Export performance and direction of trade of organic products from India
Bibliographic record
Abstract
Organic products are produced using an ecologically and socially conscious agricultural system that does not utilise chemical pesticides or fertilisers. India produced around 2.9 million metric tonnes (MT) of certified organic products between 2022 and 2023. The volume produced included various types of food items, such as tea, coffee, oil seeds, fibre, sugar cane, cereals and millets, cotton, pulses, aromatic and medicinal plants, dry fruits, vegetables, processed meals, and so on. The goal of the current study was to determine the patterns of organic product export and trade direction in India between 2012-13 and 2021-22. Secondary data regarding export of organic products and data on country wise exports was obtained from APEDA. The Compound Annual Growth Rate model is used to predict the export trend. During the first sexennial period, organic product exports had a higher CAGR of 18.67%, whereas during the second sexennial period, exports decreased and the CAGR was around 0.99%. For the overall period, it was reported to be 16.68 per cent. Cuddy & Della Valle's instability index was used to measure the export of organic products instability index. The CDVI for the whole period of record was 20.76 percent, indicating somewhat unstable exports throughout that period of time. The dynamic nature of trade pattern of the organic products was analysed by employing first order Markov process. By TPM it was noticed that most loyal country which imports organic products was USA and Canada.
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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 | 0.000 |
| 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 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".