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Record W4401954857 · doi:10.1177/08404704241264426

Equity in practice: Integrating cross cultural health brokers for culturally safe primary care for immigrants and refugees in British Columbia

2024· article· en· W4401954857 on OpenAlexafffundabout
Mei-ling Wiedmeyer, Jeanette Somlak Pedersen, Zarghoona Wakil, Lindsay Hedden

Bibliographic record

VenueHealthcare Management Forum · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityRoyal Columbian Hospital
FundersCollege of Family Physicians of Canada
KeywordsRefugeeEquity (law)ImmigrationMulticulturalismNursingHealth careCultural competenceHealth equityCultural diversityMedicinePublic relationsPsychologyPolitical sciencePublic healthPedagogy

Abstract

fetched live from OpenAlex

Umbrella Multicultural Health Co-op is a community health centre serving cultural communities of immigrants/refugees in British Columbia. It uses Cross Cultural Health Brokers (CCHBs), multicultural workers bridging patients and the healthcare system, to better meet the primary care needs of immigrant/refugee populations. Through the Team Primary Care initiative, Umbrella Co-op: (1) added new CCHBs alongside allied health practitioners; and (2) implemented team workshops and evaluation for quality improvement. The learning health system framework guided project activities. Comprehensive, culturally responsive primary care for immigrants and refugees benefits from a team-based approach that includes the integration of CCHBs. Team development activities improved team function. Co-developing evaluation with the interprofessional team enabled meaningful participation. Health system design for equity-oriented team-based primary care for immigrants and refugees should include resources for CCHBs and team development infrastructure.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.809

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0050.002
Open science0.0020.013
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.039
GPT teacher head0.473
Teacher spread0.433 · 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 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
Published2024
Admission routes3
Has abstractyes

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