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Record W2165876215 · doi:10.5539/gjhs.v4n6p43

Health Questions Posed by Amerindians in Guyana’s Deep Interior

2012· article· en· W2165876215 on OpenAlexaffvenue
Raywat Deonandan, Bekkie Vineberg, Rebecca Stulberg, Marya Jaleel, Nicholas Szecket, Dunn Sheila, Mary Ann Hamelin, Margaret Van der Kuur, Sarah Zelcer

Bibliographic record

VenueGlobal Journal of Health Science · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Health and Education
Canadian institutionsWomen's College HospitalMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsCuriosityReproductive healthDiseaseMedicineHealth promotionHuman immunodeficiency virus (HIV)Sexual transmissionPublic healthFamily medicineGerontologyPsychologyEnvironmental healthNursingSocial psychologyPopulationPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The forest-dwelling Amerindian peoples of Guyana are among that nation's most impoverished, vulnerable and least served. Health promotion messaging has been informed in large part by nation-level health indicators that may not be well targeted to this group. Our study sought to identify local health education needs, and to identify factors preventing proper uptake of health messaging. METHODS: As part of medical missions to the interior, we asked patients waiting for care to anonymously submit their health questions in writing. Conventional content analysis was employed to identify prevalent themes in their responses. FINDINGS: Sexual health (63.6%) and nutrition (17.4%) were the most popular themes asked about. Within the former, the science of sexual maturation and reproduction (31.4%) and HIV/AIDS (28.8%) were the most common sub-themes, with the pathophysiology and etiology of HIV/AIDS being the most common sub-theme within the latter. INTERPRETATION: Within Guyana's Amerindian community, there exists a prevalent curiosity about the basic science of both sexual reproduction and the transmission of sexual disease.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.467
Teacher spread0.428 · 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 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

Citations4
Published2012
Admission routes2
Has abstractyes

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