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

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

Uher, Jana ORCID: 0000-0003-2450-4943 (2020) Measurement in metrology, psychology and social sciences: data generation traceability and numerical traceability as basic methodological principles applicable across sciences. Quality & Quantity: International Journal of Methodology, 54. pp. 975-1004. ISSN 0033-5177 (Print), 1573-7845 (Online) (doi:https://doi.org/10.1007/s11135-020-00970-2)

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Abstract

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.

Item Type: Article
Additional Information: © The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Uncontrolled Keywords: Measurement; Constructs; Psychometrics; Quantitative methods; Replicability; Traceability
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Faculty / Department / Research Group: Faculty of Education, Health & Human Sciences
Faculty of Education, Health & Human Sciences > Department of Psychology, Social Work & Counselling
Related URLs:
Last Modified: 10 May 2020 21:00
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/26855

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