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

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  • Jana Uher

    (University of Greenwich, Old Royal Naval College
    London School of Economics and Political Science)

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.

Suggested Citation

  • Jana Uher, 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, Springer, vol. 54(3), pages 975-1004, June.
    • Handle: RePEc:spr:qualqt:v:54:y:2020:i:3:d:10.1007_s11135-020-00970-2
    DOI: 10.1007/s11135-020-00970-2
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    References listed on IDEAS

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    1. Daniel L. Schacter & Donna Rose Addis, 2007. "The ghosts of past and future," Nature, Nature, vol. 445(7123), pages 27-27, January.
    2. Jana Uher, 2019. "Data generation methods across the empirical sciences: differences in the study phenomena’s accessibility and the processes of data encoding," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 221-246, January.
    3. Oakes, J. Michael & Rossi, Peter H., 2003. "The measurement of SES in health research: current practice and steps toward a new approach," Social Science & Medicine, Elsevier, vol. 56(4), pages 769-784, February.
    4. David Thissen, 2001. "Psychometric engineering as art," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 473-485, December.
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    Cited by:

    1. Jana Uher, 2022. "Functions of units, scales and quantitative data: Fundamental differences in numerical traceability between sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2519-2548, August.

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