The extent and drivers of gender imbalance in neuroscience reference lists

Authors : Jordan D. Dworkin, Kristin A. Linn, Erin G. Teich, Perry Zurn, Russell T. Shinohara, Danielle S. Bassett

Like many scientific disciplines, neuroscience has increasingly attempted to confront pervasive gender imbalances within the field. While much of the conversation has centered around publishing and conference participation, recent research in other fields has called attention to the prevalence of gender bias in citation practices.

Because of the downstream effects that citations can have on visibility and career advancement, understanding and eliminating gender bias in citation practices is vital for addressing inequity in a scientific community. In this study, we sought to determine whether there is evidence of gender bias in the citation practices of neuroscientists.

Utilizing data from five top neuroscience journals, we indeed find that reference lists tend to include more papers with men as first and last author than would be expected if gender was not a factor in referencing. Importantly, we show that this overcitation of men and undercitation of women is driven largely by the citation practices of men, and is increasing with time despite greater diversity in the academy.

We develop a co-authorship network to determine the degree to which homophily in researchers’ social networks explains gendered citation practices and we find that men tend to overcite other men even when their social networks are representative of the field.

We discuss possible mechanisms and consider how individual researchers might incorporate these findings into their own referencing practices.

DOI : https://doi.org/10.1101/2020.01.03.894378

Altmetrics and societal impact measurements: Match or mismatch? A literature review

Authors : Iman Tahamtan, Lutz Bornmann

Can alternative metrics (altmetrics) data be used to measure societal impact? We wrote this literature overview of empirical studies in order to find an answer to this question. The overview includes two parts.

The first part, “societal impact measurements”, explains possible methods and problems in measuring the societal impact of research, case studies for societal impact measurement, societal impact considerations at funding organizations, and the societal problems that should be solved by science.

The second part of the review, “altmetrics”, addresses a major question in research evaluation, which is whether altmetrics are proper indicators for measuring the societal impact of research. In the second part we explain the data sources used for altmetrics studies and the importance of field-normalized indicators for impact measurements.

This review indicates that it should be relevant for impact measurements to be oriented towards pressing societal problems. Case studies in which societal impact of certain pieces of research is explained seem to provide a legitimate method for measuring societal impact.

In the use of altmetrics, field-specific differences should be considered by applying field normalization (in cross-field comparisons). Altmetrics data such as social media counts might mainly reflect the public interest and discussion of scholarly works rather than their societal impact.

Altmetrics (Twitter data) might be especially fruitfully employed for research evaluation purposes, if they are used in the context of network approaches. Conclusions based on altmetrics data in research evaluation should be drawn with caution.

URL : Altmetrics and societal impact measurements: Match or mismatch? A literature review

Original location : https://recyt.fecyt.es/index.php/EPI/article/view/epi.2020.ene.02

Inferring the causal effect of journals on citations

Author : Vincent Traag

Articles in high-impact journals are by definition more highly cited on average. But are they cited more often because the articles are somehow “better”? Or are they cited more often simply because they appeared in a high-impact journal? Although some evidence suggests the latter the causal relationship is not clear.

We here compare citations of published journal articles to citations of their preprint versions to uncover the causal mechanism. We build on an earlier model to infer the causal effect of journals on citations. We find evidence for both effects.

We show that high-impact journals seem to select articles that tend to attract more citations. At the same time, we find that high-impact journals augment the citation rate of published articles.

Our results yield a deeper understanding of the role of journals in the research system. The use of journal metrics in research evaluation has been increasingly criticised in recent years and article-level citations are sometimes suggested as an alternative.

Our results show that removing impact factors from evaluation does not negate the influence of journals. This insight has important implications for changing practices of research evaluation.

URL : https://arxiv.org/abs/1912.08648

Connecting Users to Articles: An Analysis of the Impact of Article Level Linking on Journal Use Statistics

Author : Michelle Swab

Objective

Electronic resource management challenges and “big deal” cancellations at one Canadian university library contributed to a situation where a number of electronic journal subscriptions at the university’s health sciences library lacked article level linking.

The aim of this study was to compare the usage of journals with article level linking enabled to journals where only journal level linking was available or enabled.

Methods

A list of electronic journal title subscriptions was generated from vendor and subscription agent invoices. Journal titles were eligible for inclusion if the subscription was available throughout 2018 on the publisher’s platform, if the subscription costs were fully funded by the health sciences library, and if management of the subscription required title-by-title intervention by library staff. Of the 356 journal titles considered, 302 were included in the study.

Negative binomial regression was performed to determine the effect of journal vs. article level linking on total COUNTER Journal Report 1 (JR1) successful full-text article requests for 2018, controlling for journal publisher, subject area, journal ranking, and alternate aggregator access.

Results

The negative binomial regression model demonstrated that article level linking had a significant, positive effect on total 2018 JR1 (coef: 0.645; p < 0.001). Article level linking increased the expected total JR1 by 90.7% when compared to journals where article level linking was not available or enabled.

Differences in predicted usage between journals with article level linking and those without article level linking remained significant at various journal ranking levels.

This suggests that usage of both smaller, more specialized journals (e.g., Journal of Vascular Research) and larger, general journals (e.g., New England Journal of Medicine) increases when article level linking is enabled.

Conclusions

This study provides statistical evidence that enabling article level linking has a positive impact on journal usage at one academic health sciences library. Although further study is needed, academic libraries should consider enabling article level linking wherever possible in order to facilitate user access, maximize the value of journal subscriptions, and improve convenience for users.

URL : Connecting Users to Articles: An Analysis of the Impact of Article Level Linking on Journal Use Statistics

DOI : https://doi.org/10.18438/eblip29613

The Open-Factor: Toward Impact-Aligned Measures of Open-Access eBook Usage

Author : E. S. Hellman

A statistical analysis of usage data for open-access ebooks from two different publishers and from a free ebook distribution platform indicates that open-access ebook usage is distributed following log-normal statistics, and meaningful analysis results after calculating the logarithm of the download counts.

To assess usage impact from raw usage data in alignment with the goals of open-access ebook publishing, future impact analyses should use logarithm-based metrics to measure an “open-factor”.

DOI : http://dx.doi.org/10.3998/3336451.0022.104

Does Monetary Support Increase Citation Impact of Scholarly Papers?

Authors : Yasar Tonta, Muge Akbulut

One of the main indicators of scientific development of a given country is the number of papers published in high impact scholarly journals. Many countries introduced performance-based research funding systems (PRFSs) to create a more competitive environment where prolific researchers get rewarded with subsidies to increase both the quantity and quality of papers.

Yet, subsidies do not always function as a leverage to improve the citation impact of scholarly papers. This paper investigates the effect of the publication support system of Turkey (TR) on the citation impact of papers authored by Turkish researchers.

Based on a stratified probabilistic sample of 4,521 TR-addressed papers, it compares the number of citations to determine if supported papers were cited more often than those of not supported ones, and if they were published in journals with relatively higher citation impact in terms of journal impact factors, article influence scores and quartiles.

Both supported and not supported papers received comparable number of citations per paper, and were published in journals with similar citation impact values. Findings suggest that subsidies do not seem to be an effective incentive to improve the quality of scholarly papers. Such support programs should therefore be reconsidered.

URL : https://arxiv.org/abs/1909.10068

How much research shared on Facebook is hidden from public view? A comparison of public and private online activity around PLOS ONE papers

Authors : Asura Enkhbayar, Stefanie Haustein, Germana Barata, Juan Pablo Alperin

Despite its undisputed position as the biggest social media platform, Facebook has never entered the main stage of altmetrics research. In this study, we argue that the lack of attention by altmetrics researchers is not due to a lack of relevant activity on the platform, but because of the challenges in collecting Facebook data have been limited to activity that takes place in a select group of public pages and groups.

We present a new method of collecting shares, reactions, and comments across the platform-including private timelines-and use it to gather data for all articles published between 2015 to 2017 in the journal PLOS ONE.

We compare the gathered data with altmetrics collected and aggregated by Altmetric. The results show that 58.7% of papers shared on the platform happen outside of public view and that, when collecting all shares, the volume of activity approximates patterns of engagement previously only observed for Twitter.

Both results suggest that the role and impact of Facebook as a medium for science and scholarly communication has been underestimated. Furthermore, they emphasise the importance of openness and transparency around the collection and aggregation of altmetrics.

URL : https://arxiv.org/abs/1909.01476