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Stevan Harnad University of Quebec at Montreal University of Southampton. Open Access and the assessment of research quality. Basic metric types. User (reader)-generated data = USAGE -based metrics Author-generated data = CITATION -based metrics. Rankings (institutions). - PowerPoint PPT Presentation
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Stevan HarnadUniversity of Quebec at MontrealUniversity of Southampton
User (reader)-generated data =
USAGE-based metrics
Author-generated data =
CITATION-based metrics
Academic Ranking of World Universities (“Shanghai” Ranking)
THES World University Ranking G-factor Ranking Webometrics Ranking of World
Universities
Web of Science SCImago
COUNTER statistics (per publisher, per journal, per site)
MESUR (LANL): using SFX logs in CA
On repositories: Citeseer LogEc Google Analytics AWstats IRS
NIPS Workshop linked to this eprint from its web
page
Link placed on “Canonical correlation” page in Wikipedia
Number of articles / other outputs Number of citations h-index (Hirsch) g-index (Egghe) – plus other
modifications of the h-index eigenfactor Y-factor (LANL) Series of weighted indices in a
multiple regression equation (Harnad et al)
Immediacy Latency Decay rate Authority (‘fan in’) Hub (‘fan out’) Co-citation Cited by Citing rank (cites from high-ranking
journals) Semiometrics (semantic distance)
Harnad, 2006, 2007
OAR2008
Sample citation and download growth with time. (Downloads only start in 2005 because that is when this paper was deposited.) Early growth rate and late decay metrics for downloads and citations can also be derived.
Citation-related metrics have in general not yet been systematically face-validated
Benchmarks are still up for grabs N.B. Early citation counts predict
later ones N.B. Download counts predict
citations (even earlier)
RAE 2001: Ranking for psychology departments
OAR2008
Correlation between RAE ratings and mean departmental citations +0.91 (1996) +0.86 (2001) (Psychology)
RAE and citation counting measure broadly the same thing
Citation counting is both more cost-effective and more transparentSource: Eysenck
UK’s RAE 2008 will be a parallel panel/metric exercise
Possible to develop a rich spectrum of candidate metrics
Validate each metric against the panel rankings, discipline by discipline, through multiple regression analysis
Determining and calibrating the weights on each metric
