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<p>Construct proliferation poses significant challenges for cumulative science in organizational psychology. This article explores how natural language can be used to evaluate construct clarity by introducing an integrated approach combining content and semantic overlap using meaningful work measurement as a case study. Across two studies, we find evidence that measures of meaningful work sample different psychological content areas (i.e., within-construct heterogeneity or a jingle fallacy). Content overlap analysis identified 31 unique content areas captured by the measures, providing an initial taxonomy of meaningful work content, with only 36% of scales reaching the weak overlap threshold. Embedding-based semantic similarity analysis found that only 38% of measures reach the somewhat similar cutoff. Integrating these approaches, we classified only 16% of scale-pair comparisons as converging around a content space, with the remainder being at risk of Jingle and Jangle (44%) or sampling distinct spaces altogether (40%). This work provides further evidence for using natural language to evaluate the conceptual clarity of organizational constructs.</p>

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Using Natural Language for Conceptual Clarity in Organizational Measurement: A Case of the Many Meanings of Meaningful Work

  • 期刊论文

  • 发表日期：

    2026年6月16日

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  • Andrew Samo,
  • Scott Highhouse

摘要

Construct proliferation poses significant challenges for cumulative science in organizational psychology. This article explores how natural language can be used to evaluate construct clarity by introducing an integrated approach combining content and semantic overlap using meaningful work measurement as a case study. Across two studies, we find evidence that measures of meaningful work sample different psychological content areas (i.e., within-construct heterogeneity or a jingle fallacy). Content overlap analysis identified 31 unique content areas captured by the measures, providing an initial taxonomy of meaningful work content, with only 36% of scales reaching the weak overlap threshold. Embedding-based semantic similarity analysis found that only 38% of measures reach the somewhat similar cutoff. Integrating these approaches, we classified only 16% of scale-pair comparisons as converging around a content space, with the remainder being at risk of Jingle and Jangle (44%) or sampling distinct spaces altogether (40%). This work provides further evidence for using natural language to evaluate the conceptual clarity of organizational constructs.