Participatory Watershed Development in India: Can it Sustain Rural Livelihoods?
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The purpose of this article is to assess the impact of policy interventions through watershed development (WD) on the livelihoods of the rural communities. This is done by assessing the programme in the context of a sustainable rural livelihoods framework, that is, looking at its impact on the five types of capital assets and strategies required for the means of living. The article also examines the vulnerability and stability of these capital assets, as well as analysing which people participate in the programme and enhance their livelihoods through sharing its benefits. In the light of the analysis, it is argued that watershed development holds the potential for enhanced livelihood security even in geo‐climatic conditions where the watershed cannot bring direct irrigation benefits on a large scale. In such fragile environments, however, watershed development is a necessary but not a sufficient condition for sustaining rural livelihoods. While the focus of watershed development is primarily on strengthening the ecological base such as water bodies (including traditional tanks), grazing lands and wastelands, it should be complemented with other programmes which focus on landless poor households in order to make it pro‐poor. In the context of low rainfall regions where improvement in irrigation facilities is slow, agriculture alone cannot support the communities. Policies and programmes should aim at creating an environment for diverse livelihood activities, which are the choice of the household rather than distress activities.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it