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Record W2186119643

Improving Health Equity: The Promising Role of Community Health Workers in Canada Improving Health Equity: The Promising Role of Community Health Workers in Canada

2014· article· en· W2186119643 on OpenAlexaboutno aff
Sara Torres, Ronald Labonté

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHealth equityHealth careEquity (law)RefugeeImmigrationSocial determinants of healthCommunity health workersEconomic growthPublic healthPublic relationsBusinessNursingPopulationPolitical scienceMedicineEnvironmental healthHealth services
DOInot available

Abstract

fetched live from OpenAlex

Abstract This article reports findings from an applied case study of collaboration between a commu-nity-based organization staffed by community health workers/multicultural health brokers (CHWs/MCHBs) serving immigrants and refugees and a local public health unit in Alberta, Canada. In this study, we explored the challenges, successes and unrealized potential of CHWs/MCHBs in facilitating culturally responsive access to healthcare and other social services for new immigrants and refugees. We suggest that health equity for marginalized populations such as new immigrants and refugees could be improved by increasing the role of CHWs in population health programs in Canada. Furthermore, we propose that recognition by health and social care agencies and institutions of CHWs/MCHBs, and the role they play in such programs, has the potential to transform the way we deliver healthcare services and address health equity challenges. Such recognition would also benefit CHWs and the popula-tions they serve.

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)0.006
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 score0.081
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0270.007
Scholarly communication0.0080.002
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.056
GPT teacher head0.387
Teacher spread0.331 · 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
Published2014
Admission routes1
Has abstractyes

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