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<p>Quantitative indicators are used in environmental systems research to assess governance, sustainability, and system performance. However, one common practice remains insufficiently examined: treating Likert-type data as fully quantitative. This paper argues that such treatment produces a form of <i>pseudoquantification</i>. Likert items provide ordinal information. They indicate order but not equal intervals between response categories or a true zero. This makes arithmetic operations such as multiplication, division, and ratio-based interpretation conceptually problematic. Aggregating multiple items into composite scales does not automatically resolve these limitations. Nor does psychometric reliability establish metric legitimacy. Drawing on measurement theory and systems epistemology, the paper shows how this process, termed <i>metric inflation</i>, creates an illusion of precision, amplifies subjective judgments, and obscures uncertainty in indicator-based research. These effects are especially important in environmental governance, where indicators shape policy priorities and institutional evaluation. The paper calls for greater reflexivity in measurement practice and closer alignment between data properties and analytical claims.</p>

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The misuse of Likert data and the illusion of quantification in social and environmental research

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月18日

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  • Sibongiseni Hlabisa

摘要

Quantitative indicators are used in environmental systems research to assess governance, sustainability, and system performance. However, one common practice remains insufficiently examined: treating Likert-type data as fully quantitative. This paper argues that such treatment produces a form of pseudoquantification. Likert items provide ordinal information. They indicate order but not equal intervals between response categories or a true zero. This makes arithmetic operations such as multiplication, division, and ratio-based interpretation conceptually problematic. Aggregating multiple items into composite scales does not automatically resolve these limitations. Nor does psychometric reliability establish metric legitimacy. Drawing on measurement theory and systems epistemology, the paper shows how this process, termed metric inflation, creates an illusion of precision, amplifies subjective judgments, and obscures uncertainty in indicator-based research. These effects are especially important in environmental governance, where indicators shape policy priorities and institutional evaluation. The paper calls for greater reflexivity in measurement practice and closer alignment between data properties and analytical claims.