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Record W2791601040 · doi:10.1177/1049732317742129

Localizing Global Medicine: Challenges and Opportunities in Cervical Screening in an Indigenous Community in Ecuador

2018· article· en· W2791601040 on OpenAlexafffund
Peter Nugus, Julie Désalliers, Juana Morales, Lisa Graves, Andrea Evans, Ann C. Macaulay

Bibliographic record

VenueQualitative Health Research · 2018
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsUniversity of TorontoMcGill University
FundersMcGill University
KeywordsIndigenousCervical screeningMedicinePolitical scienceFamily medicineTraditional medicineGeography

Abstract

fetched live from OpenAlex

This participatory research study examines the tensions and opportunities in accessing allopathic medicine, or biomedicine, in the context of a cervical cancer screening program in a rural indigenous community of Northern Ecuador. Focusing on the influence of social networks, the article extends research on "re-appropriation" of biomedicine. It does so by recognizing two competing tensions expressed through social interactions: suspicion of allopathic medicine and the desire to maximize one's health. Semistructured individual interviews and focus groups were conducted with 28 women who had previously participated in a government-sponsored cervical screening program. From inductive thematic analysis, the article traces these women's active agency in navigating coherent paths of health. Despite drawing on social networks to overcome formidable challenges, the participants faced enduring system obstacles-the organizational effects of the networks of allopathic medicine. Such obstacles need to be understood to reconcile competing knowledge systems and improve health care access in underresourced communities.

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)0.037
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0370.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.685
GPT teacher head0.614
Teacher spread0.071 · 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 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

Citations18
Published2018
Admission routes2
Has abstractyes

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