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Record W3195172826 · doi:10.1002/ar.24735

The imperative for scientific societies to change the face of academia: Recommendations for immediate action

2021· article· en· W3195172826 on OpenAlexaff
Melissa A. Carroll, Shawn Boynes, Loydie A. Jerome‐Majewska, Kimberly Topp

Bibliographic record

VenueThe Anatomical Record · 2021
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsMcGill University Health Centre
FundersAmerican Association for Anatomy
KeywordsCommitFace (sociological concept)Inclusion (mineral)Diversity (politics)Public relationsUnderrepresented MinorityPolitical scienceAction (physics)Equity (law)Engineering ethicsBest practiceSociologyMedical educationSocial scienceLawMedicineEngineering

Abstract

fetched live from OpenAlex

As organizations that facilitate collaboration and communication, scientific societies have an opportunity, and a responsibility, to drive inclusion, diversity, equity, and accessibility in science in academia. The American Association for Anatomy (AAA), with its expressed and practiced culture of engagement, can serve as a model of best practice for other professional associations working to become more inclusive of individuals from historically underrepresented groups. In this publication, we acknowledge anatomy's exclusionary past, describe the present face of science in academia, and provide recommendations for societies, including the AAA, to accelerate change in academia. We are advocating for scientific societies to investigate inequities and revise practices for inclusivity; develop and empower underrepresented minority leadership; and commit resources in a sustained manner as an investment in underrepresented scientists who bring diverse perspectives and lived experiences to science in academia.

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)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.683
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.329
GPT teacher head0.501
Teacher spread0.172 · 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 designNot applicable
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

Citations13
Published2021
Admission routes1
Has abstractyes

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