Dix, Alan (2016) Evaluating research assessment: metrics-based analysis exposes implicit bias in REF2014 results. Impact of Social Sciences Blog (22 Mar 2016). Website.
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Abstract
The recent UK research assessment exercise, REF2014, attempted to be as fair and transparent as possible. However, Alan Dix, a member of the computing sub-panel, reports how a post-hoc analysis of public domain REF data reveals substantial implicit and emergent bias in terms of discipline sub-areas (theoretical vs applied), institutions (Russell Group vs post-1992), and gender. While metrics are generally recognised as flawed, our human processes may be uniformly worse.
| Item Type: | Online resource (Website) |
|---|---|
| Official URL: | http://blogs.lse.ac.uk/impactofsocialsciences/ |
| Additional Information: | © 2016 LSE Impact of Social Sciences © CC BY 3.0 |
| Divisions: | LSE |
| Subjects: | H Social Sciences > HC Economic History and Conditions Q Science > QA Mathematics |
| Date Deposited: | 31 May 2016 07:44 |
| Last Modified: | 11 Dec 2024 14:51 |
| URI: | http://eprints.lse.ac.uk/id/eprint/66679 |
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