War and wildlife: linking armed conflict to conservation
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
Armed conflict throughout the world's biodiversity hotspots poses a critical threat to conservation efforts. To date, research and policy have focused more on the ultimate outcomes of conflict for wildlife rather than on the ecological, social, and economic processes that create those outcomes. Yet the militarization that accompanies armed conflict, as well as consequent changes in governance, economies, and human settlement, has diverse influences on wildlife populations and habitats. To better understand these complex dynamics, we summarized 144 case studies from around the world and identified 24 distinct pathways linking armed conflict to wildlife outcomes. The most commonly cited pathways reflect changes to institutional and socioeconomic factors, rather than tactical aspects of conflict. Marked differences in the most salient pathways emerge across geographic regions and wildlife taxa. Our review demonstrates that mitigating the negative effects of conflict on biodiversity conservation requires a nuanced understanding of the ways in which conflict affects wildlife populations and communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it