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wiley journals acceptance rate
In the AGU data from this period, gender is measured as a male/female binary (with an option of prefer not to declare, although we recognize that this delineation does not capture the spectrum of gender identities). We hope that this study will incentivize more researchers to provide race/ethnic demographic information so that AGU and similar institutions can analyze it with more statistical power and make robust, data‐driven policies to better serve underrepresented populations. However, we know that racial/ethnic exclusion is particularly apparent in the geosciences (Bernard & Cooperdock, 2018; Dutt, 2019; Ford et al., 2019). More nuanced metrics of scientific success such as the differences in citations and citing literature as developed by Wu et al. Diverse teams composed of Asian American and Caucasian/White as well as teams with Asian American, All Other Minority, and Caucasian/White authors did not have significantly different acceptance rates than single‐race/ethnicity teams (differences < 3%, pAsian American and Caucasian/White = 0.749, pAsian American, All Other Minority, and Caucasian/White = 0.443). STEM employees are women (in 2018, U.S. Bureau of Labor Statistics, 2019), which is perhaps slightly underrepresented in AGU's authorship dataset where 19.3% of individuals on fully matched teams are women.
Mean ± s.d. 3. Mean ± s.d. Papers with mixed‐gender and mixed‐career stage teams had slightly fewer citations on average than their nondiverse counterparts, although these differences are statistically insignificant. Acceptance rates and citations are used here to measure the quality of science and impact of a study on the scientific community. Of all authors with nation affiliation provided, 32.9% are from the United States. Here, we compare metrics of success in academic research, acceptance rates, and citations, among/across differing team compositions regarding demographic diversity. Twenty‐three percent of U.S. This data set includes 91,427 submitted manuscripts containing 440,191 authors (non‐unique). The Journal follows the style recommendations given in the Publication manual of the American Psychological Association (5th edn., 2001). Matched individuals in the AGU team‐matched dataset are 13.4% Asian American, 72.6% White/Caucasian, and 14.0% other minorities (this category is described further in supporting information, similarly described by Ford et al., 2019). Of the racially/ethnically matched dataset (n = 4,975), 50.6% are single race teams. From their perspective, a consistently low acceptance rate may prove to be a deterrent to future submissions.
The opposite difference in citations has been found in other studies by Freeman and Huang (2015) and AlShebli et al. In this paper, we assess multiple metrics of demographic diversity including national affiliation, gender, and career stage of authors working in teams. Journals with lower article acceptance rates are frequently considered to be more prestigious and more “meritorious”. Citations of 38,184 published manuscripts were collected as of early 2019 using citation counts from Clarivate Analytics and only include citations by journals indexed in the Web of Science. Mixed‐race/ethnicity teams were associated with statistically significantly lower acceptance rates and fewer citations than racially/ethnically nondiverse teams. When U.S. author teams have multiracial/multiethnic teams, these scientific outcomes are lower than single‐race/ethnicity teams.
In the matched datasets, acceptance rates increase by 17.8% in manuscripts with two to eight authors. Although not every difference is statistically significant, the overall results are consistent with the notion that diversity can benefit science, but equitable practices and inclusive cultures must also be fostered. Use the link below to share a full-text version of this article with your friends and colleagues. Papers from racially/ethnically homogenous teams are accepted at a 5.5% higher rate than papers from racially/ethnically diverse teams (p < 0.01), although both types of teams fare about the same as single‐authored manuscripts (Figure 4a). Unlimited viewing of the article/chapter PDF and any associated supplements and figures. Use one of the options below to find the perfect journal for your article. The unmatched (full) datasets acceptance rates increase by 7.7%. Unlimited viewing of the article PDF and any associated supplements and figures. Data were received from 30 (26%) journals. (2015). Citation counts were matched to 2,943 of these (495 of these were single‐author papers). Enter your email address below and we will send you your username, If the address matches an existing account you will receive an email with instructions to retrieve your username, © 2020 British Equine Veterinary Association, I have read and accept the Wiley Online Library Terms and Conditions of Use. Diverse papers had 1.2 more citations for international teams than single‐nation teams (pnation < 0.01). Race/ethnicity for U.S.‐based authors is based on U.S. Census categories, 22.0% match. We compare each type of demographic diversity to the scientific “quality” of team manuscript submissions to peer‐reviewed journals to assess whether/the degree that diversity impacts science. Manuscripts of racially/ethnically homogenous teams had an average of 0.8 more citations than diverse ones, although this difference is not statistically significant (p = 0.15) (Figure 4b).
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