Negotiating power relations, gender equality, and collective agency: are village health committees transformative social spaces in northern India?
Bibliographic record
Abstract
BACKGROUND: Participatory health initiatives ideally support progressive social change and stronger collective agency for marginalized groups. However, this empowering potential is often limited by inequalities within communities and between communities and outside actors (i.e. government officials, policymakers). We examined how the participatory initiative of Village Health, Sanitation, and Nutrition Committees (VHSNCs) can enable and hinder the renegotiation of power in rural north India. METHODS: Over 18 months, we conducted 74 interviews and 18 focus groups with VHSNC members (including female community health workers and local government officials), non-VHSNC community members, NGO staff, and higher-level functionaries. We observed 54 VHSNC-related events (such as trainings and meetings). Initial thematic network analysis supported further examination of power relations, gendered "social spaces," and the "discourses of responsibility" that affected collective agency. RESULTS: VHSNCs supported some re-negotiation of intra-community inequalities, for example by enabling some women to speak in front of men and perform assertive public roles. However, the extent to which these new gender dynamics transformed relations beyond the VHSNC was limited. Furthermore, inequalities between the community and outside stakeholders were re-entrenched through a "discourse of responsibility": The comparatively powerful outside stakeholders emphasized community responsibility for improving health without acknowledging or correcting barriers to effective VHSNC action. In response, some community members blamed peers for not taking up this responsibility, reinforcing a negative collective identity where participation was futile because no one would work for the greater good. Others resisted this discourse, arguing that the VHSNC alone was not responsible for taking action: Government must also intervene. This counter-narrative also positioned VHSNC participation as futile. CONCLUSIONS: Interventions to strengthen participation in health systems can engender social transformation. However they must consider how changing power relations can be sustained outside participatory spaces, and how discourse frames the rationale for community participation.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".