Bibliographic record
Abstract
Giant freshwater prawn ( Macrobrachium rosenbergii ) or scampi is an important product in the Indian seafood export basket, the predominant form being frozen scampi. An analysis of the scampi export from India for the period 1995 to 2009 is attempted in this paper. The compound growth rates, market concentration and instability indices of the Indian scampi export were analyzed. The quantity and value of frozen scampi export from India increased by 67.22 and 117% respectively over the period, largely aided by the rapid growth of aquaculture. The study concentrates on major markets viz., Belgium, Canada, Germany, Japan, Netherlands, UAE, USA and UK since more than 80% of the scampi exports from India were to these markets. Results showed low and negative growth of Indian scampi export in terms of quantity, value and unit value for the period of study. There was evidence of high market concentration of Indian scampi export to various countries. High degree of instability in Indian scampi export was revealed using Absolute difference method and Coppock’s instability index (CII). The study revealed that India’s scampi export was concentrated mainly to those countries, which is either less desirable (low growth & high risk) or least desirable (low growth & low risk) category which in turn affects the economic growth of the country. The causes for the export instability index have also been discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".