Using local actors’ perceptions to evaluate a conservation tool: the case of the Mexican compensation scheme for predation in Calakmul
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
Compensation schemes are important tools to counteract crop or livestock loss caused by wildlife of conservation concern. We adopted a research action approach that focused on local actors’ knowledge and evaluations of a compensation scheme for carnivore depredation on livestock in Mexico. We conducted 165 questionnaires with livestock producers in the Calakmul region, who rated criteria covering various aspects of the scheme’s functioning. Three-quarters of participants had heard of the scheme, but only half of those knew the scheme beyond its name. Satisfaction with the scheme’s operation was associated with ease of contacting staff, whereas satisfaction with the result of application related to trust in staff. Using local actors’ perceptions allowed us to reveal criteria used for shaping evaluations. Results were presented during participatory workshops that generated targeted recommendations such as focusing efforts on information reaching areas where producers are less aware of the scheme and vulnerable to predation.
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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