Bibliographic record
Abstract
Abstract: Community‐based conservation (CBC) is based on the idea that if conservation and development could be simultaneously achieved, then the interests of both could be served. It has been controversial because community development objectives are not necessarily consistent with conservation objectives in a given case. I examined CBC from two angles. First, CBC can be seen in the context of paradigm shifts in ecology and applied ecology. I identified three conceptual shifts—toward a systems view, toward the inclusion of humans in the ecosystem, and toward participatory approaches to ecosystem management—that are interrelated and pertain to an understanding of ecosystems as complex adaptive systems in which humans are an integral part. Second, I investigated the feasibility of CBC, as informed by a number of emerging interdisciplinary fields that have been pursuing various aspects of coupled systems of humans and nature. These fields—common property, traditional ecological knowledge, environmental ethics, political ecology, and environmental history—provide insights for CBC. They may contribute to the development of an interdisciplinary conservation science with a more sophisticated understanding of social‐ecological interactions. The lessons from these fields include the importance of cross‐scale conservation, adaptive comanagement, the question of incentives and multiple stakeholders, the use of traditional ecological knowledge, and development of a cross‐cultural conservation ethic.
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.
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 | 0.042 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.047 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".