Who Brings in the Fish? The Relative Contribution of Small-Scale and Industrial Fisheries to Food Security in Southeast Asia
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
Amidst overexploited fisheries and further climate related declines projected in tropical fisheries, marine dependent small-scale fishers in Southeast Asia face an uncertain future. Yet, small-scale fishers are seldom explicitly considered in regional fisheries management and their contribution to national fish supply tends to be greatly under-estimated compared to industrial fisheries. Lack of knowledge about the small-scale sector jeopardises informed decision-making for sustainable ecosystem based fisheries planning and social development. We fill this knowledge gap by applying reconstructed marine fish catch statistics from Cambodia, Malaysia, Thailand, and Vietnam – countries of the Gulf of Thailand - from 1950 to 2013 to assess the relative contribution of small-scale and industrial fisheries to national food security. Reconstructed catches quantify reported and unreported fish catch from industrial, small-scale, and recreational fishing. We then conduct a comparative analysis of the degree to which the industrial and small-scale sectors support food security, by converting total catch to the portion that is kept for human consumption and that which is diverted to fishmeal for animal feed or other purposes. Total reconstructed marine fish catch from the four Southeast Asian countries totalled 282 million t from 1950 to 2013, with small-scale sector catches being underestimated by an average of around 2 times. When the amount of fish that is diverted to fishmeal is omitted, small-scale fishers contribute more food fish for humans than do industrial fisheries for much of the period until 2000. These results encourage regional fisheries management to be cognisant of small-scale fisheries as a pillar of socio-economic well-being for coastal communities.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it