A structural interpretation of measurement and some related epistemological issues

Mari, Luca; Carbone, Paolo; Giordani, Alessandro; Petri, Dario

doi:10.1016/j.shpsa.2017.08.001

Cited by 31 publications

(64 citation statements)

References 18 publications

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“…1). But RTM did not resonate with psychometricians, partly because it seemed so far removed from empirical applications (Cliff [1992]; Luce [1997]; see also Mari et al [2017]; Reiss [2008]). Thus psychometrics carried on largely unaffected by mathematical theories of measurement, and RTM found its allies in economics, where proving representation and uniqueness theorems is part and parcel of measurement practice.…”

Section: Representational Interpretabilitymentioning

confidence: 99%

“…By contrast, a proponent of the present interpretation of RTM need not get entangled in that thorny debate. Hence there are both correctness-and expediencyrelated reasons to focus our attention to the implications of the present take on RTM, which, as the Complementarity Claim shows, has much more practical utility than RTM is typically credited for (Mari et al [2017]; Boumans [2016]; Reiss [2008]).…”

Section: Rasch and Conjoint Measurementmentioning

confidence: 99%

“…6 (Suppes and Zinnes [1963], p. 3). 7 (Mari et al [2017]; Boumans [2016]; Reiss [2008], chapter 4). 8 For example (Krantz et al [1971], p. 9; Luce and Tukey [1964]).…”

Section: Introductionmentioning

confidence: 99%

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The Complementarity of Psychometrics and the Representational Theory of Measurement

Vessonen¹

2020

The British Journal for the Philosophy of Science

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Psychometrics and the representational theory of measurement (RTM) 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

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Section: Representational Interpretabilitymentioning

confidence: 99%

Section: Rasch and Conjoint Measurementmentioning

confidence: 99%

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The Complementarity of Psychometrics and the Representational Theory of Measurement

Vessonen¹

2020

The British Journal for the Philosophy of Science

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“…Note that species delimitation using the Tobias criterion has all the components by which metrologists and philosophers of measurement typically define measurement (Cartwright et al 2011;Tal 2013;Mari et al 2017). Most obviously, there is a clearly defined set of objects (i.e.…”

Section: Evolutionary Independence Measurement and The Tobias Criterionmentioning

confidence: 99%

Measuring evolutionary independence: A pragmatic approach to species classification

Conix

2019

Biol Philos

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After decades of debates about species concepts, there is broad agreement that species are evolving lineages. However, species classification is still in a state of disorder: different methods of delimitation lead to competing outcomes for the same organisms, and the groups recognised as species are of widely different kinds. This paper considers whether this problem can be resolved by developing a unitary scale for evolutionary independence. Such a scale would show clearly when groups are comparable and allow taxonomists to choose a conventional threshold of independence for species status. Existing measurement approaches to species delimitation are typically shot down by what I call the heterogeneity objection, according to which independently evolving groups are too heterogeneous to be captured by a single scale. I draw a parallel with the measurement of temperature to argue that this objection does not provide sufficient reasons to abandon the measurement approach, and that such an approach may even help to make the vague notion of evolutionary independence more precise.

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“…Quantification denotes the assignment of numerical values; measurement is a purposeful multi-step process, comprising operative structures for making such assignments in reliable, valid and explicitly justified ways. Thus, measurement defines a process structure, quantification its result (Mari et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Measurement in metrology, psychology and social sciences: data generation traceability and numerical traceability as basic methodological principles applicable across sciences

Uher

2020

Qual Quant

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Measurement creates trustworthy quantifications. But unified frameworks applicable to all sciences are still lacking and discipline-specific terms, concepts and practices hamper mutual understanding and identification of commonalities and differences. Transdisciplinary and philosophy-of-science analyses are used to compare metrologists' structural framework of physical measurement with psychologists' and social scientists' fiat measurement of constructs. The analyses explore the functions that measuring instruments and measurement-executing persons in themselves fulfil in data generation processes, and identify two basic methodological principles critical for measurement. (1) Data generation traceability requires that numerical assignments depend on the properties to be quantified in the study objects (object-dependence). Therefore, scientists must establish unbroken documented connection chains that directly link (via different steps) the quantitative entity to be measured in the study property with the numerical value assigned to it, thereby making the assignment process fully transparent, traceable and thus reproducible. (2) Numerical traceability requires that scientists also directly link the assigned numerical value to known standards in documented and transparent ways, thereby establishing the results' public interpretability (subject-independence). The article demonstrates how these principles can be meaningfully applied to psychical and social phenomena, considering their peculiarities and inherent limitations, revealing that not constructs in themselves but only their indicators (proxies) can be measured. These foundational concepts allow to distinguish measurement-based quantifications from other (subjective) quantifications that may be useful for pragmatic purposes but lack epistemic authority, which is particularly important for applied (e.g., legal, clinical) contexts. They also highlight new avenues for establishing transparency and replicability in empirical sciences.

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A structural interpretation of measurement and some related epistemological issues

Cited by 31 publications

References 18 publications

The Complementarity of Psychometrics and the Representational Theory of Measurement

The Complementarity of Psychometrics and the Representational Theory of Measurement

Measuring evolutionary independence: A pragmatic approach to species classification

Measurement in metrology, psychology and social sciences: data generation traceability and numerical traceability as basic methodological principles applicable across sciences

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