Should I stay or should I go? Fishers’ ability and willingness to adapt to environmental change in Cambodia's Tonle Sap Lake
Bibliographic record
Abstract
Abstract The livelihoods of people dependent on the Tonle Sap floodplain ecosystem in Cambodia are expected to be affected by changes in economic conditions, social circumstances, environmental perturbations, demographic shifts and political climates. This study assesses how small‐scale fisheries’ livelihoods are changing in response to social and environmental conditions using the opinions of fishers collected through an intensive family survey of 514 households from Pursat and Battambang Provinces in Cambodia. Probit modelling approach was used to assess whether a fisher would continue fishing or not in the future when subjected to a variety of shifting conditions and identify the factors associated with their response. It was found that in any future condition about 50% of fishers would likely continue to fish, which suggests how much they love their traditional livelihood of fishing. The remaining 50% considered to diversify their livelihood strategy by shifting towards a combination of fishing, farming, and off‐farm jobs. Furthermore, the analysis found that the fishers will change their fishing practices depending on how other sectors in the region develop. The model showed increasing access to agricultural activities decreased the likelihood of continuing to fish, whereas finding an off‐farm job corresponded to increased likelihood of continuing to fish.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".