Deep impact: unintended consequences of journal rank

By Björn Brembs, Marcus Munafò. Frontiers in Human Neuroscience, 2013

373 citations recorded by the source corpus.

Most researchers acknowledge an intrinsic hierarchy in the scholarly journals (“journal rank”) that they submit their work to, and adjust not only their submission but also their reading strategies accordingly. On the other hand, much has been written about the negative effects of institutionalizing journal rank as an impact measure. So far, contributions to the debate concerning the limitations of journal rank as a scientific impact assessment tool have either lacked data, or relied on only a few studies. In this review, we present the most recent and pertinent data on the consequences of our current scholarly communication system with respect to various measures of scientific quality (such as utility/citations, methodological soundness, expert ratings or retractions). These data corroborate previous hypotheses: using journal rank as an assessment tool is bad scientific practice. Moreover, the data lead us to argue that any journal rank (not only the currently-favored Impact Factor) would have this negative impact. Therefore, we suggest that abandoning journals altogether, in favor of a library-based scholarly communication system, will ultimately be necessary. This new system will use modern information technology to vastly improve the filter, sort and discovery functions of the current journal system.

Subfields: Information Systems and Management, Public Health, Environmental and Occupational Health, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9e91f13b18b4012a4bd83de73e6d3ce02d2ccad5

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Citations in the corpus

The natural selection of bad science (2016, background): “…have found that the statistical power of papers published in prestigious (high impact factor) journals is no different from those with lower impact factors (Brembs et al., 2013), while the rate of retractions for journals is positively correlated with impact factor (Fang & Casadevall, 2011).”
How open science helps researchers succeed (2016, background): “The IF is a flawed metric that correlates poorly with the scientific quality of individual articles (Brembs et al., 2013; Neuberger and Counsell, 2002; PLOS Medicine Editors, 2006; Seglen, 1997).”
Excellence or quality? Impact of the current competition regime on science and scientific publishing in Latin America and its implications for development (2014, background): “Finally, those who compete without owning what it takes to win may even seek unacceptable shortcuts: currently, cheating and plagiarizing are on the rise and a recent study disquietingly suggests that the higher the impact factor of a journal, the larger the number of tainted articles that have to b”
The Impact Factor Fallacy (2017, background): “…there is some evidence that the number of citations of an article is influenced by the JIF of the journal where the article was published, regardless of the quality of the article itself (Brembs et al., 2013; Callaham, Wears, & Weber, 2002; Cantrill, 2016; Lozano, Larivière, & Gingras, 2012).”