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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Supplementary material of the manuscript "Beyond authorship: Analyzing disciplinary patterns of contribution statements using the CRediT taxonomy"

Authors: González-Salmón, Elvira; Di Césare, Victoria; Xiao, Aoxia; Robinson-Garcia, Nicolas;

Supplementary material of the manuscript "Beyond authorship: Analyzing disciplinary patterns of contribution statements using the CRediT taxonomy"

Abstract

Supplementary material of the manuscript "Beyond authorship: Analyzing disciplinary patterns of contribution statements using the CRediT taxonomy". In this research article, we present the first cross-disciplinary descriptive analysis of the use of contribution statements. Our main objective is to obtain further insight on contributions by a variety of fields (Multidisciplinary, Health, Life, Physical, and Social Sciences) from the largest dataset used up to now. We examine more than 700,000 articles published between 2018 and 2023 in Elsevier and PLOS journals, in combination with bibliometric data extracted from the Scopus database. The descriptive analysis of the dataset focuses on the overall coverage of the merged data, the distribution of authorship and disciplines at paper level, and the interactions between contribution statements, author order, and disciplines. Our two main findings indicate that, on the one hand, looking at contributions and authorship order can enrich the way we understand science as a social endeavor. On the other hand, delving deeper into contributorship differences by field is key. We underscore the value of the CRediT taxonomy in unveiling nuanced research dynamics and offering a more equitable framework for evaluation.

This paper is part of the COMPARE project (Ref: PID2020-117007RA-I00) funded by the Spanish Ministry of Science (Ref: MCIN/AEI/10.13039/501100011033 FSE invierte en tu futuro). Elvira González-Salmón is currently supported by an FPU grant from the Spanish Ministry of Science (Ref: FPU2021/02320). Victoria Di Césare is supported by a FPI grant from the Spanish Ministry of Science (Ref: PRE2021-097022). Aoxia Xiao is supported by a scholarship by from the China State Scholarship Fund. Nicolas Robinson-Garcia is supported by a Ramón y Cajal grant from the Spanish Ministry of Science (Ref: RYC2019-027886-I).

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Keywords

Contributorship, CRediT taxonomy, Contribution statements, Division of labor, CRediT, Authorship

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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