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Record W4206366475 · doi:10.7870/cjcmh-2021-022

An Action Plan to Modernize Gender, Sex, and Sexual Orientation Information Practices in Canadian Electronic Health Record Systems

2021· article· en· W4206366475 on OpenAlexaffvenueabout
Francis Lau

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAction planPlan (archaeology)Sexual orientationAction (physics)Information sharingPsychologyReproductive healthOrientation (vector space)Electronic health recordPublic relationsPolitical scienceMedicineSocial psychologyGeographyManagementEnvironmental healthHealth care

Abstract

fetched live from OpenAlex

This brief report contains a summary version of the proposed action plan to modernize gender, sex, and sexual orientation (GSSO) information practices in Canadian electronic health record (EHR) systems. The plan was co-created by a research team with guidance from the Infoway Sex and Gender Working Group, organizations and communities involved with sexual and gender minorities (SGM), and those with lived and living experiences as SGM. The plan describes seven high level actions needed to improve the principles, approaches, policies, and processes of defining, collecting, organizing, sharing, and using GSSO information in EHRs.

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)0.074
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.586

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.073
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0060.004
Science and technology studies0.0150.005
Scholarly communication0.0100.005
Open science0.0070.008
Research integrity0.0120.009
Insufficient payload (model declined to judge)0.0090.002

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 head0.113
GPT teacher head0.397
Teacher spread0.284 · 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.

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

Citations2
Published2021
Admission routes3
Has abstractyes

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