Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
110 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Predicting results of the Research Excellence Framework using departmental $h$-Index (1411.1996v2)

Published 7 Nov 2014 in cs.DL and physics.soc-ph

Abstract: We compare estimates for past institutional research performances coming from two bibliometric indicators to the results of the UK's Research Assessment Exercise which last took place in 2008. We demonstrate that a version of the departmental h-index is better correlated with the actual results of that peer-review exercise than a competing metric known as the normalised citation-based indicator. We then determine the corresponding h-indices for 2008-2013, the period examined in the UK's Research Excellence Framework (REF) 2014. We place herewith the resulting predictions on the arXiv in advance of the REF results being published (December 2014). These may be considered as unbiased predictions of relative performances in that exercise. We will revisit this paper after the REF results are available and comment on the reliability or otherwise of these bibliometrics as compared with peer review.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (4)
  1. Olesya Mryglod (14 papers)
  2. Ralph Kenna (49 papers)
  3. Yurij Holovatch (44 papers)
  4. Bertrand Berche (62 papers)
Citations (35)

Summary

We haven't generated a summary for this paper yet.