Using quantitative metrics to assess researchers is often seen as a poor choice compared with using qualitative assessments. In this Perspective, the authors argue in favor of using rigorous, field-adjusted, centralized, quantitative metrics in a bid to help improve research practices as a low-cost public good.

Data is powerful because it’s universal. The cost is context. Policymakers want to make decisions based on clear data, but important factors are lost when we rely solely on data.

Nguyen, C. Thi. “The Limits of Data.” Issues in Science and Technology 40, no. 2 (Winter 2024): 94–101. https://doi.org/10.58875/LUXD6515

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