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Revisiting The 2023 SRI Update: An Empirical Methodology

April 16, 2026

In 2023, the Scholarly Research Index (SRI) underwent a significant methodological update. This work was a collaboration between the Academic Analytics Research Center (AARC) and the Academic Analytics Analyst Team (at the time of this update, the AARC operated as a department within Academic Analytics, prior to our transition into an independent non-profit organization). Director Anthony J. Olejniczak, a key architect of the original index, co-created this version to move the SRI toward an entirely empirical framework. By utilizing factor analysis, the new methodology accounts for the latent relationships between variables rather than relying on static assumptions.

Core Principles of the Index

The SRI is a composite measurement of scholarly output and recognition. It is independently calculated for each academic discipline and expressed as a z-score to enable cross-disciplinary comparisons. Recognizing that different modes of scholarship have different "rhythms" of publication (Olejniczak et al., 2022), the methodology employs variable timeframes for each data element:

  • 4 Years: Articles, Conference Proceedings, and Chapters.

  • 5 Years: Citations (for works published in that window), Clinical Trials, and Grants.

  • 10 Years: Books and Patents.

  • Variable: Awards.

The Order of Operations: Creating the Weighting Scheme

The weighting for the SRI was established through the following sequence:

  • Metric Identification: Relevant metrics were matched to scholars within each specific discipline.

  • Work Type Quantification: The count of unique works was calculated for each faculty member within each work type.

  • Factor Analysis: Statistical factor analysis identified the dominant "factor" while accounting for relationships between variables.

  • Model Selection: Multiple models were created for each discipline, with the "best fit" model selected for the final index.

  • Bimodal Disciplines: For eight disciplines - including Anthropology, Architecture, and Sociology - the complexity of variables required two separate models focusing on articles and books.

  • Weight Transformation: Factor loadings (the extent of a metric's relation to the primary factor) were transformed into percentage weights.

  • Individual Calculation: These weights were applied to individual scholars to create a composite SRI score.

  • Aggregation: Individual scores were averaged to provide mean SRI scores for departments, programs, and universities.

While these default weights provide a robust standard, it is important to reiterate that the SRI measures output and recognition rather than research impact or quality.