Risk coping strategies in tropical forests: floods, illnesses, and resource extraction
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
This paper examines coping strategies in response to covariate flood shocks and idiosyncratic health shocks among riverine peasant households in the Amazonian tropical forests. An assessment of coping strategies reveals that although precautionary savings (food stock and livestock) are important for both types of shocks, ex post labor supply responses in the form of upland cropping and resource extraction (fishing and non-timber forest product gathering) are more common to cope with the flood shock depending on local environments. A bivariate probit model examines what factors shape households' adoption decisions of gathering and fishing as a coping strategy. The analysis reveals an important insurance role of non-timber forest product gathering for the asset poor who have limited options for coping with flood risk. Targeted interventions and programs for the poor to promote sustainable forest resource use are discussed.
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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 | 0.000 | 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) | 0.000 | 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