Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The organic food industry in India is in the early stages of growth. Higherdisposable income and greater health awareness have resulted in an increaseddomestic demand for organic food. There is huge premium in selling organicproducts, not only to export markets but also to affluent, health conscious domesticconsumers. India is endowed with an abundance of labour and has diverse agroclimaticregion that is well suited to year round agriculture. It still has strongtraditional agricultural practices. Can India make use of this comparative advantageto introduce sustainable agriculture practices and at the same time improveincomes of small and marginal farmers?On the supply side, small and marginalfarmers realize that there is an opportunity to get higher net incomes even if yieldsare low in organic agriculture. This is because the price of pesticides and chemicalshas increased significantly over the last few decades resulting in a significantincrease in the cost of production. Organic farming cost could be 50% to 60% lesswhen compared to inorganic farming practices.In addition to domestic demandside, globalized markets provide significant opportunities for Indian agriculture tocapture a larger share of the global demand for organic food. This paper analyzesthe growth of the organic food industry in relation to domestic and export demand.We also look at the supply side to determine if organic farming and sustainableagricultural practices could help improve farmers’ income. Finally, this paperanalyses existing policy framework towards organic agriculture and how small andmarginal farmers could possibly benefit in this niche market.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it