A cultural consensus regarding the king vulture?: preliminary findings and their application to Mexican conservation
Bibliographic record
Abstract
Ecosystem management regularly requires bridging diverse cultural perspectives. As a result, researchers commonly assert that including local ecological knowledge in conservation strategies is essential to crafting enduring environmental solutions. Using the case of the king vulture (Sarcoramphus papa), we take preliminary steps in asking how ethnoecology and field biology might be combined in conservation practice. The paper reports on a questionnaire applied to sixty-six local experts in southern Yucatán, home to Mexico’s largest expanse of tropical forest and the Calakmul Biosphere Reserve. Local experts included forest workers, i.e. hunters, loggers, and gum tappers, some of whom worked as guides for field biologists. The research results point to the possibility of a cultural consensus among these experts regarding the bird’s natural history. After outlining this preliminary consensus and contrasting it with academic findings, the paper considers the implications of a consensus for conservation programming.
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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 | 0.001 | 0.001 |
| 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 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".