MétaCan
Menu
Back to cohort
Record W2124914723 · doi:10.1177/10432302012006009

Focus Groups in Rural Gujarat, India: A Modified Approach

2002· article· en· W2124914723 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

VenueQualitative Health Research · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsFocus groupSociocultural evolutionContext (archaeology)Public relationsFocus (optics)Data collectionRural areaPoliticsPopulationSociologyEconomic growthSocial sciencePolitical scienceGeographyAnthropology

Abstract

fetched live from OpenAlex

Focus groups have become increasingly popular in health research. However, their feasibility depends on the context of such research. Through discussion of focus groups they conducted in rural India, the authors argue that successful focus groups in rural contexts must be culturally sensitive, with a research team that goes beyond the mere technicalities of collecting data. A culturally competent focus group can result when the research team has geographic, political, economic, and sociocultural knowledge related to the research area and its population. With extensive local collaboration, foreign researchers are better able to conduct data collection respectfully. The authors provide recommendations for future studies toward increasing the cultural appropriateness of focus groups in areas such as rural India.

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)0.067
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.721
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0670.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.629
GPT teacher head0.618
Teacher spread0.010 · 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