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4篇 您的检索式：作者名="Jonathan Levitt"

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		题名	作者	年代	出处	被引量
	1	Parenchymal Echo Texture Predicts Testicular Salvage After Torsion: Potential Impact on the Need for Emergent Exploration显示文摘	Jonathan D. Kaye Edan Y. Shapiro Selwyn B. Levitt Steven C. Friedman Jordan Gitlin Jaime Freyle Lane S. Palmer	2008	The Journal of Urology2008，，4：	1
	2	Citation Levels and Collaboration Within Library and Information Science显示文摘	Jonathan M Levitt Mike Thelwall	2009	Journal of the American Society for Information Science and Technology2009，60，3：	1
	3	The most highly cited Library and Information Science articles: Interdisciplinarity, first authors and citation patterns显示文摘	Jonathan M. Levitt Mike Thelwall	2009	Scientometrics2009，，1：	1
	4	Is big team research fair in national research assessments? The case of the UK Research Excellence Framework 2021显示文摘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.	Mike Thelwall Kayvan Kousha Meiko Makita Mahshid Abdoli Emma Stuart Paul Wilson Jonathan Levitt	2023	Journal of Data and Information Science2023，8，1：	0

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