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Record W2911477604 · doi:10.1002/ece3.4962

A sponsorship action plan for increasing diversity in STEMM

2019· article· en· W2911477604 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

VenueEcology and Evolution · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsDiversity (politics)Plan (archaeology)Action planInclusion (mineral)Action (physics)Public relationsInstitutionPsychological interventionPolitical scienceSociologyManagementPsychologySocial science

Abstract

fetched live from OpenAlex

There are numerous structural and cultural barriers to the progression of women and marginalized groups to leadership in academia, especially in Science, Technology, Engineering, Mathematics and Medicine (STEMM). A range of interventions have been described to address this inequity, with varying success. Here, we suggest that sponsorship could be one effective intervention and propose an institutional action plan to implement a sponsorship program in academia. We outline why sponsorship could be an effective strategy, especially if implemented through a deliberate program by an institution. We then detail the three components of an action plan to be considered in implementation: the elements of the program, the activities that sponsorship in academia likely encompasses, and the selection of sponsors and protégés. The plan could also be enacted by academic leadership in the absence of an institutional program and could serve as a guide to individuals in academia aspiring to address diversity and inclusion in STEMM.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.060
GPT teacher head0.275
Teacher spread0.215 · 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