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)

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)

This paper assesses the comparative reliability of two belief-revision rules relevant to the epistemology of disagreement, the Equal Weight and Stay the Course rules. I use two measures of reliability for probabilistic belief-revision rules, calibration and Brier Scoring, to give a precise account of epistemic peerhood and epistemic reliability. On the calibration measure of reliability, epistemic peerhood is easy to come by, and employing the Equal Weight rule generally renders you less reliable than Staying the Course. On the (...) Brier-Score measure of reliability, epistemic peerhood is much more difficult to come by, but employing the Equal Weight rule always renders you more reliable than Staying the Course. I conclude with some normative lessons we can draw from these formal results. (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)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. Models function as measuring instruments by transferring observations of an economic system into quantitative facts about that system. These facts are evaluated by their accuracy. Accuracy is achieved by calibration. For calibration standards are needed. Then two strategies can be distinguished. One aims at estimating the invariant (structural) equations of the system. The other is to use (...) known stable facts about the system to adjust the model parameters. For this latter strategy, the requirement of models as homomorphic mappings is not required anymore. (shrink)

The signals in numerous complex systems of engineering can be regarded as nonlinear parameter trend with noise which is identically distributed random signals or deterministic stationary chaotic signals. The commonly used methods for parameter estimation of nonlinear trend in signals are mainly based on least squares. It can cause inaccurate estimation results when the noise is complex. This paper proposes a calibration method for this issue in the case of single parameter via nonstationarity measure from the perspective of the (...) stationarity of residual sequence. Some numerical studies are conducted for validation. Results of numerical studies show that the proposed calibration method performs well for various models with different noise strengths and types and can significantly improve the accuracy of initial estimates obtained by least squares method. This is the first time that the nonstationarity measure is applied to the parameter calibration. All these results will be a guide for future studies of other parameter calibrations. (shrink)

Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring "goodness" of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of.5 occur, 70 percent of forecasts made with probability.7 occur, etc. To summarize the conclusions: (i) Surveys designed to display calibration curves, (...) from which a recalibration is to be calculated, are useless without due consideration for the interconnections between questions (forecasts) in the survey. (ii) Subject to feedback, calibration in the long run is otiose. It gives no ground for validating one coherent opinion over another as each coherent forecaster is (almost) sure of his own long-run calibration. (iii) Calibration in the short run is an inducement to hedge forecasts. A calibration score, in the short run, is improper. It gives the forecaster reason to feign violation of total evidence by enticing him to use the more predictable frequencies in a larger finite reference class than that directly relevant. (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 the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and thus alternative with (...) one another, as sometimes claimed nowadays. The crucial problem is whether assuming this standpoint implies definitely renouncing to maintain a role for truth and the related concepts, particularly accuracy, in measurement. It is argued here that the well known objections against true values in measurement, which would lead to refuse the concept of accuracy as non-operational, or to maintain it as only qualitative, derive from a not clear distinction between three distinct processes: the metrological characterization of measuring systems, their calibration, and finally measurement. Under the hypotheses that (1) the concept of true value is related to the model of a measurement process, (2) the concept of uncertainty is related to the connection between such model and the world, and (3) accuracy is a property of measuring systems (and not of measurement results) and uncertainty is a property of measurement results (and not of measuring systems), not only the compatibility but actually the conjoint need of error-based and uncertainty-based modeling emerges. (shrink)

H. Collins has challenged the empiricist understanding of experimentation by identifying what he thinks constitutes the experimenter’s regress: an instrument is deemed good because it produces good results, and vice versa. The calibration of an instrument cannot alone validate the results: the regressive circling is broken by an agreement essentially external to experimental procedures. In response, A. Franklin has argued that calibration is a key reasonable strategy physicists use to validate production of results independently of their interpretation. The (...) physicists’ arguments about the merits of calibration are not coextensive with the interpretation of results, and thus an objective validation of results is possible. I argue, however, that the in-situ calibrating and measurement procedures and parameters at the Large Hadron Collider are closely and systematically interrelated. This requires empiricists to question their insistence on the independence of calibration from the outcomes of the experiment and rethink their position. Yet this does not leave the case of in-situ calibration open to the experimenter’s regress argument; it is predicated on too crude a view of the relationship between calibration and measurement that fails to capture crucial subtleties of the case. (shrink)

The paper introduces and formally defines a functional concept of a measuring system, on this basis characterizing the measurement as an evaluation performed by means of a calibrated measuring system. The distinction between exact and uncertain measurement is formalized in terms of the properties of the traceability chain joining the measuring system to the primary standard. The consequence is drawn that uncertain measurements lose the property of relation-preservation, on which the very concept of measurement is founded according (...) to the representational viewpoint. Finally, from the analysis of the inter-relations between calibration and measurement the fundamental reasons of the claimed objectivity and intersubjectivity of measurement are highlighted, a valuable epistemological result to characterize measurement as a particular kind of evaluation. (shrink)

This paper deals with calibration in scientific practices which investigate relatively well-understood natural phenomena by means of already standardized instrumental devices. Calibration is a crucial topic, since it conditions the reliability of instrumental procedures in science. Yet although important, calibration is a relatively neglected topic. We think more attention should be devoted to calibration. The paper attempts to take a step in this direction. The aims are two-fold: (1) to characterize calibration in a relatively simple (...) kind of scientific practices; (2) to provide conceptual and taxonomic tools of broader scope that help to get a better understanding of calibration in more complex cases and other kinds of scientific practices. For this purpose, we first provide indications for why a conceptual framework is needed. Second, a bibliographic survey of works dealing with calibration is attempted. Third, we introduce different tools to enable a better understanding of calibration. Fourth, we turn to the elaboration of what we call a “simple exemplar” of calibration, illustrated through the case of the calibration of an equal-arm balance. Fifth, the tools previously introduced, and the framework of the simple exemplar, are applied to a more complex case of calibration: calibration procedures in X-ray experiments. This serves to show the work accomplished by the simple exemplar and to emphasize features of more complex cases of calibration. Eventually, we revisit and specify the nature, status, scope and value of the proposed framework. (shrink)

Visual aids can improve comprehension of risks associated with medical treatments, screenings, and lifestyles. Do visual aids also help decision makers accurately assess their risk comprehension? That is, do visual aids help them become well calibrated? To address these questions, we investigated the benefits of visual aids displaying numerical information and measured accuracy of self-assessment of diagnostic inferences (i.e., metacognitive judgment calibration) controlling for individual differences in numeracy. Participants included 108 patients who made diagnostic inferences about three medical tests (...) on the basis of information about the sensitivity and false-positive rate of the tests and disease prevalence. Half of the patients received the information in numbers without a visual aid, while the other half received numbers along with a grid representing the numerical information. In the numerical condition, many patients --especially those with low numeracy-- misinterpreted the predictive value of the tests and profoundly overestimated the accuracy of their inferences. Metacognitive judgment calibration mediated the relationship between numeracy and accuracy of diagnostic inferences. In contrast, in the visual aid condition, patients at all levels of numeracy showed high-levels of inferential accuracy and metacognitive judgment calibration. Results indicate that accurate metacognitive assessment may explain the beneficial effects of visual aids and numeracy --a result that accords with theory suggesting that metacognition is an essential part of risk literacy. We conclude that well-designed risk communications can inform patients about health-relevant numerical information while helping them assess the quality of their own risk comprehension. (shrink)

Grounded in a will to adapt to dangers, and espouse both responsibility and resilience, voluntary measures have largely replaced one of the oldest public health strategies, quarantine. The Covid-19 pandemic, however, elicited a broad sweep of tactics from the archive of public health armoury. On a general level, this review essay addresses the common measures rolled out by various authorities against the pandemic - the lock-downs, reopening process, financial support and vaccination. By relating these measures to 1) the “plague-stricken town”, (...) deployed during the seventeenth and eighteenth centuries in Europe by the Polizeistaat; 2) the “self-regulation strategy” that emerged with liberal ideas at the end of the eighteenth century; and 3) the “minimum security” programmed by neoliberal governmentality in the second half of the twentieth century, it is suggested that tensions between freedom and security during, and after, the pandemic can be better understood. To end, the essay noticed that the pandemic has enforced tensions in the administration and calibration of individual wishes and collective wellbeing, creating a fragile “freedom-security relationship” and new problem space for self-regulation. (shrink)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. There are two different approaches to deal with the justification of a model: an axiomatic and an empirical approach. The axiomatic approach verifies whether a given relational structure satisfies certain axioms to secure homomorphic mapping. The empirical approach conceives models to function as measuring instruments by transferring observations of a phenomenon under investigation into quantitative facts about that phenomenon. (...) These facts are evaluated by their accuracy and precision. Precision is generally achieved by least squares methods and accuracy by calibration. For calibration standards are needed. Then two polar strategies can be distinguished: white-box modeling and black-box modeling. The first strategy of modeling aims at estimating the invariant equations of the phenomenon, thereby fulfilling Hertz’s correctness requirement. The latter strategy of modeling is to use known stable facts about the phenomenon to adjust the model parameters, thereby fulfilling Hertz’s appropriateness requirement. For this latter strategy, the requirement of models as homomorphic mappings has been dropped. Where one will find the axiomatic approach more often used for measurement in the laboratory, the empirical approach is more appropriate for measurement outside the laboratory. The reason for this is that for measurement of phenomena outside the laboratory, one also needs to take account of the environment to achieve accurate results. Environments are generally too relation-rich for an axiomatic approach, which are only applicable for relation-poor systems. The white-box modeling strategy, reflecting the complexity of the environment due to its correctness requirement, will, however, lead to immensely large models. To avoid this problem, modular design is an appropriate strategy to reduce this complexity. Modular design is a grey-box modeling strategy. Grey-box models are assemblies of modules; these are black boxes with standard interface. It should be noted that the structure of the assemblage need not be homomorphic to the relations describing the interaction between phenomenon and environment. These three modeling strategies map out the possible designs for computer simulations as measuring instruments. Whether a simulation is based on a white-box, grey-box or black-box model is only determined by the relationship between the phenomenon and its environment and not by e.g. its materiality or physicality. (shrink)

A prominent feature of late nineteenth-century psychology was its intense preoccupation with precision. Precision was at once an ideal and an argument: the quest for precision helped psychology to establish its status as a mature science, sharing a characteristic concern with the natural sciences. We will analyse how psychologists set out to produce precision in 'mental chronometry', the measurement of the duration of psychological processes. In his Leipzig laboratory, Wundt inaugurated an elaborate research programme on mental chronometry. We will (...) look at the problem of calibration of experimental apparatus and will describe the intricate material, literary, and social technologies involved in the manufacture of precision. First, we shall discuss some of the technical problems involved in the measurement of ever shorter time-spans. Next, the Cattell-Berger experiments will help us to argue against the received view that all the precision went into the hardware, and practically none into the social organization of experimentation. Experimenters made deliberate efforts to bring themselves and their subjects under a regime of control and calibration similar to that which reigned over the experimental machinery. In Leipzig psychology, the particular blend of material and social technology resulted in a specific object of study: the generalized mind. We will then show that the distribution of precision in experimental psychology outside Leipzig demanded a concerted effort of instruments, texts, and people. It will appear that the forceful attempts to produce precision and uniformity had some rather paradoxical consequences. (shrink)

The assessment of models in an experiment depends on their material nature and their function in the experiment. Models that are used to make the phenomenon under investigation visible - sensors - are assessed by calibration. However, calibration strategies assume material intervention. The experiment discssed in this paper is an experiment in economics to measure the influence of technology shocks on business cycles. It uses immaterial, mathematical instruments. It appears that calibration did not work for these kinds (...) of models, it did not provide reliable evidence for the facts of the business cycle. (shrink)

This study explored calibrating a large item bank for use in multidimensional health measurement with computerized adaptive testing, using both item responses and response time (RT) information. The Activity Measure for Post-Acute Care is a patient-reported outcomes measure comprised of three correlated scales (Applied Cognition, Daily Activities, and Mobility). All items from each scale are Likert type, so that a respondent chooses a response from an ordered set of four response options. The most appropriate item response theory model for (...) analyzing and scoring these items is the multidimensional graded response model (MGRM). During the field testing of the items, an interviewer read each item to a patient and recorded, on a tablet computer, the patient’s responses and the software recorded RTs. Due to the large item bank with over 300 items, data collection was conducted in four batches with a common set of anchor items to link the scale. Van der Linden’s (2007) hierarchical modeling framework was adopted. Several models, with or without interviewer as a covariate and with or without interaction between interviewer and items, were compared for each batch of data. It was found that the model with the interaction between interviewer and item, when the interaction effect was constrained to be proportional, fit the data best. Therefore, the final hierarchical model with lognormal model for RT and the MGRM for response data was fitted to all batches of data via a concurrent calibration. Evaluation of parameter estimates revealed that (1) adding response time information did not affect the item parameter estimates and their standard errors significantly; (2) adding response time information helped reduce the standard error of patients’ multidimensional latent trait estimates, but adding interviewer as a covariate did not result in further improvement. Implications of the findings for follow up adaptive test delivery design are discussed. (shrink)

IntroductionThe National Institute for Health and Care Excellence guidelines acknowledge the importance of the parent–infant relationship for child development but highlight the need for further research to establish reliable tools for assessment, particularly for parents of children under 1 year. This study explores the acceptability and psychometric properties of a co-developed tool, ‘Me and My Baby’.Study designA cross-sectional design was applied. The MaMB was administered universally with mothers during routine 6–8-week Health Visitor contacts. The sample comprised 467 mothers. Dimensionality of (...) instrument responses were evaluated via exploratory and confirmatory ordinal factor analyses. Item response modeling was conducted via a Rasch calibration to evaluate how the tool conformed to principles of ‘fundamental measurement’. Tool acceptability was evaluated via completion rates and comparing ‘completers’ and ‘non-completers’ demographic differences on age, parity, ethnicity, and English as an additional language. Free-text comments were summarized. Data sharing agreements and data management were compliant with the General Data Protection Regulation, and University of York data management policies.ResultsHigh completion rates suggested the MaMB was acceptable. Psychometric analyses showed the response data to be an excellent fit to a unidimensional confirmatory factor analytic model. All items loaded statistically significantly and substantially on a single underlying factor. The item response modeling showed that most MaMB items fitted the Rasch model. item reliability was high yet the test yielded little information on each respondent, as highlighted by the relatively low ‘person separation index’ of 0.1.Conclusion and next stepsMaMB reliably measures a single construct, likely to be infant bonding. However, further validation work is needed, preferably with ‘enriched population samples’ to include higher-need/risk families. The MaMB tool may benefit from reduced response categories and some modest item wording amendments. Following further validation and reliability appraisal the MaMB may ultimately be used with fathers/other primary caregivers and be potentially useful in research, universal health settings as part of a referral pathway, and clinical practice, to identify dyads in need of additional support/interventions. (shrink)

Drawing on a passage from Ramsey's Truth and Probability, we formulate a simple, plausible constraint on evaluating the accuracy of credences: the Calibration Test. We show that any additive, continuous accuracy measure that passes the Calibration Test will be strictly proper. Strictly proper accuracy measures are known to support the touchstone results of accuracy-first epistemology, for example vindications of probabilism and conditionalization. We show that our use of Calibration is an improvement on previous such appeals by showing (...) how it answers or sidesteps problems that have been raised for previous work in this area. (shrink)

Hacking’s Law of Likelihood says—paraphrasing—that data support hypothesis H1 over hypothesis H2 whenever the likelihood ratio for H1 over H2 exceeds 1. But Hacking later noted a seemingly fatal flaw in the LR itself: it cannot be interpreted as the degree of “evidential significance” across applications. I agree with Hacking about the problem, but I do not believe the condition is incurable. I argue here that the LR can be properly calibrated with respect to the underlying evidence, and I sketch (...) the rudiments of a methodology for so doing. (shrink)

Abner Shimony argues that degrees of belief satisfy the axioms of probability because their epistemic goal is to match estimates of objective probabilities. Because the estimates obey the axioms of probability, degrees of belief must also obey them to reach their epistemic goal. This calibration argument meets some objections, but with a few revisions it can surmount those objections. It offers a good alternative to the Dutch book argument for compliance with the probability axioms. The defense of Shimony's (...) class='Hi'>calibration argument examines rational pursuit of an epistemic goal, introduces strength of evidence and its measurement, and distinguishes epistemic goals and functions. (shrink)

Ignoring consciousness, I apply Palmer 's ideas to a photometer, for which calibration is analogous to socialization of humans to agree in color. Some attributes of the photometer – such as its aperture – do not need to be known because their values are transparent to calibration. But a writing demon can wreak havoc if it permutes measured values before interpolation completes calibration – as happens in Palmer 's color rewirings.

Calibration errors are inevitable and should not be ignored during the estimation of item parameters. Items with calibration error can affect the measurement results of tests. One of the purposes of the current study is to investigate the impacts of the calibration errors during the estimation of item parameters on the measurement accuracy, average test length, and test efficiency for variable-length cognitive diagnostic computerized adaptive testing. The other purpose is to examine the methods for reducing (...) the adverse effects of calibration errors. Simulation results show that calibration error has negative effect on the measurement accuracy for the deterministic input, noisy “and” gate model, and the reduced reparameterized unified model; the average test lengths is shorter, and the test efficiency is overestimated for items with calibration errors; the compensatory reparameterized unified model is less affected by the calibration errors, and the classification accuracy, average test length, and test efficiency are slightly stable in the CRUM framework; methods such as improving the quality of items, using large calibration sample to calibrate the parameters of items, as well as using cross-validation method can reduce the adverse effects of calibration errors on CD-CAT. (shrink)

The words 'true value' assume an existential relationship with the thing being measured. There is assumed to exist some aspect of the thing being measured that is independent of its relationship to the person who is interested in the result of the measurement. Yet measurement is a response to the need of an observer to know something about the real world. There is therefore an epistemological aspect to measurement. Some aspect of measurement has to do with (...) the observer as a knower of the result of the measurement. The paper considers electrical measurement. It proposes that these relationships correspond to two distinct kinds of measurement: one has the characteristic that there does exist such a thing as a true value, though it cannot be known: in the other kind, no such thing as true value even exists. The notion of true value is very useful, and for the kind of measurement where such a thing does not exist, the paper defines an alternative that has the advantage that it can actually be known under some circumstances in calibration. (shrink)

The practice of economic science is dominated by model building. To evaluate economic policy, models are built and used to produce numbers to inform us about economic phenomena. Although phenomena are detected through the use of observed data, they are in general not directly observable. To 'see' them we need instruments. More particularly, to obtain numerical facts of the phenomena we need measuring instruments. This paper will argue that in economics models function as such instruments of observation, more specific as (...) measuring instruments. In measurement theory, measurement is a mapping of some class of aspects of characteristics of the empirical world into a set of numbers. The paper's view is that economic modelling is a specific kind of mapping to which the standard account on how models are obtained and assessed does not apply. Models are not easily or simply derived from theories and subsequently tested against empirical data. Instruments are constructed by integrating several theoretical and empirical ideas and requirements in such a way that their performance meets a beforehand chosen standard. The empirical requirement is that the model should take account of the phenomenological facts, so that the reliability of the model is not assessed by post-model testing but obtained by calibration. (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)

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)

The aim of this work is twofold. First, we survey the techniques developed in Perthame and Zubelli (Inverse Probl 23(3):1037–1052, 2007 ), Doumic et al. (Inverse Probl 25, 2009 ) to reconstruct the division (birth) rate from the cell volume distribution data in certain structured population structured population models. Secondly, we implement such techniques on experimental cell volume distributions available in the literature so as to validate the theoretical and numerical results. As a proof of concept, we use the experimental (...) data experimental data reported in the classical work of Kubitschek (Biophys J 9(6):792–809, 1969 ) concerning Escherichia coli in vitro experiments measured by means of a Coulter transducer-multichannel analyzer system (Coulter Electronics, Inc., Hialeah, FL, USA). Despite the rather old measurement technology, the reconstructed division rates still display potentially useful biological features. (shrink)

As machine learning informs increasingly consequential decisions, different metrics have been proposed for measuring algorithmic bias or unfairness. Two popular “fairness measures” are calibration and equality of false positive rate. Each measure seems intuitively important, but notably, it is usually impossible to satisfy both measures. For this reason, a large literature in machine learning speaks of a “fairness tradeoff” between these two measures. This framing assumes that both measures are, in fact, capturing something important. To date, philosophers have seldom (...) examined this crucial assumption, and examined to what extent each measure actually tracks a normatively important property. This makes this inevitable statistical conflict – between calibration and false positive rate equality – an important topic for ethics. In this paper, I give an ethical framework for thinking about these measures and argue that, contrary to initial appearances, false positive rate equality is in fact morally irrelevant and does not measure fairness. (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)

Medicine is often criticized in science and technology studies (STS) for its dominating measuring practices. To date, the focus has been on two areas of “metric work”: health-care workers and metric infrastructures. In this article, I step back into the training of clinicians, which is important for understanding more about how practices of measurement are developed. I draw on ethnographic fieldwork in a Dutch medical school to look at how a ubiquitous and mundane tool––measuring tapes––is embodied by medical students (...) as they learn to coordinate their sensory knowledge. In doing so, they create their own bodies as the standard or measure of things. Unpacking educational practices concerning this object, I suggest that tracing the making of measuring bodies offers new insights into medical metric work. This also speaks to the growing interest in STS in sensory science, where the body is fashioned as a measuring instrument. Specifically, two interrelated contributions build on and deepen STS scholarship: first, the article shows that learning is an embodied process of inner-scaffold making; second, it suggests that the numerical objectification of sensory knowing is not a calibration to “objectivity machines” but rather to oscillations between bodies and objects that involve sensory-numerical work. (shrink)

The Journal of "Religious Ethics" marks the tercentenary of Edwards's birth with the following collection of essays. In keeping with the overall mission of the journal, this tribute takes the form of historical and constructive reflection, in which diverse perspectives on Edwards's work and diverse forms of engagement with it supplement and correct one another. Our hope is that these essays will serve both to generate interest in Edwards's work among those who are unfamiliar with him, and to advance the (...) discussion of central issues in theological and religious ethics. In this introductory essay, we will offer some reflections on Edwards's general significance for contemporary ethics, followed by a closer examination of his main texts and a brief summary of the essays collected here. (shrink)

A healthy work-life balance has become increasingly important to people trying to cope with the pressures of contemporary society. This trend highlights the fallacy of assessing well-being in terms of finance alone; how much time we have matters just as much as how much money. The authors of this book have developed a novel way to measure 'discretionary time': time which is free to spend as one pleases. Exploring data from the US, Australia, Germany, France, Sweden and Finland, they show (...) that temporal autonomy varies substantially across different countries and under different living conditions. By calibrating how much control people have over their time, and how much they could have under alternative welfare, gender or household arrangements, this book offers a new perspective for comparative cross-national enquiries into the temporal aspects of human welfare. (shrink)

How is conceptual foreignness received within an existing territory? I am grateful to my respondents for receiving my invocation of foreignness from phenomenological psychopathology not as a question of culture or nationality but rather, in terms of philosophical distance. As I ask in the article: how do we measure philosophical distance? Rather than complete agreement, or assimilation, or estrangement, perhaps distance is best calibrated through the small events of thought–understandings, misunderstandings, and clarifications, that punctuate even the most thoughtful and hospitable (...) reception, as I have been fortunate to receive from our respondents. In my brief response, I will focus on some of these smaller events... (shrink)

Epistemologists and philosophers of science have often attempted to express formally the impact of a piece of evidence on the credibility of a hypothesis. In this paper we will focus on the Bayesian approach to evidential support. We will propose a new formal treatment of the notion of degree of confirmation and we will argue that it overcomes some limitations of the currently available approaches on two grounds: (i) a theoretical analysis of the confirmation relation seen as an extension of (...) logical deduction and (ii) an empirical comparison of competing measures in an experimental inquiry concerning inductive reasoning in a probabilistic setting. (shrink)

Brain–computer interfaces (BCIs) utilizing machine learning techniques are an emerging technology that enables a communication pathway between a user and an external system, such as a computer. Owing to its practicality, electroencephalography (EEG) is one of the most widely used measurements for BCI. However, EEG has complex patterns and EEG-based BCIs mostly involve a cost/time-consuming calibration phase; thus, acquiring sufficient EEG data is rarely possible. Recently, deep learning (DL) has had a theoretical/practical impact on BCI research because of its (...) use in learning representations of complex patterns inherent in EEG. Moreover, algorithmic advances in DL facilitate short/zero-calibration in BCI, thereby suppressing the data acquisition phase. Those advancements include data augmentation (DA), increasing the number of training samples without acquiring additional data, and transfer learning (TL), taking advantage of representative knowledge obtained from one dataset to address the so-called data insufficiency problem in other datasets. In this study, we review DL-based short/zero-calibration methods for BCI. Further, we elaborate methodological/algorithmic trends, highlight intriguing approaches in the literature, and discuss directions for further research. In particular, we search forgenerative model-based andgeometric manipulation-based DA methods. Additionally, we categorize TL techniques in DL-based BCIs intoexplicitandimplicitmethods. Our systematization reveals advances in the DA and TL methods. Among the studies reviewed herein, ~45% of DA studies used generative model-based techniques, whereas ~45% of TL studies used explicit knowledge transferring strategy. Moreover, based on our literature review, we recommend an appropriate DA strategy for DL-based BCIs and discuss trends of TLs used in DL-based BCIs. (shrink)

Hacking’s Law of Likelihood says – paraphrasing– that data support hypothesis H1 over hypothesis H2 whenever the likelihood ratio for H1 over H2 exceeds 1. But Hacking noted a seemingly fatal flaw in the LR itself: it cannot be interpreted as the degree of “evidential significance” across applications. I agree with Hacking about the problem, but I don’t believe the condition is incurable. I argue here that the LR can be properly calibrated with respect to the underlying evidence, and I (...) sketch the rudiments of a methodology for so doing. (shrink)

The attribution of beliefs and other propositional attitudes is best understood as a form of measurement, however counter-intuitive this may seem. Measurement theory does not require that the thing measured should be a magnitude, or that the calibration of the measuring instrument should be numerical. It only requires a homomorphism between the represented domain and the representing domain. On this basis, maps measure parts of the world, usually geographical locations, and 'belief' statements measure other parts of the (...) world, namely people's aptitudes. Having outlined an argument for this view, I deal with an obvious objection to it: that self-attribution of belief cannot be an exercise in measurement, because we are all aware, from introspection, that our beliefs have an intrinsically semantic form. Subsequently, I turn to the philosophical and methodological ramifications of the measurement theoretic view. I argue, first, that it undermines at least one version of constructivism and, second, that it provides an effective alternative to the residually Cartesian philosophy that underpins much qualitative research. Like other anti-Cartesian strategies, belief-attribution-as-measurement implies that the objective world is far more knowable than the subjective one, and that reality is ontologically prior to meaning. I regard this result as both plausible and welcome. (shrink)

To measure non-cognitive facets of competence, we developed and tested a new method that we refer to as Embedded Experience Sampling (EES). Domain-specific problem-solving competence is a multi-faceted construct that is not limited to cognitive facets such as domain knowledge or problem-solving strategies but also comprises non-cognitive facets in the sense of domain-specific emotional and motivational dispositions such as interest and self-concept. However, in empirical studies non-cognitive facets are usually either neglected or measured by generalized self-report questionnaires that are detached (...) from the performance assessment. To enable an integrated measurement, we developed the EES method to collect data on non-cognitive facets during scenario-based low-stakes assessments. Test-takers are requested to stop at certain times and spontaneously answer short items (EES items) regarding their actual experience of the problem situation. These EES items are embedded in an EES event that resembles typical social interactions with non-player characters. To evaluate the feasibility and validity of the method, we implemented EES in a series of three studies in the context of commercial vocational education and training (VET): A feasibility study with 77 trainees, a pilot study with 20 trainees, and the main study with 780 trainees who worked on three complex problem scenarios in a computer-based office simulation. In the present paper, we investigate how test-takers perceived the EES events, and whether social desirability biased their answers, and investigate the internal structure of the data and the relationship between EES data and data from several other sources. Interview data and survey data indicated no biases due to social desirability and no additional burden for the test-takers due to the EES events. A correlation analysis following the multitrait-multimethod approach as well as the calibration of a multidimensional model based on Item Response Theory (IRT) also supported the construct validity. Furthermore, EES data shows substantial correlations with test motivation but almost zero correlations with data from generalized retrospective self-report questionnaires on non-cognitive facets. Altogether, EES offers an alternative approach to measuring non-cognitive facets of competence under certain conditions. For instance, EES is also based on self-reporting and thus might not be suitable for high-stakes testing. (shrink)