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Record W2527711138 · doi:10.18294/sc.2016.883

Guías bilingües: una estrategia para disminuir las barreras culturales en el acceso y la atención en salud de las comunidades wayuu de Maicao, Colombia

2016· article· es· W2527711138 on OpenAlexaff
Sandra Yaneth Patiño-Londoño, Javier Mignone, Diana María Castro-Arroyave, Natalia Gómez Valencia, Carlos Rojas

Bibliographic record

VenueSalud Colectiva · 2016
Typearticle
Languagees
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsUniversity of ManitobaManitoba Health
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

The article examines the use of bilingual guides to decrease cultural barriers to health care access in the Wayuu indigenous communities of Colombia. Within a larger project on HIV carried out between 2012 and 2014, 24 interviews were conducted with key actors in the administrative and health areas, including Wayuu bilingual guides. As a result of the qualitative analysis, the study identified three cultural barriers to health care access: a) language; b) the Wayuu worldview regarding the body, health, and illness; and c) information about sexual and reproductive health and HIV not adapted to the Wayuu culture. The study identifies the bilingual guides as key actors in reducing these barriers and concludes with a discussion of the role of the guides, the tensions inherent to their work, and the complexity of their contributions as cultural mediators.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.166
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.037
GPT teacher head0.444
Teacher spread0.406 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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