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Record W4391097528 · doi:10.5399/osu/advjrnl.4.2.2

Results & Successes of eAlliances: A Distributed Peer Mentoring Network Model for Women in Physics & Astronomy

2024· article· en· W4391097528 on OpenAlexfundno aff
Anne‐Barrie Hunter, Anne J. Cox, Cindy Blaha, Beth A. Cunningham, Rachel Ivie, K. P. H. Lui, Idalia Ramos-Colón, Barbara L. Whitten

Bibliographic record

VenueADVANCE Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsnot available
FundersLawrence Livermore National LaboratoryDivision of Materials ResearchDirectorate for STEM EducationUniversity of North Carolina at Chapel HillUniversity of AlbertaIllinois Wesleyan UniversityUniversity of MiamiRhodes CollegeColorado CollegeUniversity of Colorado BoulderUniversity of PennsylvaniaKent State UniversityUniversity of RochesterUniversity of MinnesotaHoward Hughes Medical InstituteBucknell UniversityCarleton CollegeNational Science Foundation
KeywordsPhysicsAstronomyAstrophysicsEngineering physics

Abstract

fetched live from OpenAlex

Physics continues to be a highly gendered discipline (AIP, 2020) with women faculty in physics and astronomy often working in isolation. Here we report on the results of an NSF-ADVANCE PLAN D project designed to combat this isolation through distributed peer-mentoring networks. The women physics and astronomy faculty participants in this project were overwhelmingly positive about the experience. This was true independent of career stage and institutional context. Participants reported that their networks were highly effective: providing support, guidance, and a sense of belonging to the discipline. We discuss important research and evaluation results, the elements necessary for successful distributed peer-mentoring networks, and suggest ways this model could be adapted and adopted for other minoritized faculty.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.942
Threshold uncertainty score0.512

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 head0.033
GPT teacher head0.390
Teacher spread0.358 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2024
Admission routes1
Has abstractyes

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