Pursuing Authenticity From Process to Outcome in a Community-Based Participatory Research Study of Intimate Partner Violence and HIV Vulnerability in North Karnataka, India
Bibliographic record
Abstract
Community-based participatory research has been seen to hold great promise by researchers aiming to bridge research and action in global health programs and practice. However, there is still much debate around whether achieving authenticity in terms of in-depth collaboration between community and academic partners is possible while pursuing academic expectations for quality. This article describes the community-based methodology for a qualitative study to explore intimate partner violence and HIV/AIDS among women in sex work, or female sex workers, and their male partners in Karnataka, South India. Developed through collaborative processes, the study methodology followed an interpretive approach to qualitative inquiry, with three key components including long-term partnerships, knowledge exchange, and orientation toward action. We then discuss lessons learned on how to pursue authenticity in terms of truly collaborative processes with inherent value that also contribute to, rather than hinder, the instrumental goal of enhancing the quality and relevance of the research outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".