I argue that dimensional analysis provides an answer to a skeptical challenge to the theory of model mediated measurement. The problem arises when considering the task of calibrating a novel measurement procedure, with greater range, to the results of a prior measurement procedure. The skeptical worry is that the agreement of the novel and prior measurement procedures in their shared range may only be apparent due to the emergence of systematic error in the exclusive range of the novel measurement procedure. (...) Alternatively: what if the two measurement procedures are not in fact measuring the same quantity? The theory of model mediated measurement can only say that we _assume_ that there is a common quantity. In contrast, I show that the satisfaction of dimensional homogeneity across the metrological extension is independent evidence for the so-called assumption. This is illustrated by the use of dimensional analysis in high pressure experiments. This results in an extension of the theory of model mediated measurement, in which a common quantity in metrological extension is no longer assumed, but hypothesized. (shrink)

Both metaphysics and cognitive science raise the question of what natural concepts or properties are. A link between the two is notoriously hard to establish. I propose to take natural concepts or properties to be those that are revealed in interaction. The concept of affordances is refined and naturalized to spell out how interacting with objects grounds concepts. I will call this account “Ecological Empiricism”. I argue that the notion of naturalness within this framework turns out to be a gradable (...) – there are more or less natural properties – and dependent on the perspective taken – metaphysically natural properties are different from cognitive natural properties. From a metaphysical point of view, perfect correlations between actions and sensory input are relevant, which are best approximated by scientific measurement. For cognition, simple or basic actions are relevant. Although metaphysical and cognitive naturalness does not coincide according to Ecological Empiricism, it presents a common framework with a uniform conception of naturalness. (shrink)

Philosophers and scientists have often adopted the orthodox version of calibration which involves standardizing an instrument using a known phenomenon. The essential link between theoretical concepts and empirical data, in the philosophy of measurement, has generated the formulation of principles of coordination, synthetic a priori, and revisables. Operationalist thinking wanted to limit the scope of concepts to operations of measurement that are actually achievable. The coherentist perspective in the philosophy of measurement has operated a recovery of coordinationist epistemology and operationalism, (...) relying on a minimal number of ontological principles. Models of an instrument involve a commitment to separation between idealized theories and material things. However, philosophers and metrologists have advocated the requirement of a rich theoretical content in the modeling of measuring instruments. According to other contributions, the epistemic privilege of measurement precedes a background theory and its robustness lies in the free contact with empirical data. Moreover, the applicability regime of a theory dictates its boundary conditions, which guide the experimenter in the design of measuring instruments and provide the basis for operationalizing the meaning of theoretical terms. I support operational pluralism, measurement operations involving different physical indicators, accompanied by dynamic coherentism. The James Webb Space Telescope calibration program is a significant case. Observations of calibration stars by various methods are used to calculate the factors that convert a measurement in instrumental units to physical units. (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)

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)

This paper proposes an account of accurate scientific representation in terms of techniques that produce data from a target phenomenon. I consider an approach to accurate representation that abstracts from such epistemic factors, justified by a thesis I call Ontic Priority. This holds that criteria for representational accuracy depend on a pre-established account of the nature of the relation between a model and its target phenomenon. I challenge Ontic Priority, drawing on the observation that many working scientists do not have (...) access to information allowing them to describe this relation between model and target or compare them accordingly. I critique the ability of an ontic-first approach to provide accuracy criteria in such cases and present historical support for an alternative according to which a model is accurate if and only if integrating the model into a theory of the data acquisition process yields well-fitting predictions of patterns in the data. (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.

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value of (...) discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

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

While the pursuitworthiness of philosophical ideas has changed over time, philosophical practice and methodology have not kept pace. The worthiness of a philosophical pursuit includes not only the ideas and objectives one pursues but also the methods with which one pursues them. In this paper, we articulate how empirical approaches benefit philosophy of science, particularly advocating for the use of qualitative methods for understanding the social and normative aspects of scientific inquiry. After situating qualitative methods within empirical philosophy of science, (...) we discuss how to adapt these traditionally sociological methods to empirically inform philosophical questions. Our aim is to normalize and legitimize qualitative methods for philosophical purposes and discuss how they can elucidate descriptive and normative components of scientific practice in a more generalizable non-idealized manner. We contend that qualitative methods are particularly well suited to philosophical interest in the social norms of science, their achievability, and their mutability. Furthermore, unlike more historical case studies in philosophy, qualitative methods enable more confidence in generalizability, albeit limited, from a concrete sample to a larger class. We conclude by addressing anxieties about the distinctness of empirical philosophy of science from social epistemology and from sociology of science. (shrink)

The status of laws of nature has been the locus of a lively debate in recent philosophy. Most participants have assumed laws play an important role in science and metaphysics while seeking their objective ground in the natural world, though some skeptics have questioned this assumption. So-called Humeans look to base laws on actual, particular facts such as those specified in David Lewis’s Humean mosaic. Their opponents argue that such a basis is neither necessary nor sufficient to support the independent (...) existence of scientific laws. This essentially metaphysical debate has paid scant attention to the details of scientific practice. It has mostly focused on so-called fundamental laws, assumed to take a particular form. I propose a pragmatist alternative—not as another position in the debate but as an alternative to the debate itself. This pragmatist alternative offers a view that questions the representational conception of truth presupposed by participants to the debate as well as the metaphysical import of fundamental laws. Statements of law serve many different purposes in science: I’ll look at some. But their central role is in inference, primarily to improve the epistemic state of a scientist with limited access to information. To play this role, a scientific law statement need be neither necessary, unconditionally universal nor even true. It must merely be sufficiently reliable within its domain of application. The use of laws in astrophysics and metrology will help to illustrate these points. (shrink)

Measures of happiness are increasingly being used throughout the social sciences. While these measures have attracted numerous types of criticisms, a crucial aspect of these measures has been left largely unexplored—their calibration. Using Eran Tal’s recently developed notion of calibration we argue first that the prospect of continued calibration of happiness measures is crucial for the science of happiness, and second, that continued calibration of happiness measures faces a particular problem—The Two Unknowns Problem. The Two Unknowns Problem relies on the (...) claim that individuals are necessarily a part of the measurement apparatus in first person measures of happiness, and the claim that we have no reason to believe that the evaluation standards people employ are invariant across individuals and time. We argue that calibrating happiness measures therefore involves solving an equation with two unknowns—an individual’s degree of happiness, and their evaluation standards—which is, generally, not possible. Third, we consider two possible escape routes from this problem and we suggest that the most promising route requires yet unexplored empirical and theoretical work on linking happiness to behavioral or neural evidence. (shrink)

In this paper, I argue for a distinction between two scales of coordination in scientific inquiry, through which I reassess Georg Simon Ohm’s work on conductivity and resistance. Firstly, I propose to distinguish between measurement coordination, which refers to the specific problem of how to justify the attribution of values to a quantity by using a certain measurement procedure, and general coordination, which refers to the broader issue of justifying the representation of an empirical regularity by means of abstract mathematical (...) tools. Secondly, I argue that the development of Ohm’s measurement practice between the first and the second experimental phase of his work involved the change of the measurement coordination on which he relied to express his empirical results. By showing how Ohm relied on different calibration assumptions and practices across the two phases, I demonstrate that the concurrent change of both Ohm’s experimental apparatus and the variable that Ohm measured should be viewed based on the different form of measurement coordination. Finally, I argue that Ohm’s assumption that tension is equally distributed in the circuit is best understood as part of the general coordination between Ohm’s law and the empirical regularity that it expresses, rather than measurement coordination. (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)

When discrepancies are discovered between the outcomes of different measurement procedures, two sorts of explanation are open to scientists. Either some of the outcomes are inaccurate or the procedures are not measuring the same quantity. I argue that, due to the possibility of systematic error, the choice between and is underdetermined in principle by any possible evidence. Consequently, foundationalist criteria of quantity individuation are either empty or circular. I propose a coherentist, model-based account of measurement that avoids the underdetermination problem, (...) and use this account to explain how scientists individuate quantities in practice. (shrink)

This paper provides a philosophical assessment of leading theory-based, evidence-based and coherentist approaches to the definition and the measurement of well-being. It then builds on this assessment to articulate a reformed division of labor for the science of well-being and argues that this reformed division of labor can improve on the proffered approaches by combining the most plausible tenets of theory-based approaches with the most plausible tenets of coherentist approaches. This result does not per se exclude the possibility that theory-based (...) and coherentist approaches may be independently improved or amended in the years to come. Still, together with the challenges that affect these approaches, it strengthens the case for combining the most plausible tenets of those approaches. (shrink)

Axiomatic measurement theories are commonly interpreted as claiming that, in order to quantify an empirical domain, the qualitative structure of data about that domain must be mapped to a numerical structure. Such mapping is supposed to be established independently, i.e., without presupposing that the domain can be quantified. This interpretation is based on two myths: that it is possible to independently infer the qualitative structure of objects from empirical data, and that the adequacy of numerical representations can only be justified (...) by mapping such qualitative structures to numerical ones. I dispel the myths and show that axiomatic measurement theories provide an inadequate characterization of the kind of evidence required to detect quantities. (shrink)

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are data-laden and data are model-laden. In this articl...

This paper explores the use of new scientific techniques to examine collections of historic scientific apparatus and other technological artefacts. One project under discussion uses interferometry to examine the history of lens development, while another uses X-ray fluorescence to discover the kinds of materials used to make early mathematical and astronomical instruments. These methods lead to surprising findings: instruments turn out to be fake, and lens makers turn out to have been adept at solving the riddle of aperture. Although exciting, (...) in some ways this is neither novel nor particularly unusual. After all, lab techniques have been used in art and archaeological collections for a very long time. In fact, scientific instruments themselves have been examined in this way since at least the 1950s. What, then, is special about the use of new instruments to examine old instruments? We argue that the answer has less to do with measuring historical innovation or establishing priority, and more to do with networks of craft know-how that, typically, have left no other historical traces than those embodied in surviving instruments themselves. We show, in particular, how collections of objects can be mobilised within wider histories of knowledge, placing instruments within a dynamic interplay of craft knowledge, expertise, labour, commerce, and material exchange, over the longue durée. Finally, we suggest that these kinds of lab analyses can be given an extra dimension through the use of computational modelling, and we introduce the “Tools of Knowledge” project, which is designed to bring together XRF with techniques from the digital humanities, in order to tell a new story about the development of scientific instruments from the 16th to the 20th century. (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)

We present a novel kind of “socio-functional” foundationalism rooted in the division of scientific labor. Our foundationalism is social in that it involves a socio-epistemic phenomenon we dub epistemic outsourcing, whereby claims from one group of scientists provide epistemological foundations for another group of scientists. We argue that: (1) epistemic outsourcing results in a legitimate form of epistemic foundationalism, (2) this sort of foundationalism can be used to shed light on the epistemology of measurement; and (3) epistemic outsourcing is a (...) distinctively collective epistemic phenomenon. (shrink)

Supervised machine learning has found its way into ever more areas of scientific inquiry, where the outcomes of supervised machine learning applications are almost universally classified as predictions. I argue that what researchers often present as a mere terminological particularity of the field involves the consequential transformation of tasks as diverse as classification, measurement, or image segmentation into prediction problems. Focusing on the case of machine-learning enabled poverty prediction, I explore how reframing a measurement problem as a prediction task alters (...) the primary epistemic aim of the application. Instead of measuring a property, machine learning developers conceive of their models as predicting a given measurement of this property. I argue that this _predictive reframing_ common to supervised machine learning applications is epistemically and ethically problematic, as it allows developers to externalize concerns critical to the epistemic validity and ethical implications of their model’s inferences. I further hold that the predictive reframing is not a necessary feature of supervised machine learning by offering an alternative conception of machine learning models as measurement models. An interpretation of supervised machine learning applications to measurement tasks as _automatically-calibrated model-based measurements_ internalizes questions of construct validity and ethical desirability critical to the measurement problem these applications are intended to and presented as solving. Thereby, this paper introduces an initial framework for exploring technical, historical, and philosophical research at the intersection of measurement and machine learning. (shrink)

In this paper we argue that the difference between standard measurement and proxy measurement in paleoclimatology should not be understood in terms of ‘directness’. Measurements taken by climatologists to be paradigmatically non-proxy exhibit the kinds of indirectness that are thought to separate them proxy measurement. Rather, proxy measurements and standard measurements differ in how they account for confounding causal factors. Measurements are ‘proxy’ to the extent that the measurements require vicarious controls, while measurements are not proxy, but rather ‘standard’, to (...) the extent that the measurement apparatus provides sufficient physical control on its own. Guided by this account of proxy measurement, we then consider some of the challenges specific to historical proxy measurement and how it is that historical scientists address these challenges. Historical scientists rely on significant causal dependencies and naturally preserved signals to mitigate the influence of destructive processes over time. (shrink)

It is assumed that scientific models contain no superfluous model elements in scientific representation. A representational model is constructed with all the model elements serving the representational purpose. The received view has it that there are no redundant model elements which are non-representational. Contrary to this received view, I argue that there exist some non-representational model elements which are essential in scientific representation. I call them representation-supporting model elements in virtue of the fact that they play the role to support (...) the representational role of representational model elements. Representation-supporting model elements, which have a characteristic of dependability, are not to be eliminated in the process of modeling although they are playing second fiddle to representational model elements in scientific representation. (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)

We propose a new account of calibration according to which calibrating a technique shows that the technique does what it is supposed to do. To motivate our account, we examine an early twentieth-century debate about chlorophyll chemistry and Mikhail Tswett’s use of chromatographic adsorption analysis to study it. We argue that Tswett’s experiments established that his technique was reliable in the special case of chlorophyll without relying on either a theory or a standard calibration experiment. We suggest that Tswett broke (...) the experimenters’ regress by appealing to material facts in the common ground for chemists at the time. (shrink)

Over the last twenty-five years, climate scientists working on the attribution of climate change to humans have developed increasingly sophisticated statistical models in a process that can be understood as a kind of calibration: the gradual changes to the statistical models employed in attribution studies served as iterative revisions to a measurement(-like) procedure motivated primarily by the aim of neutralizing particularly troublesome sources of error or uncertainty. This practice is in keeping with recent work on the evaluation of models more (...) generally that views models as tools for particular tasks: what drives the process is the desire for models that provide more reliable grounds for inference rather than accuracy to the underlying mechanisms of data-generation. (shrink)