File uploads: We have fixed an issue which caused file uploads to fail. We apologise for the inconvenience it may have caused.

Published November 15, 2024 | Version v1
Preprint Open

Beyond authorship: Analyzing disciplinary patterns of contribution statements using the CRediT taxonomy

  • 1. University of Granada
  • 2. Wuhan University

Description

In this research article we present the first cross-disciplinary descriptive analysis on 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 2017 and 2024 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.

Notes (English)

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).

Files

Gonzalez-Salmon-Manuscript.pdf

Files (1.5 MB)

Name Size Download all
md5:adc531ea3ac922e2d0bd8fefb62c9c94
1.5 MB Preview Download

Additional details

Related works

Is supplemented by
Dataset: 10.5281/zenodo.14131422 (DOI)

Software

Repository URL
https://github.com/vdicesare/CRediT-Descriptive
Programming language
Python