Article

The Possible Role of Resource Requirements and Academic Career-Choice Risk on Gender Differences in Publication Rate and Impact

Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Spain.
PLoS ONE (Impact Factor: 3.23). 12/2012; 7(12):e51332. DOI: 10.1371/journal.pone.0051332
Source: PubMed

ABSTRACT

Many studies demonstrate that there is still a significant gender bias, especially at higher career levels, in many areas including science, technology, engineering, and mathematics (STEM). We investigated field-dependent, gender-specific effects of the selective pressures individuals experience as they pursue a career in academia within seven STEM disciplines. We built a unique database that comprises 437,787 publications authored by 4,292 faculty members at top United States research universities. Our analyses reveal that gender differences in publication rate and impact are discipline-specific. Our results also support two hypotheses. First, the widely-reported lower publication rates of female faculty are correlated with the amount of research resources typically needed in the discipline considered, and thus may be explained by the lower level of institutional support historically received by females. Second, in disciplines where pursuing an academic position incurs greater career risk, female faculty tend to have a greater fraction of higher impact publications than males. Our findings have significant, field-specific, policy implications for achieving diversity at the faculty level within the STEM disciplines.

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Available from: Xiao Han T. Zeng, Jan 14, 2015
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    • "Specifically, we demonstrate that the distribution of the asymptotic number of accumulated citations to publications by a researcher or from a research institution is consistent with a discrete lognormal model [32] [38]. We validate our approach with two datasets acquired from Thomson Reuters' Web of Science (WoS): • Manually disambiguated citation data pertaining to researchers at the top United States (U.S.) research institutions across seven disciplines [39]: chemical engineering, chemistry, ecology, industrial engineering, material science, molecular biology, and psychology; • Citation data from the chemistry departments of 106 U.S. institutions classified as " very high research activity " . "
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    ABSTRACT: How to quantify the impact of a researcher's or an institution's body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact Factor, have become widespread despite their known limitations. We argue that most existing bibliometric indicators are inconsistent, biased, and, worst of all, susceptible to manipulation. Here, we pursue a principled approach to the development of an indicator to quantify the scientific impact of both individual researchers and research institutions grounded on the functional form of the distribution of the asymptotic number of citations. We validate our approach using the publication records of 1,283 researchers from seven scientific and engineering disciplines and the chemistry departments at the 106 U.S. research institutions classified as "very high research activity". Our approach has three distinct advantages. First, it accurately captures the overall scientific impact of researchers at all career stages, as measured by asymptotic citation counts. Second, unlike other measures, our indicator is resistant to manipulation and rewards publication quality over quantity. Third, our approach captures the time-evolution of the scientific impact of research institutions.
    Full-text · Article · Nov 2015 · PLoS ONE
    • "Of course, the biases that affect the evaluation of individual papers are amplified when these aggregate measures are considered. Most impact metrics have been shown to be strongly biased by multiple factors when authors are considered (Alonso, Cabrerizo, Herrera-Viedma, & Herrera, 2009; Duch et al., 2012; Kaur, Radicchi, & Menczer, 2013; Radicchi & Castellano, 2013) and corrections to mitigate biases due to discipline, multiple authors, and academic age have been proposed (Batista, Campiteli, & Kinouchi, 2006; Kaur et al., 2013; Schreiber, 2008; Sidiropoulos, Katsaros, & Manolopoulos, 2007; Waltman, van Eck, van Leeuwen, Visser, & van Raan, 2011). Unfortunately none of these corrections is effective against the whole spectrum of potential biases (Kaur et al., 2013). "
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    ABSTRACT: Citation metrics are becoming pervasive in the quantitative evaluation of scholars, journals, and institutions. Hiring, promotion, and funding decisions increasingly rely on a variety of impact metrics that cannot disentangle quality from quantity of scientific output, and are biased by factors such as discipline and academic age. Biases affecting the evaluation of single papers are compounded when one aggregates citation-based metrics across an entire publication record. It is not trivial to compare the quality of two scholars that during their careers have published at different rates, in different disciplines, and in different periods of time. Here we evaluate a method based on the generation of a statistical baseline specifically tailored on the academic profile of each researcher. We demonstrate the effectiveness of the approach in decoupling the roles of quantity and quality of publications to explain how a certain level of impact is achieved. The method can be extended to simultaneously suppress any source of bias. As an illustration, we use it to capture the quality of the work of Nobel laureates irrespective of number of publications, academic age, and discipline, even when traditional metrics indicate low impact in absolute terms. The procedure is flexible enough to allow for the evaluation of, and fair comparison among, arbitrary collections of papers - scholar publication records, journals, and institutions; in fact, it extends a similar technique that was previously applied to the ranking of research units and countries in specific disciplines (Crespo, Ortuño-Ortí, & Ruiz-Castillo, 2012). We further apply the methodology to almost a million scholars and over six thousand journals to measure the impact that cannot be explained by the volume of publications alone.
    No preview · Article · Oct 2015 · Journal of Informetrics
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    • "Peer reviewers strive to exercise impartial judgment to determine what information warrants publication, but objectivity may be hard to consistently achieve (Hojat et al. 2003; DeVries et al. 2009; Aarssen 2012; Duch et al. 2012; Heidari and Babor 2013). Single-blind review models have the potential to be problematic when authors are not anonymous because author characteristics may influence reviews (e.g., Blank 1991). "
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    ABSTRACT: This study investigated the possibility of gender differences in outcomes throughout the peer review process of American Fisheries Society (AFS) journals. For each manuscript submitted to four AFS journals between January 2003 and December 2010, we collated information regarding the gender and nationality of authors, gender of associate editor, gender of reviewers, reviewer recommendations, associate editor's decision, and publication status of the manuscript. We used hierarchical linear modeling to test for differences in manuscript decision outcomes associated with author, reviewer, and associate editor gender. Gender differences were present at some but not every stage of the review process and were not equal among the four journals. Although there was a small gender difference in decision outcomes, we found no evidence of bias in editors’ and reviewers’ recommendations. Our results support the conclusion that the current single-blind review system does not result in bias against female authors within AFS journals.
    Full-text · Article · Sep 2015 · Fisheries
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