History, culture, infrastructure and export markets shape fisheries and reef accessibility in India's contrasting oceanic islands
Bibliographic record
Abstract
SUMMARY Islands offer unique model systems for studying fisheries development in relation to the growing global seafood trade. This study examines how export-driven fisheries in India's oceanic islands (Andaman and Nicobar Islands and Lakshadweep Islands) differ significantly as a result of their varied history, culture, available infrastructure and market access. Despite being geographically closer to export centres on the Indian mainland, processing and transport infrastructure in the Lakshadweep Islands are limited. This only allows for the trade of non-perishable commodities like dried tuna that are caught using traditional pole-and-line fishing techniques, restricting reef exploitation to local preference-based consumption and opportunistic export. The Andaman Islands, on the other hand, with multiple daily flight connections and large private and government processing facilities, are better connected to export markets. The relatively recent and multicultural fisheries of these islands supply marine commodity chains for reef fishery goods such as dried shark fins, frozen snapper fillets and chilled groupers. The Nicobar Islands are furthest away from mainland export centres and are mostly populated by indigenous communities – fishing here is mostly for subsistence and local sale. Revised estimates of travel times to export market centres are counterintuitive in terms of geographical distances and are significantly different from travel times to local markets.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".