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Record W4400955615 · doi:10.3233/shti240176

Intersectionality in Developing a Virtual Community of Practice Platform on Abortion

2024· article· en· W4400955615 on OpenAlexaffabout
Abdul‐Fatawu Abdulai, Efrat Czerniak, Cam Duong, Aashay Mehta, Rachel Chiu, Eleni Stroulia, Wendy V. Norman

Bibliographic record

VenueStudies in health technology and informatics · 2024
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsEquity (law)AbortionIndigenousHealth careIntersectionalityHealth equityPublic relationsPolitical scienceBusinessMedicineInternet privacySociologyGender studiesComputer sciencePregnancyLaw

Abstract

fetched live from OpenAlex

Abortion is an essential healthcare service in many countries including Canada. The number of people who seek abortion is disproportionately higher among equity-deserving populations. Yet the knowledge needed to provide evidence-based, culturally safe, and gender-affirming abortion services remain limited among healthcare professionals. Using an intersectional lens, we conducted focus group discussions with 14 healthcare professionals to understand how an abortion web-based platform, which is currently under development, can be adapted to meet the needs of equity deserving populations. The findings revealed the need for multi-lingual resources on abortion, information on funding coverage for undocumented migrants, educational resources on Indigenous cultural safety and gender-affirming practices, and a mapping tool to locate providers or pharmacists. Beyond presenting clinical guidelines on web platforms, this study revealed important considerations for the design of web platforms that can help advance access to abortion for equity-deserving populations.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.093
GPT teacher head0.444
Teacher spread0.352 · 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 designQualitative
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
Published2024
Admission routes2
Has abstractyes

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