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Record W3032855166 · doi:10.1002/leap.1301

Evaluating equity in scholarly publishing

2020· article· en· W3032855166 on OpenAlexaff
Simone Taylor, Susan Spilka, Kristen Monahan, Isabel Mulhern, Jeri Wachter

Bibliographic record

VenueLearned Publishing · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsPublishingWorkforceBachelorEquity (law)Diversity (politics)Ethnic groupPublic relationsWhite paperProject commissioningPolitical scienceSociologyPsychologyLaw

Abstract

fetched live from OpenAlex

Abstract The Workplace Equity Project (WE) conducted a global survey in 2018 to map the parameters that define the scholarly publishing landscape, understand the drivers for change, and recommend solutions for delivering improved outcomes. Results find that there are imbalances in diversity inherent in the workforce (96% with a Bachelor's degree or higher, 76% female, 83% heterosexual, 81% White, and 89% report no disabilities) and that outcomes diverge for respondents based on their gender and ethnicity, highlighting distinct inequities in the workplace. The leadership profile is more male (33% vs. 21%), and more White (91% vs. 81%) than the sample as a whole. Moreover, those respondents with characteristics more reflective of the leadership profile are more likely to report that they believe they are fairly compensated, recognized by the leadership, and have fair opportunities for advancement. The article recommends improvements to current practice in recruitment, sponsorship and advocacy, and staff retention to drive change towards creating a more equitable, inclusive workforce. Key points Senior leaders in scholarly publishing are more likely to be older, White males with master's degrees. The chances of attaining a senior position in scholarly publishing are higher for White males with no tertiary‐level qualifications than for Black females with postgraduate degrees. Most demographic groups (with the exception of the Black cohort) recognize their own challenges but are blind to the bias experienced by other groups. Direct line management practice defines individual experience irrespective of organizational policy. White and Asian males are more likely to be satisfied with career prospects and rewards than other groups. White women are more likely to be satisfied with their current positions than other groups. Job satisfaction in scholarly publishing varies according to ethnicity and gender, and companies have a duty to be more inclusive and diverse in their employment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.100
metaresearch head score (Gemma)0.243
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1000.243
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.008
Science and technology studies0.0040.006
Scholarly communication0.0130.012
Open science0.0020.012
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.553
GPT teacher head0.446
Teacher spread0.107 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainEvaluation
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

Citations12
Published2020
Admission routes1
Has abstractyes

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