The impact of stock collapse on small-scale fishers’ behavior: evidence from Japan
Bibliographic record
Abstract
Understanding behavioral responses of resource users to environmental changes and incentives created by management systems is imperative to implement effective resource management and development policies. A small-scale mixed fishery in the Maizuru Bay, Japan, provides a natural experiment to evaluate changes in small-scale fishers’ harvesting and targeting behavior over the years that one of the key species in the fishery experienced a collapse of the stock. Using data on individual fishers across the pre- and postcollapse periods, we find that inefficient fishers were forced to shut down or stay idle along with the collapse of the stock, and this behavior led to an increase in the overall efficiency in the production of clams (Venerupis philippinarum). The depletion of the stock, however, imposed a natural constraint on the operation, resulting in a substantial decline in the maximum production achievable by the remaining fishers. We further show that the collapse of the stock not only affected the harvesting behavior against the declining species but also led to the expansion of the fishing capacity and effort to catch other species and the development of aquaculture as an alternative form of fish production in the region.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".