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)

Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriately termed “model-based,” and I examine the use of statistics in climate fingerprinting to show (...) how the difficulties that climate scientists encounter in applying statistics to ensemble-generated data are the practical difficulties of normal statistical practice. The upshot is that whether the application of statistics to ensemble-generated data yields trustworthy results should be expected to vary from case to case. (shrink)

As far as disputes in the philosophy of pure mathematics goes, these are usually between classical mathematics, intuitionist mathematics, paraconsistent mathematics, and so on. My own view is that of a mathematical pluralist: all these different kinds of mathematics are equally legitimate. Applied mathematics is a different matter. In this, a piece of pure mathematics is applied in an empirical area, such as physics, biology, or economics. There can then certainly be a disputes about what the correct pure mathematics to (...) apply is. Such disputes may be settled by the standard criteria of scientific theory selection (adequacy of empirical predications, simplicity, etc.) But what, exactly is it to apply a piece of pure mathematics? How is mathematics applied? By and large, philosophers of mathematics have cared more about pure mathematics than applied mathematics, and not a lot of thought has gone into this question. In this paper I will address the issue and some of its implications. (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)

This article examines how geologists, botanists, and ecologists used pollen as a proxy for past climates in the first half of the twentieth century. It focuses on a particular challenge of measuring climate with pollen: pollen’s mobility. As scientists came to learn, pollen from some vegetation is more mobile than others. Pollen’s differential mobility challenged regional climatic conclusions because of the potential mixing of pollen from various locations. To minimize the effects of this problem, pollen analysts sought to decrease the (...) noise produced by highly local or foreign pollen. Yet, many ground-truthing and calibration methods were not available to pollen analysts because of the temporal separation between the observer and the object of interest. Instead, pollen analysts had to make spatial meaning out of fossil pollen using empirical studies of modern pollen, inferences from macrofossils and successional history, and applying statistical theories to fossil pollen data. Many of these corrections factors relied on pollen analysts’ knowledge of place, including elements like the location’s topography, prevailing winds, and plant cover. These elements were a natural part of vegetation-pollen-climate interactions. Scientists needed to account for them to turn pollen into a proxy for climate. Pollen’s movement was equally natural, but scientists decided to eliminate some pollen to augment the regional climate signal. These selective eliminations of place suggest that not all elements of place are equally important. Scientists had to omit some elements of place to make sense of the complexities of the natural world. (shrink)

While anti-exceptionalism about logic is now a popular topic within the philosophy of logic, there’s still a lack of clarity over what the proposal amounts to. currently, it is most common to conceive of AEL as the proposal that logic is continuous with the sciences. Yet, as we show here, this conception of AEL is unhelpful due to both its lack of precision, and its distortion of the current debates. Rather, AEL is better understood as the rejection of certain traditional (...) properties of logic. The picture that results is not of one singular position, but rather a cluster of often connected positions with distinct motivations, understood in terms of their rejection of clusters of the various traditional properties. In order to show the fruitfulness of this new conception of AEL, we distinguish between two prominent versions of the position, metaphysical and epistemological AEL, and show how the two positions need not stand or fall together. (shrink)

I argue that the appropriateness of an assertion is sensitive to context—or, really, the “common ground”—in a way that hasn’t previously been emphasized by philosophers. This kind of context-sensitivity explains why some scientific conclusions seem to be appropriately asserted even though they are not known, believed, or justified on the available evidence. I then consider other recent attempts to account for this phenomenon and argue that if they are to be successful, they need to recognize the kind of context-sensitivity that (...) I argue for. (shrink)

Thick concepts, namely those concepts that describe and evaluate simultaneously, present a challenge to science. Since science does not have a monopoly on value judgments, what is responsible research involving such concepts? Using measurement of wellbeing as an example, we first present the options open to researchers wishing to study phenomena denoted by such concepts. We argue that while it is possible to treat these concepts as technical terms, or to make the relevant value judgment in-house, the responsible thing to (...) do, especially in the context of public policy, is to make this value judgment through a legitimate political process that includes all the stakeholders of this research. We then develop a participatory model of measurement based on the ideal of co-production. To show that this model is feasible and realistic, we illustrate it with a case study of co-production of a concept of thriving conducted by the authors in collaboration with a UK anti-poverty charity Turn2us. (shrink)

The article advances a new way of thinking about classifications in general and the classification of mental disorders in particular. By applying insights from measurement practice to the context of classification, I defend a notion of epistemic accuracy that allows one to evaluate and improve classifications by comparing different classifying methods to each other. Progress in classification arises from the mutual development of classification systems and classifying methods. Based on this notion of accuracy, the article illustrates with an example how (...) psychiatric classifications can be improved via circumscribed comparisons of different perspectives on mental disorders, without relying on complete models of their complex aetiology. When applying this strategy, the traditional opposition between symptom-based and causal approaches is of little consequence for making progress in the epistemic accuracy of psychiatric classification. (shrink)

There is a received view on measurement scales. It includes both a classification of scales and a set of prescriptions regarding measurement inferences. This article casts doubt on the adequacy of this received view. To do this, I propose an epistemic characterization of the ordinal/interval distinction, that is, one in terms of researchers’ beliefs. This novel characterization reveals the ordinal/interval distinction as too coarse grained and thus the received view as too restrictive of a framework for measurement research.

(This is for the Cambridge Handbook of Analytic Philosophy, edited by Marcus Rossberg) In this handbook entry, I survey the different ways in which formal mathematical methods have been applied to philosophical questions throughout the history of analytic philosophy. I consider: formalization in symbolic logic, with examples such as Aquinas’ third way and Anselm’s ontological argument; Bayesian confirmation theory, with examples such as the fine-tuning argument for God and the paradox of the ravens; foundations of mathematics, with examples such as (...) Hilbert’s programme and Gödel’s incompleteness theorems; social choice theory, with examples such as Condorcet’s paradox and Arrow’s theorem; ‘how possibly’ results, with examples such as Condorcet’s jury theorem and recent work on intersectionality theory; and the application of advanced mathematics in philosophy, with examples such as accuracy-first epistemology. (shrink)

What is a valid measuring instrument? Recent philosophy has attended to logic of justification of measures, such as construct validation, but not to the question of what it means for an instrument to be a valid measure of a construct. A prominent approach grounds validity in the existence of a causal link between the attribute and its detectable manifestations. Some of its proponents claim that, therefore, validity does not depend on pragmatics and research context. In this paper, I cast doubt (...) on the possibility of a context-independent causal account of validity (what I call unconditional validity). I assess several versions, arguing that all of them fail to judge the validity of measuring instruments correctly. Because different research purposes require different properties from measuring instruments, no account of validity succeeds without referring to the specific research purpose that creates the need for measurement in the first place. (shrink)

This paper looks at the question of what it means for a psychological test to have construct validity. I approach this topic by way of an analysis of recent debates about the measurement of implicit social cognition. After showing that there is little theoretical agreement about implicit social cognition, and that the predictive validity of implicit tests appears to be low, I turn to a debate about their construct validity. I show that there are two questions at stake: First, what (...) level of detail and precision does a construct have to possess such that a test can in principle be valid relative to it? And second, what kind of evidence needs to be in place such that a test can be regarded as validated relative to a given construct? I argue that construct validity is not an all-or-nothing affair. It can come in degrees, because both our constructs and our knowledge of the explanatory relation between constructs and data can vary in accuracy and level of detail, and a test can fail to measure all of the features associated with a construct. I conclude by arguing in favor of greater philosophical attention to processes of construct development. (shrink)

Peer review is often taken to be the main form of quality control on academic research. Usually journals carry this out. However, parts of maths and physics appear to have a parallel, crowd-sourced model of peer review, where papers are posted on the arXiv to be publicly discussed. In this paper we argue that crowd-sourced peer review is likely to do better than journal-solicited peer review at sorting papers by quality. Our argument rests on two key claims. First, crowd-sourced peer (...) review will lead on average to more reviewers per paper than journal-solicited peer review. Second, due to the wisdom of the crowds, more reviewers will tend to make better judgments than fewer. We make the second claim precise by looking at the Condorcet Jury Theorem as well as two related jury theorems developed specifically to apply to peer review. (shrink)

Peer reviewers at many funding agencies and scientific journals are asked to score submissions both on individual criteria and overall. The overall scores should be some kind of aggregate of the criteria scores. Carole Lee identifies this as a potential locus for bias to enter the peer review process, which she calls commensuration bias. Here I view the aggregation of scores through the lens of social choice theory. I argue that, when reviewing grant proposals, it is in many cases impossible (...) to avoid commensuration bias. (shrink)

Hasok Chang is developing a new form of pragmatic scientific realism that aims to reorient the debate away from truth and towards practice. Central to his project is replacing truth as correspondence with his new notion of ‘operational coherence’, which is introduced as: 1) A success term with probative value to judge and guide epistemic activities. 2) A more useful alternative than truth as correspondence in guiding scientific practice. I argue that, given its current construal as neither necessary nor sufficient (...) for success, operational coherence is too weak and fails to satisfy both 1) and 2). I offer a stronger construal of operational coherence which aims to improve on Chang’s account by tying it to systematic success. This makes operational coherence necessary and sufficient for success. This new account, if successful, rescues 1) but not 2). I then take a step back and try to locate Chang’s pragmatic realism within the broader pragmatist tradition by comparing his views to the founding fathers Peirce, James and Dewey. I also assess to what extent we should consider Chang’s position ‘realist’, arguing that despite the many relativists threads running through it, Chang’s pragmatic realism is deserving of the realist label because its aims to maximize our learning from reality, even if it falls short of what many traditional realist are happy to accept as realism. I finish with comments on the epistemology of science pointing out that there is nothing intrinsic about a practice-based philosophy of science that precludes having both operational coherence and correspondence and highlighting that given a proper understanding these two notions could, in fact, be understood as complementary. I suggest one way this could be done. (shrink)

This paper provides an account of the nature of creativity in high-energy physics experiments through an integrated historical and philosophical study of the current and planned attempts to measure the self-coupling of the Higgs boson by two experimental collaborations at the Large Hadron Collider and the planned High Luminosity Large Hadron Collider. A notion of creativity is first identified broadly as an increase in the epistemic value of a measurement outcome from an unexpected transformation, and narrowly as a condition for (...) knowledge of the measurement of the self-coupling of the Higgs. Drawing upon Tal’s model-based epistemology of measurement this paper shows how without change to ‘readings’ a transformation to the model of the measurement process can increase the epistemic value of the measurement outcome. Such transformations are attributed to the creativity of the experimental collaboration. Creativity, in this context, is both a product, a creative and improved model, and the distributed collaborative process of transformation to the model of the measurement process. For the case of the planned measurements at the HL-LHC, where models of the measurement process perform the epistemic function of prediction, creativity is included in the models of the measurement process, both as projected quantified creativity and as an assumed property of the future collaborations. (shrink)

A core, constitutive norm of science is to remove or remedy the artefacts in one’s data. Here, we consider examples of artefacts from many fields of science (for example, astronomy, economics, electrophysiology, psychology, and systems neuroscience) and discuss their contribution to a more general evidential selection problem at the heart of the epistemology of evidence. Synthesizing and building on previously disparate discussions in many areas of the philosophy of science, we provide a novel, causal–pragmatic account that fits the examples and (...) clarifies the practices by which artefacts are discovered and remedied. (shrink)

Accounts of how the concept of temperature has evolved typically cast the story as ancillary to the history of the thermometer or the history of the concept of heat. But then, because the history of temperature is not treated as a subject in its own right, modern associations inadvertently get read back into the historical record. This essay attempts to lay down an authoritative record not of what people in the past thought about what we call ‘temperature’ but of what (...) they thought about what they called ‘temperature’ (or one of its cognates), from medieval times to today. I find that invention of the thermometer had little impact on the concept of temperature. Much more significant were Fahrenheit’s invention of a reliable instrument and William Thomson’s effort to make a degree of temperature a unit of measure. Overlapping definitions of temperature then emerged in the late nineteenth century, and twentieth-century scientific developments forced physicists to reconsider temperature’s conceptual boundaries. It turns out that the concept of temperature has evolved through stages that correspond to four increasingly sophisticated types of measurement. Its maturation and its maturity shed light on the philosophy of conceptual change. (shrink)

Psychometrics and the representational theory of measurement are widely used in social scientific measurement. They are currently pursued largely in isolation from one another. I argue that despite their separation in practice, RTM and psychometrics are complementary approaches, because they can contribute in complementary ways to the establishment of what I argue is a crucial measurement property, namely, representational interpretability. Because RTM and psychometrics are complementary in the establishment of representational interpretability, the current separation of measurement approaches is unfounded. 1Introduction2Two (...) Approaches to Measurement 2.1Representational theory of measurement2.2Psychometrics2.3Representational interpretability3Complementarity, Conceptually 3.1Representational theory of measurement: Conditions of representational interpretability3.2Psychometrics: Evidence of representational interpretability4Complementarity in Action 4.1What is the Rasch model?4.2Rasch and conjoint measurement5Conclusion: Critics and Fruits of Complementarity. (shrink)

Studies of patient decision‐making use many different measures to evaluate the quality of decisions and the decision‐making process, partly to determine whether the ethical goals of informed consent, patient autonomy, and shared decision‐making have been achieved. We describe these measures, grouped under three main approaches, and review their limitations, leading to three conclusions. First, no measure or combination of measures can provide a complete assessment of decision quality. Second, the quality of a decision is best characterized vaguely, for instance as (...) “good,” “satisfactory,” or “poor,” and these categorizations depend on qualitative judgments that go beyond quantitative measures. Third, bioethicists should focus on identifying and addressing poor or problematic decisions, rather than trying to incrementally increase decision quality, quantified by a measure. Decision‐quality measures can be useful in research and in advancing important goals of bioethics, as long as the challenges of defining and measuring decision quality are recognized. (shrink)

We analyze the usage of computer simulation at the LHC and derive seven jointly necessary requirements for a simulation to be considered ’trustworthy’, such that it can be used as proxy for experiments. We show that these requirements can also be applied to systems without direct experimental access and discuss their validity for properties that have not yet been probed. While being necessary, these requirements are not sufficient. Such trustworthy simulations will be analyzed for the relative epistemic statuses of simulation (...) and material measurements, from which we argue that claims of their parity are unfounded. Instead, using credibility as a measure for epistemic status, and in view of the temporal and epistemic dependence of simulation on material measurements, we argue that the latter have a higher epistemic status than the former. We further argue that suggestions to qualify the epistemic status by ’defocussing’ on the material connection to the target system of either human or natural experiments are misleading. (shrink)

In recent years, it has become commonplace among the Global Burden of Disease study authors to regard the disability-adjusted life year primarily as a descriptive health metric. During the first phase of the GBD, it was widely acknowledged that the DALY had built-in evaluative assumptions. However, from the publication of the 2010 GBD and onwards, two central evaluative practices—time discounting and age-weighting—have been omitted from the DALY model. After this substantial revision, the emerging view now appears to be that the (...) DALY is primarily a descriptive measure. Our aim in this article is to argue that the DALY, despite changes, remains largely evaluative. Our analysis focuses on the understanding of the DALY by comparing the DALY as a measure of disease burden in the two most significant phases of GBD publications, from their beginning to the most recent releases. We identify numerous assumptions underlying the DALY and group them as descriptive or evaluative. We conclude that while the DALY model arguably has become more descriptive, it remains, by necessity, largely evaluative. (shrink)

Physical theories often characterize their observables with real number precision. Many non-fundamental theories do so needlessly: they are more precise than they need to be to capture the physical matters of fact about their observables. A natural expectation is that a truly fundamental theory will require its full precision in order to exhaustively capture all of the fundamental physical matters of fact. I argue against this expectation and I show that we do not have good reason to expect that the (...) standard of precision set by successful theories, or even by a truly fundamental theory, will match the granularity of the physical facts. (shrink)

I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an (...) external perspective. Whether or not something counts as an agent depends on whether it is able to have a certain kind of perspective. My approach differs from many others by treating possession of a perspective as more basic than the possession of agency, representational content/vehicles, cognition, intentions, goals, concepts, or mental or psychological states; these latter capabilities require the former, not the other way around. I explain what it means for a system to be able to have a perspective at all, beginning with simple cases in biology, and show how self-contained normative perspectives about proper function and control can emerge from mechanisms with relatively simple dynamics. I then describe how increasingly complex control architectures can become organized that allow for more complex perspectives that approach agency. Next, I provide my own account of the kind of perspective that is necessary for agency itself, the goal being to provide a reference against which other accounts can be compared. Finally, I introduce a crucial distinction that is necessary for understanding human agency: that between inclinational and committal agency, and venture a hypothesis about how the normative perspective underlying committal agency might be mechanistically realized. (shrink)

By understanding laws of nature as geometrical rather than linguistic entities, this paper addresses how to describe theory structures and how to evaluate their continuity. Relying on conceptual spaces as a modelling tool, we focus on the conceptual framework an empirical theory presupposes, thus obtain a geometrical representation of a theory’s structure. We stress the relevance of measurement procedures in separating conceptual from empirical structures. This lets our understanding of scientific laws come closer to scientific practice, and avoids a widely (...) recognised deficit in current philosophy of science accounts, namely to risk a collapse of the physical into the mathematical. (shrink)

Many decades ago Patrick Suppes argued rather convincingly that theoretical hypotheses are not confronted with the direct, raw results of an experiment, rather, they are typically compared with models of data. What exactly is a data model however? And how do the interactions of particles at the subatomic scale give rise to the huge volumes of data that are then moulded into a polished data model? The aim of this paper is to answer these questions by presenting a detailed case (...) study of the construction of data models at the LHCb for testing Lepton Flavour Universality in rare decays of B-mesons. The close examination of the scientific practice at the LHCb leads to the following four main conclusions: raw data in their pure form are practically useless for the comparison of experimental results with theory, and processed data are in some cases epistemically more reliable, real and simulated data are involved in the co-production of the final data model and cannot be easily distinguished, theory-ladenness emerges at three different levels depending on the scope and the purpose for which background theory guides the overall experimental process and the overall process of acquiring and analysing data in high energy physics is too complicated to be fully captured by a generic methodological description of the experimental practice. (shrink)

This paper aims to study the foundations of applied mathematics, using a formalized base theory for applied mathematics: ZFCAσ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathsf {ZFCA}_{\sigma }$$\end{document} with atoms, where the subscript used refers to a signature specific to the application. Examples are given, illustrating the following five features of applied mathematics: comprehension principles, application conditionals, representation hypotheses, transfer principles and abstract equivalents.

Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...) ideas that scientific models are ‘similar’, or structurally morphic, to their target systems. I argue that these approaches are misguided, and that at best these relationships concern the accuracy of a pre-existing representational relationship. I also pay particular attention to the sense in which target systems can be appropriately taken to exhibit a ‘structure’, and van Fraassen’s recent argument concerning the pragmatic equivalence between representing phenomena and data. My next target is the idea that models should not be seen as objects in their own right, but rather what look like descriptions of them are actually direct descriptions of target systems, albeit not ones that should be understood literally. I argue that these approaches fail to do justice to the practice of scientific modelling. Finally I turn to the idea that how models represent is grounded, in some sense, in their inferential capacity. I compare this approach to anti-representationalism in the philosophy of language and argue that analogous issues arise in the context of scientific representation. Part iii contains my positive proposal. I provide an account of scientific representation based on Goodman and Elgin’s notion of representation-as. The result is a highly conventional account which is the appropriate level of generality to capture all of its instances, whilst remaining informative about the notion. I illustrate it with reference to the Phillips-Newlyn machine, models of proteins, and the Lotka-Volterra model of predator-prey systems. These examples demonstrate how the account must be understood, and how it sheds light on our understanding of how models are used. I finally demonstrate how the account meets the desiderata laid out at the beginning of the thesis, and outline its implications for further questions from the philosophy of science; not limited to issues surrounding the applicability of mathematics, idealisation, and what it takes for a model to be ‘true’. (shrink)