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  1. Home
  3. Measuring The Menu, Not The Food: "psychometric" Data May Instead Measure "lingometrics" (and Miss Its Greatest Potential).
  1. Home
  3. Measuring The Menu, Not The Food: "psychometric" Data May Instead Measure "lingometrics" (and Miss Its Greatest Potential).

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Measuring the menu, not the food: "psychometric" data may instead measure "lingometrics" (and miss its greatest

Jan Ketil Arnulf1, Ulf Henning Olsson1, Kim Nimon2

  • 1BI Norwegian Business School, Oslo, Norway.

Frontiers in Psychology
|April 5, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Psychological research may be measuring semantic representations, not actual constructs. This review suggests a shift from nomological to semantic networks, impacting construct validation and empirical truth in psychometrics.

Keywords:
cross-cultural psychologylatent constructsmeasurementnatural language processingnomological networksorganizational behaviorsemantic algorithmssemantic networks

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Area of Science:

  • Psychology
  • Computational Linguistics
  • Psychometrics

Background:

  • Traditional psychometric methods rely on construct validation, often conceptualized within nomological networks.
  • Empirical studies using digital text algorithms analyze human responses to Likert-scale items.

Purpose of the Study:

  • To review empirical studies using text algorithms to model human responses to Likert-scale items.
  • To investigate the predictability of construct validation statistics across different levels and cultures.
  • To propose a shift from nomological networks to semantic networks in understanding psychological constructs.

Main Methods:

  • Review of empirical studies employing digital text algorithms.
  • Analysis of response patterns to Likert-scale items using text as input.
  • Examination of statistical predictability in construct validation.

    • Main Results:

    • Construct validation statistics are predictable at both sample and individual levels, across languages and cultures.
    • Relationships between variables are often semantic and a priori computable, rather than strictly empirical.
    • Psychological research consistently shows an average explained variance of 42%.

    Conclusions:

    • Human semantic processing is fast and intersubjectively consistent.
    • A categorical error exists in psychometrics, measuring representations instead of the represented.
    • The findings have significant implications for the empirical truth of traditional psychometric research.