantification. I argue that the quantity objection is not successful in this sense—it begs the question to these optimistic human scientists that, just like their colleagues in the physical sciences have done, postulate theoretical quantitative attributes as working hypotheses. But what does treating human attributes quantitatively as working hypotheses amount to? And what are, or can be, “amounts” of depression, happiness, etc.? Chapter 6 argues that there is not one but various approaches for quantitatively conceiving of human attributes, each with its own success conditions. This chapter offers a conceptual framework for making progress on debates about controversial human measurements. (shrink)

Philosophers and metrologists have refuted the view that measurement’s epistemic privilege in scientific practice is explained by its theory-neutrality. Rather, they now explicitly appeal to the role that theories play in measurement. I formulate a challenge for this view: scientists sometimes ascribe epistemic privilege to measurements even if they lack a shared theory about their target quantity, which I illustrate through a case study from early geodesy. Drawing on that case, I argue that the epistemic privilege of measurement precedes shared (...) background theory and is better explained by its pre-theoretic function in enabling a distinctive kind of inquiry. (shrink)

As a result of being measured, individuals sometimes alter their behavior and attitudes to such extent that subsequent measurement results are affected. This ‘reactivity’ to measurement problematizes prediction and explanation, but some reactivity is nevertheless legitimate. Using the example of the measurement of race in the US Census, this article demonstrates that some forms of reactivity do not affect the accuracy of research. The article argues that legitimacy of reactivity depends on the metaphysical status of the phenomenon being measured. It (...) is argued that reactivity’s legitimacy is affected by the arbitrariness of a measure and the voluntariness of measurement results. (shrink)

Philosophy &Public Affairs, Volume 52, Issue 1, Page 5-41, Winter 2024.

Experiences of racial discrimination can seem to be caused by one’s race, a combination of social identities, or non-social features. In other words, racial discrimination can be intersectional or attributionally ambiguous. This poses challenges for current understandings and measurement tools of racial discrimination in public health research, such as the explanation of racial health disparities. Different kinds of discriminatory experiences plausibly produce different psychological effects that mediate their negative health impacts. Thus, multiple characterizations and measurements of racial discrimination are needed. (...) As a result, I argue that racial discrimination should be a polysemous concept (with multiple meanings). (shrink)

Current methods of operationalizing concepts of misinformation in machine learning are often problematic given idiosyncrasies in their success conditions compared to other models employed in the natural and social sciences. The intrinsic value-ladenness of misinformation and the dynamic relationship between citizens' and social scientists' concepts of misinformation jointly suggest that both the construct legitimacy and the construct validity of these models needs to be assessed via more democratic criteria than has previously been recognized.

This paper examines the role existence plays in measurement validity. I argue that existing popular theories of measurement and of validity follow a correspondence framework, which starts by assuming that an entity exists in the real world with certain properties that allow it to be measurable. Drawing on literature from the sociology of measurement, I show that the correspondence framework faces several theoretical and practical challenges. I suggested the validity-first framework of measurement, which starts with a practice-based validation process as (...) the basis for a measurement theory, and only posits objective existence when it is scientifically useful to do so. (shrink)

In the 1780s Kant’s critique of rational cosmology clearly identified the limits of theoretical cosmology in agreement with the doctrine of transcendental idealism of space and time. However, what seems to be less explored, and remains still a desideratum for the literature, is a thorough investigation of the implications of transcendental philosophy for Kant’s view of cosmology in the 1790s. This contribution fills this gap by investigating Kant’s view of teleology and measurement in the Critique of Judgment, exploring their implications (...) for Kant’s late view of cosmology. Considering the historical and scientific context in which Kant developed his reflections motivates my proposal to read Kant’s late view of the universe in terms of “functional cosmology.” -/- . (shrink)

Our understanding of implicit bias and how to measure it has yet to be settled. Various debates between cognitive scientists are unresolved. Moreover, the public’s understanding of implicit bias tests continues to lag behind cognitive scientists’. These discrepancies pose potential problems. After all, a great deal of implicit bias research has been publicly funded. Further, implicit bias tests continue to feature in discourse about public- and private-sector policies surrounding discrimination, inequality, and even the purpose of science. We aim to do (...) our part by reconstructing some of the recent arguments in ordinary language and then revealing some of the operative norms or values that are often hidden beneath the surface of these arguments. This may help the public learn more about the science of implicit bias. It may also help both laypeople and scientists reflect on the values, interests, and stakeholders involved in establishing, justifying, and communicating scientific research. (shrink)

Policies that require male-female sex comparisons in all areas of biomedical research conflict with the goal of improving health outcomes through context-sensitive individualization of medical care. Sex, like race, requires a rigorous, contextual approach in precision medicine. A “sex contextualist” approach to gender-inclusive medicine better aligns with this aim.

It is an open question whether well-being ought to primarily be understood as a temporal concept or whether it only makes sense to talk about a person’s well-being over their whole lifetime. In this article, I argue that how this principled philosophical disagreement is settled does not have substantive practical implications for well-being science and well-being policy. Trying to measure lifetime well-being directly is extremely challenging as well as unhelpful for guiding well-being public policy, while temporal well-being is both an (...) adequate indirect measure of lifetime well-being, and an adequate focus for the purposes of improving well-being through public policy. Consequently, even if what we ought to care about is lifetime well-being, we should use temporal measures of well-being and focus on temporal well-being policies. (shrink)

Review: J. E. Wolff. The metaphysics of quantity. New York: Oxford University Press, 2020. 240 pp, $72.00 HB.

Craniology – the practice of inferring intelligence differences from the measurement of human skulls – survived the dismissal of phrenology and remained a widely popular research program until the end of the nineteenth century. From the 1970s, historians and sociologists of science extensively focused on the explicit and implicit socio-cultural biases invalidating the evidence and claims that craniology produced. Building on this literature, I reassess the history of craniological practice from a different but complementary perspective that relies on recent developments (...) in the epistemology of measurement. More precisely, I identify two aspects of the measurement culture of nineteenth-century craniologists that are crucial to understand the lack of validity of craniological inference: their neglect of the problem of coordination for their presupposed quantification of intelligence and their narrow view of calibration. Based on my analysis, I claim that these methodological shortcomings amplified the impact of the socio-cultural biases of craniologists, which had a pervasive role in their evidential use of measurement. Finally, my argument shows how the epistemology of measurement perspective can offer useful tools in debates concerning the use of biological evidence to foster social discourse and for analyzing the relationship between theory, evidence, and measurement. (shrink)

While the common procedure of statistical significance testing and its accompanying concept of p-values have long been surrounded by controversy, renewed concern has been triggered by the replication crisis in science. Many blame statistical significance tests themselves, and some regard them as sufficiently damaging to scientific practice as to warrant being abandoned. We take a contrary position, arguing that the central criticisms arise from misunderstanding and misusing the statistical tools, and that in fact the purported remedies themselves risk damaging science. (...) We argue that banning the use of p-value thresholds in interpreting data does not diminish but rather exacerbates data-dredging and biasing selection effects. If an account cannot specify outcomes that will not be allowed to count as evidence for a claim—if all thresholds are abandoned—then there is no test of that claim. The contributions of this paper are: To explain the rival statistical philosophies underlying the ongoing controversy; To elucidate and reinterpret statistical significance tests, and explain how this reinterpretation ameliorates common misuses and misinterpretations; To argue why recent recommendations to replace, abandon, or retire statistical significance undermine a central function of statistics in science: to test whether observed patterns in the data are genuine or due to background variability. (shrink)

Kant’s denial that psychology is a properly so-called natural science, owing to the lack of application of mathematics to inner sense, has garnered a great deal of attention from scholars. Although the interpretations of this claim are diverse, commentators by and large fail to ground their views on an account of Kant’s conception of applied mathematics. In this article, I develop such an account, according to which the application of mathematics to a natural science requires both a mathematical representation and (...) a metaphysical validation for the positive use of this representation to achieve a priori knowledge about nature. The second condition—that of metaphysical validation—has been overlooked in the literature. I show that psychology’s falling short of natural scientific propriety consists not in our lacking sufficient mathematical tools for the representation of inner states, according to Kant. After all, we can represent the mere temporality of inner states with the line and their intensities with numbers. Rather, the problem is that metaphysics does not validate the further use of such mathematical entities for the achievement of a priori knowledge about inner phenomena. (shrink)

This article examines the historical construction of depression over about a hundred years, employing the social life of methods as an explanatory framework. Specifically, it considers how emerging methodologies in the measurement of psychological constructs contributed to changes in epistemological approaches to mental illness and created the conditions of possibility for major shifts in the construction of depression. While depression was once seen as a feature of psychotic personality, measurement technologies made it possible for it to be reconstructed as changeable (...) and treatable. Different types of scaling techniques (Likert versus dichotomous scales) enabled the separation of depressive personality from reactive depression, paving the way for measuring the severity and intensity of emotions. Techniques to test sensitivity to change provided a means of demonstrating the efficacy of new psychoactive drug treatments. Later, more advanced techniques of precision scaling enabled the management of a new measurement problem, clinician unreliability, associated with the growing number of professionals involved in mental health care. Through statistical management of unreliability, the construct of depression has dramatically reduced over this period from hundreds of questionnaire items to potentially just two. Exploring the history of depression through this lens produces an alternative narrative to those that have emerged as a result of medicalisation and the actions of individuals and pressure groups. (shrink)

Derived measurements involve problems of coordination. Conducting them often requires detailed theoretical assumptions about their target, while such assumptions can lack sources of evidence that are independent from these very measurements. In this paper, I defend two claims about problems of coordination. I motivate both by a novel case study on a central measurement problem in the history of physical geodesy: the determination of the earth's ellipticity. First, I argue that the severity of problems of coordination varies according to scientists' (...) predictive and experimental control over perturbations of the measurement process. Second, I identify a methodology by which scientists can solve hard problems of coordination and gradually increase their predictive control over perturbations. I dub this methodology ‘operational pluralism’ since it is driven by the introduction of alternative measurement operations that involve different physical indicators. (shrink)

This paper critically explores Timothy Williamson’s view of evidence, and it does so in light of the problem of epistemic luck. Williamson’s view of evidence is, of course, a crucially important aspect of his novel and influential “knowledge-first” epistemological project. Notoriously, one crucial thesis of this project is that one’s evidence is equivalent to what one knows. This has come to be known as the E = K thesis. This paper specifically addresses Williamson’s knowledge-first epistemology and the E = K (...) thesis in the context of anti-luck epistemology and the idea that knowledge is factive. Williamson’s views on these matters are worth investigating in some detail because he subscribes to a well-worked out anti-luck view of knowledge that incorporates what is perhaps the most common anti-luck condition. But this paper is also of more general importance because the critique of Williamson’s views on these matters reveals some important things about the nature of evidence and evidence is one of the most fundamental concepts in epistemology. (shrink)

Cosmologists take the $\Lambda$CDM model to be a permanent contribution to our knowledge of the universe, based on the success of precision cosmology. Consistent, independent determinations of the parameters in this model encourage physicists to take it seriously. This stance incurs an obligation to resolve any discrepancies by reanalyzing measurements or adding further complexity. Recent observations in cosmology indicate a tension between “local” and “global” determinations of the Hubble constant. Here I argue that this tension illustrates one of the benefits (...) of taking the model seriously and consider the challenges to making a case for the permanence of $\Lambda$CDM. (shrink)

One important strategy for dealing with error in our methods is triangulation, or the use multiple methods to investigate the same object. Current accounts of triangulation assume that its primary function is to provide a confirmatory boost to hypotheses beyond what confirmation of each method alone could produce. Yet, researchers often use multiple methods to examine new constructs about which they are uncertain. For example, social psychologists use multiple indirect measures to provide convergent evidence about implicit attitudes, but how to (...) characterize implicit attitudes is an open question. To make sense of triangulation under uncertainty about constructs, I suggest two changes: first, triangulation can serve multiple epistemic functions, including some that are non-confirmatory, and second, researchers should assess the epistemic risk in claims about evidence and the acceptance/rejection of hypotheses. (shrink)

What does it mean to have “strong beliefs”? My thesis is that it can mean two very different things. That is, there are two distinct psychological features to which “strong belief” can refer, and these often come apart. I call the first feature epistemic confidence and the second identity centrality. They are conceptually distinct and, if we take ethnographies of religion seriously, distinct in fact as well. If that’s true, it’s methodologically important for the psychological sciences to have measures that (...) tease them apart. In this paper, I critique some measures that are currently in use and propose some strategies for developing measurement tools that track the distinction in question. (shrink)