Agricultural practices, food production, food security and governance in South Asia
Bibliographic record
Abstract
Background: South Asia, the most populous and densely populated geographical region in the world, has a long experience of famine. The introduction of high input modern agriculture, dependent on fossil fuels, made the region a net food exporter. However, South Asia still has the world’s highest number of undernourished children, even more than in Sub-Saharan Africa. Aims: This study explores the development paradox of high agricultural growth and looming food insecurity in South Asia, in the context of nearing limits to growth. Methods: Literature review, supplemented by field based research, conducted in rural areas of India.Results: In South Asia, the dominant strategy of food production has assumed that the natural resource base (e.g. soil, energy, water) is effectively unlimited. Adverse ecological consequences and the concept of sustainability has received inadequate attention, resulting in worsening water shortage, salinity, toxic contamination, soil erosion, , and resurgent vector borne diseases. Growing tension over trans-boundary water between India and Pakistan could even lead to a nuclear confrontation. Public investment in agriculture research has also been low, for instance, in India only 0.5% of agricultural GDP compared to 2-3% in developed countries. Advanced crop technologies have been insufficiently complemented by supportive infrastructure, inadvertently contributing to thousands of suicides in farming communities. Safety net programs for the most vulnerable population have not delivered intended food security improvement; instead endemic problems including lack of accountability, and top down, opaque governance have worsened. Relatively high population growth has impaired development trajectories and also worsened nutritional inequality. Conclusions: Current agricultural and development policies are increasing nutritional inequalities in many parts of South Asia. The current paradigms are unsustainable and need major reform.
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How this classification was reachedexpand
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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".