Technical Efficiency in the Malaysian Gill Net Artisanal Fishery
Bibliographic record
Abstract
[Conclusion]: Using individual vessel data from the Malaysian gill net, the study finds that most fishers exhibit a high degree of technical efficiency. Moreover, the factors explaining efficiency significantly differ by region and overall level of economic development. For instance, in the poorer and less developed east coast primary schooling of the skipper, smaller vessel size and larger family size significantly increase technical efficiency, but this is not yes for west coast. If these results hold yes in other artisanal fisheries with similar technology and environments, it would suggest that South East Asian gill net fishers are poor and efficient , but the factors that contribute to technical efficiency differ considerably by locality. The potential implications from our findings is that development projects targeted to artisanal fisheries must be locally-based and tailor made by region rather a broad and one size fits all approach to fisheries development. Further, the results suggest that targeted assistance to human and social capital and away from vessel and gear upgrades, may yield greater efficiency payoffs for artisanal fishers. Further, if the relatively high levels of technical efficiency found in the Malaysian gill net fishery exist in other artisanal fisheries, it suggests that targeted development assistance that has traditionally been focussed on the harvesting sector may be better directed to other priorities in artisanal fishing communities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.001 |
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".