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Record W4388979039 · doi:10.56397/sssh.2023.11.01

Accessibility of Gynecological Healthcare Services in Canada Under Immigration Policies

2023· article· en· W4388979039 on OpenAlexaffabout
Kristina Telman, Santiago Sammie, B. M. M. Kamal

Bibliographic record

VenueStudies in Social Science & Humanities · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsYork University
Fundersnot available
KeywordsImmigrationHealth careGovernment (linguistics)Stigma (botany)BusinessEconomic growthPolitical sciencePopulationLanguage barrierPublic relationsNursingMedicineEnvironmental healthEconomics

Abstract

fetched live from OpenAlex

This study examines the accessibility of gynecological healthcare services for immigrant women in Canada and explores the impact of immigration policies on their healthcare access. With a diverse immigrant population, Canada’s healthcare system faces the challenge of addressing disparities in healthcare utilization among newcomers. We investigate the barriers faced by immigrant women in accessing gynecological care, including language barriers, cultural and stigma-related challenges, and economic factors. We analyze government initiatives and community programs aimed at improving healthcare access for immigrant women. The study concludes with policy recommendations and strategies to promote awareness, emphasizing the importance of a comprehensive approach to ensure equitable healthcare access for all immigrants in Canada.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.214
GPT teacher head0.526
Teacher spread0.312 · 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 designObservational
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

Citations0
Published2023
Admission routes2
Has abstractyes

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