From causes of conflict to solutions: Shifting the lens on human–carnivore coexistence research
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
Abstract Human‐carnivore conflicts pose significant challenges in the management and conservation of carnivores across the globe. Abundant research has led to generalizable insights into the causes of such conflicts. For example, conflicts predictably occur when carnivores have access to human food resources, particularly when their natural foods are scarce. However, similar insights into the effectiveness of interventions aimed at coexistence remains comparatively scarce. We hypothesized that this disparity might be reflected in a bias toward research focused on causes of conflict rather than interventions to address it. To test our hypothesis, we evaluated the content of studies on human–carnivore conflicts and coexistence in Canada and the United States from 2010 to 2021. We found that studies disproportionately focused on causes of conflict, with that discrepancy increasing through our study period. We also found a disproportionate focus on black bears and wolves and western jurisdictions, and a disproportionate use of observational (vs. experimental) approaches. Studies on conflict interventions were primarily directed at the carnivores themselves (e.g., lethal approaches) versus human elements (e.g., attractant management, policies), despite evidence that the latter are more effective. We expect that a shift in focus toward solutions‐oriented research, integrating insights across geographies, taxa, social contexts, and disciplines, would facilitate effective interventions and foster coexistence, improving outcomes for people and carnivores alike.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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