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Record W4283727562 · doi:10.5195/ijms.2022.1581

Thinking Globally in the Pursuit of Individual Identity: Diversity, Equity, and Inclusion in the International Journal of Medical Students (IJMS)

2022· article· en· W4283727562 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

VenueInternational Journal of Medical Students · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsQueen's University
Fundersnot available
KeywordsEquity (law)Inclusion (mineral)Public relationsDiversity (politics)PublishingHealth equityPopulationPolitical scienceHealth careSociologyPsychologySocial scienceLaw

Abstract

fetched live from OpenAlex

Diversity, equity, and inclusion (DEI) are core values that are unequivocally essential to healthcare research and practice. However, global health inequities remain pervasive and disruptive to the delivery of healthcare. This unacceptable lack of inclusivity and equity infiltrates all aspects of medicine, including research and publication. Accordingly, there is a dissemination of unbalanced and homogenous perspectives which are not representative of the global population. The International Journal of Medical Students (IJMS) has strived to counter such biases through the development of content and the process of its publication. Further, the selection of its editorial team and ambassadors is conducted with the intention of diversity. We respect individual differences and celebrate them as strengths adding to the quality of our journal. Therefore, the IJMS has taken a positive step toward an equitable environment by publishing a policy statement on DEI. We hope to lead by example by fostering a culture of inclusivity for all researchers, regardless of background. Though, we recognize the complexity of implementing comprehensive DEI practices and consider it our duty to the community that we continuously develop through a dedicated effort and iterative process.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaOpen science
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
gptMetaresearchScholarly communicationOpen science
Domain: Evaluation · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.145
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1450.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0970.168
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.430
Teacher spread0.382 · 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