A Severe Lack of Evidence Limits Effective Conservation of the World's Primates
Bibliographic record
Abstract
Abstract Threats to biodiversity are well documented. However, to effectively conserve species and their habitats, we need to know which conservation interventions do (or do not) work. Evidence-based conservation evaluates interventions within a scientific framework. The Conservation Evidence project has summarized thousands of studies testing conservation interventions and compiled these as synopses for various habitats and taxa. In the present article, we analyzed the interventions assessed in the primate synopsis and compared these with other taxa. We found that despite intensive efforts to study primates and the extensive threats they face, less than 1% of primate studies evaluated conservation effectiveness. The studies often lacked quantitative data, failed to undertake postimplementation monitoring of populations or individuals, or implemented several interventions at once. Furthermore, the studies were biased toward specific taxa, geographic regions, and interventions. We describe barriers for testing primate conservation interventions and propose actions to improve the conservation evidence base to protect this endangered and globally important taxon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.100 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".