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Use of the journal impact factor for assessing individual articles: Statistically flawed or not?
Waltman, Ludo; Traag, Vincent A.
Afiliação
  • Waltman L; Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands.
  • Traag VA; Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands.
F1000Res ; 9: 366, 2020.
Article em En | MEDLINE | ID: mdl-33796272
Most scientometricians reject the use of the journal impact factor for assessing individual articles and their authors. The well-known San Francisco Declaration on Research Assessment also strongly objects against this way of using the impact factor. Arguments against the use of the impact factor at the level of individual articles are often based on statistical considerations. The skewness of journal citation distributions typically plays a central role in these arguments. We present a theoretical analysis of statistical arguments against the use of the impact factor at the level of individual articles. Our analysis shows that these arguments do not support the conclusion that the impact factor should not be used for assessing individual articles. Using computer simulations, we demonstrate that under certain conditions the number of citations an article has received is a more accurate indicator of the value of the article than the impact factor. However, under other conditions, the impact factor is a more accurate indicator. It is important to critically discuss the dominant role of the impact factor in research evaluations, but the discussion should not be based on misplaced statistical arguments. Instead, the primary focus should be on the socio-technical implications of the use of the impact factor.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bibliometria / Interpretação Estatística de Dados / Fator de Impacto de Revistas Tipo de estudo: Prognostic_studies Idioma: En Revista: F1000Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bibliometria / Interpretação Estatística de Dados / Fator de Impacto de Revistas Tipo de estudo: Prognostic_studies Idioma: En Revista: F1000Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Holanda