Researchers’ Perceptions of Ethical Authorship Distribution in Collaborative Research Teams is a research paper published in Science and Engineering Ethics (2019). On theSindex it has a DataRank of 2.2. It has been cited 67 times, with 64 citing works in its 1-hop citation network.
Authorship is commonly used as the basis for the measurement of research productivity. It influences career progression and rewards, making it a valued commodity in a competitive scientific environment. To better understand authorship practices amongst collaborative teams, this study surveyed authors on collaborative journal articles published between 2011 and 2015. Of the 8364 respondents, 1408 responded to the final open-ended question, which solicited additional comments or remarks regarding the fair distribution of authorship in research teams. This paper presents the analysis of these comments, categorized into four main themes: (1) disagreements, (2) questionable behavior, (3) external influences regarding authorship, and (4) values promoted by researchers. Results suggest that some respondents find ways to effectively manage disagreements in a collegial fashion. Conversely, others explain how distribution of authorship can become a "blood sport" or a "horror story" which can negatively affect researchers' wellbeing, scientific productivity and integrity. Researchers fear authorship discussions and often try to avoid openly discussing the situation which can strain team interactions. Unethical conduct is more likely to result from deceit, favoritism, and questionable mentorship and may become more egregious when there is constant bullying and discrimination. Although values of collegiality, transparency and fairness were promoted by researchers, rank and need for success often overpowered ethical decision-making. This research provides new insight into contextual specificities related to fair authorship distribution that can be instrumental in developing applicable training tools to identify, prevent, and mitigate authorship disagreement.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.633
From this paper's citation signal
Citation Network Contribution
1.6
From 40 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 28% comes from its base citations and 72% from the citation network (40 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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