Strengthening women’s economic empowerment: The post-COVID re-opening of the weekly market through participatory action research and deliberative forums in western Nepal
Bibliographic record
Abstract
The haat, an open-air traditional marketplace, provides small farmers with access to markets where they can sell their products. These economic spaces are particularly important for women farmers, whose access to distant markets is limited amidst persisting gender-based constraints including mobility restrictions and security concerns. Beyond direct economic benefits, haats also serve as social spaces for women to connect with other farmers and exchange information. However, one such market (haat), operating twice a week in Sandhikharka, Arghakhanchi district for the past four decades, was closed during the COVID-19 pandemic and remained closed even after other restrictions were lifted. This prompted our participatory action research team to investigate the causes and consequences of its prolonged closure and to facilitate efforts to reopen it. In collaboration with the local government, the research institution organised deliberative forums where relevant stakeholders collectively identified the key constraints to reopening the haat and developed strategies for its revival. Ongoing efforts are focused on institutionalising the haat and ensuring its sustainable operation. In this paper, we outline the process followed and share insights generated from the research and engagement conducted during the reopening effort. Women smallholder farmers have expressed their appreciation for the reopening, noting that the haat is crucial not only for securing better prices for their produce but also for significantly reducing the challenges of selling their products elsewhere, while encouraging further economic activities and contributing to their economic empowerment.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.021 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".