When is a fisher (not) a fisher? Factors that influence the decision to report fishing as an occupation in rural Cambodia
Bibliographic record
Abstract
Abstract In the developing world, the majority of people who fish in inland areas do so primarily for subsistence needs. This suggests that survey or census questionnaires which collect information concerning the occupations of respondents will underreport the number of people who fish, and corollary to this, misrepresent dependence on fishing as a support service for food and supplemental income. This study uses the results of a household survey conducted in 37 villages across Cambodia to quantify the amount of fishing that is done by inland fishers who do not report fishing as a primary or secondary occupation. The study also identifies the household characteristics which influence the decision of an individual who fishes to report fishing as an occupation. Fifty‐eight percent of households whose members engaged in fishing activities did not report fishing as an occupation. Individuals whose household owned farmland, earned off‐farm income and fished primarily for subsistence needs were significantly less likely to report fishing as an occupation. When assessing the importance of fishing to inland rural communities for the purposes of rural planning and policy development, relying solely on census‐style occupation or employment data will misrepresent the contributions of subsistence fishing to household welfare.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".