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Record W1581518647 · doi:10.1177/160940690900800306

Use of Rapid Ethnographic Methodology to Develop a Village-Level Rapid Assessment Tool Predictive of HIV Infection in Rural India

2009· article· en· W1581518647 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsSimon Fraser UniversityUniversity of Manitoba
Fundersnot available
KeywordsEthnographyHuman immunodeficiency virus (HIV)Citizen journalismPerspective (graphical)Public healthMedicineQualitative researchEnvironmental healthSociologyFamily medicineNursingPolitical scienceSocial scienceComputer scienceArtificial intelligenceAnthropology

Abstract

fetched live from OpenAlex

In rural India, with hundreds of thousands of villages, a priority from a programmatic perspective is to efficiently determine which villages are at highest risk of HIV/AIDS transmission. The authors first report on the use of a rapid ethnographic approach in 10 rural villages of Karnataka, India, to develop a domains and indicators framework of village-level HIV/AIDS risk and a subsequent rapid assessment tool. They then analyze the rapid ethnographic approach and the rapid assessment tool to discuss differences and commonalities among rapid designs. They also discuss if these studies can be properly categorized as ethnographies, are mainly qualitative in nature, and are in essence participatory, and how appropriate they are to the public health field in general and the HIV/AIDS field in particular.

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.

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)0.016
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.524
GPT teacher head0.536
Teacher spread0.012 · 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