Agriculture in Uttarakhand, India—Biodiversity, Nutrition, and Livelihoods
Bibliographic record
Abstract
This study investigates food production and agrobiodiversity in the Tarikhet and Ukhimath blocks in Uttarakhand, India, located in the middle ranges of the Himalayas. On the small patches of terraced land available to the average household in these areas, the cultivation of a wide range of traditional and high-yielding varieties of grains, legumes, vegetables, and fruits is a positive feature in terms of sustainability. Some villages also supplement plant-based food production and income by incorporating animal husbandry into the overall agroecosystem. It was found, however, that the output of the average farm provides only about half of the household energy requirements, forcing most families to resort to off-farm activities to support a large proportion of their food and other requirements. There is therefore a need to develop policies that will continue to support the rich agrobiodiversity of these areas, while providing for the nutritional and economic needs of the population.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".