Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved]
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...
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doaj-aed594d61e5e4d818e1f8525405064232021-03-24T13:11:57ZengF1000 Research LtdF1000Research2046-14022021-03-01910.12688/f1000research.23418.254872Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved]Ludo Waltman0Vincent A. Traag1Centre for Science and Technology Studies, Leiden University, Leiden, The NetherlandsCentre for Science and Technology Studies, Leiden University, Leiden, The NetherlandsMost 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.https://f1000research.com/articles/9-366/v2 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ludo Waltman Vincent A. Traag |
spellingShingle |
Ludo Waltman Vincent A. Traag Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved] F1000Research |
author_facet |
Ludo Waltman Vincent A. Traag |
author_sort |
Ludo Waltman |
title |
Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved] |
title_short |
Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved] |
title_full |
Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved] |
title_fullStr |
Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved] |
title_full_unstemmed |
Use of the journal impact factor for assessing individual articles: Statistically flawed or not? [version 2; peer review: 2 approved] |
title_sort |
use of the journal impact factor for assessing individual articles: statistically flawed or not? [version 2; peer review: 2 approved] |
publisher |
F1000 Research Ltd |
series |
F1000Research |
issn |
2046-1402 |
publishDate |
2021-03-01 |
description |
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. |
url |
https://f1000research.com/articles/9-366/v2 |
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