Dix, A: Citations and Sub-Area Bias in the UK Research Assessment Process

Abstract: This paper presents a citation-based analysis of selected results of REF2014, the periodic UK research assessment process. Data for the Computer Science and Informatics sub-panel includes ACM topic sub-area information, allowing a level of analysis hitherto impossible. While every effort is made during the REF process to be fair, the results suggest systematic latent bias may have emerged between sub-areas. Furthermore this may have had a systematic effect benefiting some institutions relative to others, and potentially also introducing gender bias. Metric-based analysis could in future be used as part of the human-assessment process to uncover and help eradicate latent bias.

License: Creative Commons Attribution 4.0 International (CC-BY 4.0)

File: ASCW15_dix-citations-and-sub-areas-bias-in-the-uk-research-assessment-process.pdf

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