Revamping community‐based conservation through participatory research
Bibliographic record
Abstract
Community‐based conservation is experiencing a crisis of identity and purpose as a result of a disappointing track record and unresolved deficiencies. The latter include over‐simplified assumptions and misconceptions of “community,” the imposition of externally designed and driven projects at the community level, a focus on conservation outcomes at the expense of community empowerment and social justice, and limited attention to participatory processes. New approaches are urgently needed to address these weaknesses and to counter a rising trend towards environmental protectionism and a preference for conservation approaches at an eco‐regional scale that threaten the interests of local and Indigenous communities. We propose that three core principles of community‐based participatory research (CBPR)—(1) community‐defined research agenda; (2) collaborative research process; and (3) meaningful research outcomes—hold much promise. Drawing on the experience of a research partnership involving the James Bay Cree community of Wemindji, northern Quebec, and academic researchers from four Canadian universities, we document the process of applying these principles to a community‐based conservation project that uses protected areas as a political strategy to redefine relations with governments in terms of a shared responsibility to care for land and sea. We suggest that basic assumptions of CBPR, including collaborative, equitable partnerships in all phases of the research, promotion of co‐learning and capacity building among all partners, emphasis on local relevance, and commitment to long‐term engagement, can provide the basis for a revamped phase of community‐based conservation that supports environmental protection while strengthening local institutions, building capacity, and contributing to cultural survival.
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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 | 0.377 | 0.187 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.019 | 0.102 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.010 | 0.051 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".