基于百分比的作者贡献指数:衡量作者对科学文章贡献的通用指标。

IF 7.2 Q1 ETHICS Research integrity and peer review Pub Date : 2017-11-03 eCollection Date: 2017-01-01 DOI:10.1186/s41073-017-0042-y
Stéphane Boyer, Takayoshi Ikeda, Marie-Caroline Lefort, Jagoba Malumbres-Olarte, Jason M Schmidt
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摘要

背景:破解科学论文中不同共同作者的工作量一直是科学界反复出现的问题。尽管有无数的衡量标准,但科学界在很大程度上仍然依赖于作者列表中的位置来评估贡献,这种衡量标准将主观和无根据的功劳归于共同作者。我们提出了一个易于应用、具有普遍可比性和公平性的指标来衡量和报告科学文献中共同作者的贡献:建议的作者贡献指数(ACI)基于作者提供的贡献百分比,最好是在投稿时提供。研究人员可以利用 ACI 比较不同作者的贡献,描述特定研究人员的贡献概况,或分析贡献随时间的变化情况。我们根据生态学领域 97 位科学家提供的贡献百分比进行了这样的分析,这些科学家自愿回答了在线匿名调查:ACI 易于理解和实施,因为它完全基于贡献百分比和合著者人数。它提供了一个连续的分数,反映了一位作者的贡献与所有其他作者的平均贡献的比较。例如,ACI(i) = 3 表示作者 i 的贡献是其他作者平均贡献的三倍。我们的分析包括 2014-2016 年发表的 836 篇论文,揭示了 ACI 值与职业发展相关的模式:提出作者贡献指数的例子很多,但没有一个真正被科学期刊采用。许多建议的解决方案要么过于复杂,要么不够准确,要么无法在不同文章、作者和学科之间进行比较。本文提出的作者贡献指数解决了这三个主要问题,有可能提高科学文献的透明度。如果被科学期刊采用,它可以为求职者、招聘者和评估机构提供一种工具,用于收集对他们至关重要的信息,而这些信息是无法通过其他方式轻松准确地获得的。我们还建议,无论期刊是否采用该索引,科学家都应使用它。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Percentage-based Author Contribution Index: a universal measure of author contribution to scientific articles.

Background: Deciphering the amount of work provided by different co-authors of a scientific paper has been a recurrent problem in science. Despite the myriad of metrics available, the scientific community still largely relies on the position in the list of authors to evaluate contributions, a metric that attributes subjective and unfounded credit to co-authors. We propose an easy to apply, universally comparable and fair metric to measure and report co-authors contribution in the scientific literature.

Methods: The proposed Author Contribution Index (ACI) is based on contribution percentages provided by the authors, preferably at the time of submission. Researchers can use ACI to compare the contributions of different authors, describe the contribution profile of a particular researcher or analyse how contribution changes through time. We provide such an analysis based on contribution percentages provided by 97 scientists from the field of ecology who voluntarily responded to an online anonymous survey.

Results: ACI is simple to understand and to implement because it is based solely on percentage contributions and the number of co-authors. It provides a continuous score that reflects the contribution of one author as compared to the average contribution of all other authors. For example, ACI(i) = 3, means that author i contributed three times more than what the other authors contributed on average. Our analysis comprised 836 papers published in 2014-2016 and revealed patterns of ACI values that relate to career advancement.

Conclusion: There are many examples of author contribution indices that have been proposed but none has really been adopted by scientific journals. Many of the proposed solutions are either too complicated, not accurate enough or not comparable across articles, authors and disciplines. The author contribution index presented here addresses these three major issues and has the potential to contribute to more transparency in the science literature. If adopted by scientific journals, it could provide job seekers, recruiters and evaluating bodies with a tool to gather information that is essential to them and cannot be easily and accurately obtained otherwise. We also suggest that scientists use the index regardless of whether it is implemented by journals or not.

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