Measurement in Science

By late 20th century, the rationality wars had launched debates about the nature and norms of intuitive and reflective thinking. Those debates drew from mid-20th century ideas such as bounded rationality, which challenged more idealized notions of rationality observed since the 19th century. Now that 21st century cognitive scientists are applying the resulting dual process theories to artificial intelligence, it is time to dust off some lessons from this history. So this paper synthesizes old ideas with recent results from experiments (...) on humans and machines. The result is Strategic Reflectivism, which takes the position that one key to intelligent systems (human or artificial) is pragmatic switching between intuitive and reflective inference to optimally fulfill competing goals. Strategic Reflectivism builds on American Pragmatism, transcends superficial indicators of reflective thinking such as model size or chains of thought, and becomes increasingly actionable as we learn more about the value of intuition and reflection. (shrink)

I will look at Bohr's contentious doctrine of classical concepts - the claim that measurement requires classical concepts to be understood - and argue that measurement theory supports a similar conclusion. I will argue that representing a property in terms of a metric scale, which marks a shift from the empirical process of measurement to the informational output, introduces the inherently classical assumption of definite states and precise values, thus fulfilling Bohr's doctrine. I examine how realism about metric scales implies (...) that Bohr's doctrine is ontological, while more moderate coherentist or model-based approaches to realism render it epistemological. Regardless of one's stance towards measurement realism, however, measurement cannot be entirely quantum and quantum mechanics can model only the empirical side of measurement, not its informational output. Finally, I discuss how this might influence our understanding of the measurement problem. (shrink)

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)

Scientific data without uncertainty estimates are increasingly seen as incomplete. Recent discussions in the philosophy of data, however, have given little attention to the nature of uncertainty estimation. We begin to redress this gap by, first, discussing the concepts and practices of uncertainty estimation in metrology and showing how they can be adapted for scientific data more broadly; and second, advancing five philosophical theses about uncertainty estimates for data: they are substantive epistemic products; they are fallible; they can be iteratively (...) improved; they should be judged in terms of their adequacy-for-purpose; and these estimates, in turn, are essential for judging data adequacy. We illustrate these five theses using the example of the GISTEMP global temperature dataset. Our discussion introduces a novel adequacy-for-purpose view of uncertainty estimation, addresses a weakness in a recent philosophical account of data, and provides a new perspective on the “safety” versus “precision” debate in metrology. (shrink)

A large number of diversity measures have been proposed in the literature, almost all of which are designed for sets with elements that differ in multiple aspects. However, these types of measures are not appropriate for sets with elements that differ in a single aspect only, such as duration, value or probability. In this essay I present a new measure of diversity, designed specifically for single aspect diversity. The measure captures the intuitive idea that single aspect diversity is affected by (...) the maximal dissimilarity between the elements, the number of different elements, and the even spacing of the elements’ aspect values, when represented as points in one dimension. I show that the measure satisfies six plausible conditions for a single aspect diversity measure, which concern scale independence, minimal diversity, maximal dissimilarity, restricted function growth, strict monotonicity, and even spacing. The measure is also characterised. (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)

Despite the recent “epistemic turn” in the philosophy of measurement, philosophers have ignored a nearly 80 year controversy about the relationship between statistical inference and measurement theory. Some scholars maintain that measurement theory places no constraints on statistics, whereas others argue that the measurement scale (e.g., ordinal or interval) of one’s data determines which statistical methods are “permissible.” I defend an intermediate position: even if existing measurement theory were irrelevant to statistical inference, it would be critical for scientific inference, which (...) requires connecting statistical hypotheses to broader research hypotheses. (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)

Neuralink could distribute artificial superintelligence to humans, thus allowing the homosapiens to synchronize the hemispheres of their brains, thereby transcending space-time, and potentially time traveling. While backwards time travel cannot change the past, due to paradoxes, the time traveler would probably share a soul with the alternate timeline self, thus providing closure for regrets, errors, injustice, etc. Plus, if one time travels with AI superintelligence, the time traveler may mend errors with greater ease. -/- Although other potential time travel methods (...) are displayed in the reference section, only the Gateway Process will be observed in this essay. The Gateway Process may allow for backwards time travel, under the rules that time travel cannot change the past, yet by attempting to change the past, new dimensions will be created, thus growing the universe. To determine if the Gateway Process allows for backwards time travel, researchers can use computer brain interface to examine the inside of a subject’s brain and mind. Plus, researchers can also check if the universe has grown after the subject has attempted to alter a past event, theoretically only creating another dimension. Soon technology may detect the exact expansion of the universe. Perhaps scientists can use space tunnels to investigate the possible creation of new dimensions from the Gateway Process backwards time traveling, attempting to alter past events. EXPERIMENT STEPS: 1)Automate the Gateway Process with Neuralink to ease suspected backwards time travel. 2)Connect the subject’s brain and mind to computer brain interface, or more specifically, magnetic resonance imaging, so the suspected time travel is recorded. 3)Build a space tunnel device to determine if the subject is creating new alternate dimensions with the suspected backwards time travel. 4)Stop, review and try again. Space tunnels may further corroborate if more dimensions have been created with the Gateway Process. Since hemisphere synchronization transcends the time-space dimension, effective enough Neuralink devices could allow someone to synchronize brain hemispheres and time travel to the past. Neuralink technology may both allow a deeper meditative state, thus backwards time travel, and computer monitoring of the backwards time travel and alternate dimension creation /universe expansion. At least presumably through scientific studies, each individual has alternate selves throughout alternate timelines thus, each individual(all alternate selves) become one in the afterlife. So backwards time traveling to correct a mistake, injustice, or error, thus creating alternate timelines, out of the past, would not change the original timeline but, would add a deeper satisfaction for the time traveler by sharing a soul with the alternative timeline self. While correcting the error, injustice, or mistake, the time traveler and alternative timeline self may share an individual consciousness. More concretely, quantum entanglement may illustrate how an individual’s selves, across different alternate timelines, share a deeper fundamental self, like a soul. I hereby invite experts in AI, quantum mechanics, and neuroscience to collaborate in adding technical rigor to this preprint. (shrink)

There is a growing consensus among philosophers that quantifying value-laden concepts can be epistemically successful and politically legitimate if all value-laden choices in the process of quantification are aligned with stakeholder values. I argue that proponents of this view have failed to argue for its basic premise: successful quantification is sufficiently unconstrained so that it can be achieved along multiple stakeholder-specific pathways. I then challenge this premise by considering a rare example of successful value-laden quantification in seismology. Seismologists quantified earthquake (...) size precisely by excluding stakeholder values from measure design and testing. (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)

In this critical response to John Doris's book "Character Trouble: Undisciplined Essays on Moral Agency and Personality," I analyze his updated take on character skepticism—the view that character traits have surprisingly limited influence on behavior across diverse situations—from a philosophy of science perspective. While I find his updated view compelling, I challenge his reliance on Cohen's conventional effect size benchmarks, arguing that qualitative labels for effect sizes obscure rather than clarify the practical significance of results. I propose that Doris's strongest (...) argument lies in what I call the "disproportion thesis"—the view that personality variables exert less influence, and situational variables more influence, on behavior than our intuitive expectations would predict, creating a disconcerting gap. However, I argue that this thesis requires a more explicit quantification of those prior expectations. I conclude that character skepticism would benefit from formulations of its insights in a way that directly addresses character theorists' empirical commitments, avoiding vague benchmarks and contextualizing effects. (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)

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)

Philosophers provide excellent resources for developing a science of virtues, and an interdisciplinary collaboration between philosophers and psychologists seems ideal. This suggestion is not new, but there has been little guidance for psychologists about how philosophical work can be useful in developing a science of virtue. This article provides some guidance by dividing the contributions of philosophers into three categories. First, many philosophers provide theories of virtue’s nature or value, but these are generally not useful for psychological scientists and can (...) be safely ignored. Second, awareness of the range of philosophic positions can enable scientists to recognize contentious theoretical assumptions that they are making. Psychologists need not try to resolve these debates; they can choose to only identify which position(s) they are taking. Third, awareness of the range of philosophic positions and the competing conceptual analyses of various virtue concepts and traits can help psychologists to identify and test new empirical hypotheses. (shrink)

In this paper, we will focus on a specific way in which non-epistemic values can influence scientific inquiry, i.e., how they affect the way in which members of a scientific community apply epistemic values. We will first introduce the concept of epistemic niche construction in science, that is, the idea that the epistemic commitments underlying the practice of a scientific community result from a feedback-loop process between the scientific practice itself and the related disciplinary matrix. We will then describe how (...) non-epistemic values can affect the different steps of this feedback-loop process. We will substantiate our argumentation through a historical case study: the rise and fall of nineteenth-century craniology. (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)

David Kinnebrook is remembered as the assistant to the Astronomer Royal dismissed in 1796 for marking stellar transits too slowly. Kinnebrook’s firing is commonly listed as the origin point for the personal equation and empirical psychology. Historians have viewed Kinnebrook as a slightly misused, although mute, party in the affair, drawing their accounts from Nevil Maskelyne’s published account of the dismissal. Kinnebrook’s letters, which resurfaced in 1985, detail a monthslong dispute with Maskelyne concerning observational disagreements. The letters provide an account (...) of observational practice and individual differences in marking transits; they also detail Maskelyne’s failure to recognize an epistemic problem. Kinnebrook’s letters show that the problem of individual differences was known to Maskelyne as well as several of his contemporaries. Evidence from the letters shows that Maskelyne passed off six weeks of observations collected by his disgraced assistant as his own. The letters also state that Maskelyne had substantial personal observational differences with previous assistants. While Bessel later conjectured that Kinnebrook was under pressure to speed up his observations, Kinnebrook’s letters confirm that conjecture and reveal that Kinnebrook had a deeper comprehension of the epistemological problems of observation than has been recognized. Kinnebrook’s recognition of personal differences in marking stellar transits is a significant moment in the prehistory of the personal equation. (shrink)

Narratives, or constructing storylines, serve important cognitive functions in life and historical studies. A growing interest lies in their roles in generating and structuring frontier scientific knowledge. Philosophers of science characterize narratives as a “technology of sense-making,” as they connect diverse scientific elements from different sources to create a coherent understanding. Distinctive features of narratives lead to both appreciation and criticism. Because narratives can be loose in organization and connect gappy materials, they empower the study of complex phenomena. However, they (...) are also criticized for generating “just-so” stories, which, without being verified with other established scientific methods, are not useful to science. -/- I defend the central role of narratives in science, focusing on cases in astronomy. Astronomy has achieved remarkable progress in the last century despite theoretical and empirical challenges. Philosophy of science needs to explain how knowledge about the universe’s unobservable past can be reliably obtained. I argue that narrative construction is a key solution. Specifically, I argue that unverified narratives can still provide a special kind of knowledge for science, the knowledge about how to use certain scientific tools. -/- I demonstrate this by showing how constructing coherent narratives makes astronomers develop three key tools for productive research. First, narratives enable the establishment of time measurement methods in the universe. Second, in astronomers’ first account of the exoplanet Hot Jupiter, constructing a narrative for its orbital migration suggested the novel use of existing models and produced a toolkit for studying similar phenomena. Third, when astronomers integrate a data-driven method, machine learning, into research, narratives mitigate its uncertainties and adapt it for solving problems about the Galaxy’s past. -/- To conclude, my dissertation demonstrates narratives’ power as a meta-method for science. This also helps to understand important discoveries in 20th-21st-century astronomy and provides lessons for its continuing success. (shrink)

Governments and social scientists are increasingly developing machine learning methods to automate the process of identifying terrorists in real time and predict future attacks. However, current operationalizations of “terrorist”’ in artificial intelligence are difficult to justify given three issues that remain neglected: insufficient construct legitimacy, insufficient criterion validity, and insufficient construct validity. I conclude that machine learning methods should be at most used for the identification of singular individuals deemed terrorists and not for identifying possible terrorists from some more general (...) class, nor to predict terrorist attacks more broadly, given intolerably high risks that result from such approaches. (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)

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)

"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)

‘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)

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)

This thesis tells the story of a surprisingly difficult problem in gravitational physics: deriving and measuring the shape of our planet. Chapter 1 reconstructs the emergence of gravitational theories of planetary equilibrium figures and quantitative measurements of the Earth’s shape and surface gravity (c. 1660-1730). I show that early geodesists made substantial empirical progress despite deep theoretical disagreements about the nature of gravitation. Chapter 2 reconstructs how geodesy came to offer a decisive test of the interactive nature and compositionality of (...) gravitation (c. 1740-1825). I retell how Pierre-Simon Laplace established that the Earth’s external attraction is the resultant force of the mutual attractions between its constituent particles; a momentous but overlooked achievement in the history of gravitational physics. Chapter 3 traces the numerical conflicts in the measurement of the central quantity characterising Earth’s figure: its ellipticity. These conflicts persisted throughout the nineteenth century and complicated the coordination between geodetic models and measurements. Chapter 4 reconstructs how geodesists finally achieved convergent measurements of Earth’s ellipticity between 1880 and 1924. Jointly, the four chapters illustrate key steps in obtaining strong evidence for quantitative claims about a complex and partially inaccessible system: using measurements to initiate theoretical inquiry (chapter 1), using measurements to conduct severe tests of theoretical laws (chapter 2), using discordant measurements to study second-order phenomena (chapter 3), and using multiple alternative measures to identify the sources of persistent errors (chapter 4). (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)

To study consciousness, scientists need to determine when participants are conscious and when they are not. They do so with consciousness detection procedures. A recurring skeptical argument against those procedures is that they cannot be calibrated: there is no way to make sure that detection outcomes are accurate. In this article, I address two main skeptical arguments purporting to show that consciousness scientists cannot calibrate detection procedures. I conclude that there is nothing wrong with calibration in consciousness science.

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)