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Record W3015467212 · doi:10.1057/s41304-020-00251-4

The distribution of authors and reviewers in EPS

2020· article· en· W3015467212 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Political Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPublishingInequalityParity (physics)Gender disparityGender inequalityGender gapComparative politicsPhenomenonPolitical sciencePsychologySocial scienceDemographyDemographic economicsSociologyPoliticsLawEconomicsEpistemologyMathematics

Abstract

fetched live from OpenAlex

Abstract Gender inequality as a phenomenon is also present in academic writing and publishing. In this article, we review the gender imbalance in the percentage of authors and reviewers in EPS from 2015 to 2019. At the submissions stage, male authors submit approximately twice as many manuscripts compared to female authors. At the publication stage, there is less of a gender difference due to a higher success rate for female authors. For reviewers, however, the gender discrepancies are even wider. At the invitation stage, we invited only roughly four women to review for every ten men. When it comes to completed reviews, the gap widens to roughly three women for ten men. Our findings show that we still have a long way to go to achieve parity in the review process. We suggest that parity in the review process is not independent of more women scholars being promoted to higher level academic positions.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.977
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.127
GPT teacher head0.328
Teacher spread0.201 · 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