From food security to food wellbeing: examining food security through the lens of food wellbeing in Nepal’s rapidly changing agrarian landscape
Bibliographic record
Abstract
This paper argues that existing food security and food sovereignty approaches are inadequate to fully understand contradictory human development, nutrition, and productivity trends in Nepalese small-scale agriculture. In an attempt to bridge this gap, we developed a new food wellbeing approach that combines insights from food security, food sovereignty, and social wellbeing perspectives. We used the approach to frame 65 semi-structured interviews in a cluster of villages in Kaski district in the mid-hills of Nepal on various aspects of food security, agriculture, off-farm livelihood opportunities, and women's wellbeing. Our results indicate that context-specific subjective and social relational factors highlighted by the food wellbeing approach are key to understanding a paradox of increased food security, yet decreasing sustainability of small-scale agriculture. Increased levels of male out-migration and opportunities for local off-farm work have increased local capacity to purchase food. The positive consequences for food security are indicated by evidence that households with non-farm income sources had better food sufficiency, absorption capacity, nutritional quality, and stability of food supply. These off-farm employment opportunities have also led to the greater involvement of low caste groups and women in small-scale agriculture. This has been empowering for both groups and led to an increase in wellbeing, particularly for those women who have become de facto heads of household. Yet, small landholdings, persistent patterns of unequal and absentee land ownership, sharecropping, women's overwork, and the aspirations of low caste farmers and women away from agriculture are simultaneously driving the erosion of local small-scale agricultural productivity and ecological sustainability.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| 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".