Author Index
Ontology highlight
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PROVIDER: S-EPMC8414987 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
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Project description:BackgroundDeciphering 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.MethodsThe 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.ResultsACI 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.ConclusionThere 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.
| S-EPMC5803580 | biostudies-literature
Project description:BackgroundBibliometric analyses show gender bias against women in scientific publications and citations. We hypothesized that a metric of an individual senior author's inclusivity of women as first authors in critical care publications would predict gender inequality.MethodsUsing PubMed and Web of Science, we conducted a bibliometric analysis of original research publications in critical care from 2008 to 2018 in 11 specialty and general journals. Gender for first and senior authors was assigned by a gender determination application, and manually if needed. For all senior authors we defined the novel Female First Author Index (FFA-index) = #Female first authors in publications by an individual senior author/Total # publications by that senior author. We produced a novel interactive web-based application using the R package Shiny to increase potential utilization of the FFA-index.ResultsOf 7370 publications, 30.4% had female first authors and 15.5% had female senior authors. After adjustment for impact factor, journal, year of publication, number of authors, country, and gender determination accuracy, female senior authorship was associated with a 1.9-fold increase in female first authorship [OR = 1.85 (95% CI 1.62, 2.11); p < 0.001] compared with male senior authorship. The mean (SD) FFA-index for all individual senior authors was 30.5 (42.9); with a significant difference in FFA-index between male and female senior authors (27.6 versus 42.5, respectively; p < 0.001). The interactive web-based application (FFA-index App) produces the same FFA-index output as our study results.ConclusionsFemale representation at prominent authorship positions in critical care publications is still far from achieving gender parity. By creating an authorship index score, we propose a frame of reference for the advancement of female first authorship.
| S-EPMC8253865 | biostudies-literature
Project description: Not available
| S-EPMC8578204 | biostudies-literature
Project description:Author-level metrics are a widely used measure of scientific success. The h-index and its variants measure publication output (number of publications) and research impact (number of citations). They are often used to influence decisions, such as allocating funding or jobs. Here, we argue that the emphasis on publication output and impact hinders scientific progress in the fields of ecology and evolution because it disincentivizes two fundamental practices: generating impactful (and therefore often long-term) datasets and sharing data. We describe a new author-level metric, the data-index, which values both dataset output (number of datasets) and impact (number of data-index citations), so promotes generating and sharing data as a result. We discuss how it could be implemented and provide user guidelines. The data-index is designed to complement other metrics of scientific success, as scientific contributions are diverse and our value system should reflect that both for the benefit of scientific progress and to create a value system that is more equitable, diverse, and inclusive. Future work should focus on promoting other scientific contributions, such as communicating science, informing policy, mentoring other scientists, and providing open-access code and tools.
| S-EPMC8571609 | biostudies-literature
Project description:BackgroundThe aims of this bibliometric study were to determine author self-citation trends in high-impact orthodontic literature and to investigate possible association between self-citation and publication characteristics.MethodsSix orthodontic journals with the highest impact factor as ranked by 2017 Journal Citation Reports were screened for a full publication year (2018) for original research articles, reviews, and case reports. Eligible articles were scrutinized for article and author characteristics and citation metrics. Univariable and multivariable negative binomial regression was used to examine associations between self-citation incidence and publication characteristics.ResultsMedians for author self-citation rate of the most self-citing authors and self-citations were 3.03% (range 0-50) and 1 (range 0-19), respectively. In the univariable analysis, there was no association between self-citation counts and study type (P = 0.41), article topic (P = 0.61), number of authors (P = 0.62), and rank of authors (P = 0.56). Author origin (P = 0.001), gender (P = 0.001) and journal (P = 0.05) were associated with self-citation counts and in the multivariable analysis only origin and gender remained strong self-citation predictors. Asian authors and females self-cited significantly less often than all other regions and male authors.ConclusionsAuthors in orthodontics do not self-cite at a frequency that suggests potential citation manipulation. Author origin and gender were the only variables associated with citations counts. More bibliometric research is necessary to draw solid conclusions about author self-citation trends in orthodontic literature.
| S-EPMC7788150 | biostudies-literature