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Record W3162078592 · doi:10.1139/cjc-2020-0329

Starting grassroots initiatives to foster equity, diversity, and inclusivity in the Chemistry Department at the University of Alberta

2021· article· en· W3162078592 on OpenAlexaffvenueabout
Sorina Chiorean, Meagan S. Oakley, Jocelyn Sinclair

Bibliographic record

VenueCanadian Journal of Chemistry · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGrassrootsDiversity (politics)Equity (law)ChemistryInclusion (mineral)Public relationsPolitical scienceLaw

Abstract

fetched live from OpenAlex

The University of Alberta Working for Inclusivity in Chemistry (UAWIC) group was formed in 2017 to increase equity, diversity, and inclusion in the Department of Chemistry. With the goals of fostering a community amongst department members and retaining a diverse graduate student population, UAWIC has created initiatives addressing equity, diversity and inclusivity, professional development, and promoted visibility of diversity within the department. Training students how to overcome systemic barriers and providing platforms to share experiences will help aspiring chemists prepare for future career paths and develop a network of mentors and colleagues.

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)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
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 score0.998
Threshold uncertainty score0.726

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0260.007
Scholarly communication0.0130.002
Open science0.0020.015
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0150.001

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 head0.030
GPT teacher head0.254
Teacher spread0.224 · 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 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

Citations2
Published2021
Admission routes3
Has abstractyes

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