Journal of Data and Information Science ›› 2023, Vol. 8 ›› Issue (1): 9-20.doi: 10.2478/jdis-2023-0004

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Is big team research fair in national research assessments? The case of the UK Research Excellence Framework 2021

Mike Thelwall(), Kayvan Kousha, Meiko Makita, Mahshid Abdoli, Emma Stuart, Paul Wilson, Jonathan Levitt   

  1. Statistical Cybermetrics and Research Evaluation Group, University of Wolverhampton, UK.
  • Received:2022-12-11 Revised:2023-02-07 Accepted:2023-02-08 Online:2023-02-20 Published:2023-02-22
  • Contact: Mike Thelwall (Email:; ORCID: 0000-0001-6065-205X).


Collaborative research causes problems for research assessments because of the difficulty in fairly crediting its authors. Whilst splitting the rewards for an article amongst its authors has the greatest surface-level fairness, many important evaluations assign full credit to each author, irrespective of team size. The underlying rationales for this are labour reduction and the need to incentivise collaborative work because it is necessary to solve many important societal problems. This article assesses whether full counting changes results compared to fractional counting in the case of the UK's Research Excellence Framework (REF) 2021. For this assessment, fractional counting reduces the number of journal articles to as little as 10% of the full counting value, depending on the Unit of Assessment (UoA). Despite this large difference, allocating an overall grade point average (GPA) based on full counting or fractional counting gives results with a median Pearson correlation within UoAs of 0.98. The largest changes are for Archaeology (r=0.84) and Physics (r=0.88). There is a weak tendency for higher scoring institutions to lose from fractional counting, with the loss being statistically significant in 5 of the 34 UoAs. Thus, whilst the apparent over-weighting of contributions to collaboratively authored outputs does not seem too problematic from a fairness perspective overall, it may be worth examining in the few UoAs in which it makes the most difference.

Key words: Collaboration, Research assessment, REF, REF2021, Research quality, Scientometrics