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Record W3023730740 · doi:10.1002/bes2.1705

Effects of Inferred Gender on Patterns of Co‐Authorship in Ecology and Evolutionary Biology Publications

2020· article· en· W3023730740 on OpenAlexafffund
Dachin N. Frances, Connor R. Fitzpatrick, Janet Koprivnikar, Shannon J. McCauley

Bibliographic record

VenueBulletin of the Ecological Society of America · 2020
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsToronto Metropolitan UniversityCanadian Celiac AssociationUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPublicationProductivitySpeculationEcologySubject (documents)Set (abstract data type)Position (finance)BiologyPolitical scienceLibrary scienceEconomic growthLawComputer science

Abstract

fetched live from OpenAlex

Abstract Senior positions in academia such as tenured faculty and editorial positions often exhibit large gender imbalances across a broad range of research disciplines. The forces driving these imbalances have been the subject of extensive speculation and a more modest body of research. Given the central role publications play in determining individual outcomes and progress in academic settings, unequal patterns of authorship across gender could be a potent driver of observed gender imbalance in academia. Here, we investigate patterns of co‐authorship across four journals in ecology and evolutionary biology at four time‐points spanning four decades. Co‐authorship patterns are of interest because collaborations are important in scientific research, affecting individual researcher productivity, and increasingly, funding opportunities. Based on inferred gender from set criteria, we found significant differences between male and female researchers in their tendency to publish with female co‐authors. Specifically, compared to women, male researchers in the last author position were more likely to co‐author papers with other males. While we did find that the proportion of female co‐authors has increased modestly over the last thirty years, this is strongly correlated with an increase in the average number of authors per paper over time. Additionally, the proportion of female co‐authors on papers remains well below the proportion of PhDs awarded to females in biology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.014
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.341
GPT teacher head0.471
Teacher spread0.130 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2020
Admission routes2
Has abstractyes

Explore more

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