Facilitating biodiversity conservation through partnerships to achieve transformative outcomes
Bibliographic record
Abstract
Conservation biology is a mission-driven discipline that must navigate a new relationship between conservation and science. Because conservation is a social and political as well as an ecological project, conservation biologists must practice interdisciplinarity and collaboration. In a comparative study of 7 cases (Jaguars in the Chaco, Grevy's zebra in Kenya, Beekeeping in Tanzania, Andean cats in Argentina, Jaguars in Mexico, Lobster fishing, and Black bears in Mexico), we examined motivations for collaboration in conservation, who can collaborate in conservation, and how conservation professionals can work well together. In 5 case studies, successful conservation outcomes were prioritized over livelihood benefits. In the other 2 cases, livelihoods were prioritized. All case studies employed participatory approaches. There were multiple external actors, including local and Indigenous communities, nongovernmental organizations, agencies, regional and national governments, and international organizations, which enhanced conservation and wider sustainability outcomes. Key collaboration aspects considered across the case studies were time (mismatch between relationship building and project schedules), trust required for meaningful partnerships, tools employed, and transformative potential for people, nature, and the discipline of conservation biology. We developed guidelines for successful collaboration, including long-term commitment, knowledge integration, multiscalar and plural approaches, cultivation of trust, appropriate engagement, evaluation, supporting students, and efforts for transformation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.004 |
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".