Measures for Impact, Consistency and the h- and g-indices

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DC Field	Value	Language
dc.contributor.author	Gangan Prathap	-
dc.date.accessioned	2016-09-20T11:16:02Z	-
dc.date.available	2016-09-20T11:16:02Z	-
dc.date.issued	2014-05	-
dc.identifier.citation	Journal of the Association for Information Science and Technology, 65(5):1076-1078	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/2452	-
dc.description.abstract	An altogether different view on the properties of a good performance measure than that given in Egghe (2012) is offered. Egghe argued that a good impact measure should reward nonconsistency; that is, the more citations over papers are unequally distributed, the higher the impact should be. Here, a quantitative proxy for consistency is offered, and it is shown that as consistency increases, the ideal performance measure, which is sensitive to changes in consistency, should increase, reflecting this virtue.	en_US
dc.language.iso	en	en_US
dc.publisher	Wiley Online Library	en_US
dc.title	Measures for Impact, Consistency and the h- and g-indices	en_US
dc.type	Article	en_US
Appears in Collections:	2014

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