Conservation (In)Action: Renewing the Relevance of UNESCO Biosphere Reserves
Bibliographic record
Abstract
Abstract The research and policy landscape for biodiversity conservation is changing. Protected areas are now expected to meet a broad range of objectives including effective and equitable management. In this new landscape, organizations strive to find ways to ensure the rights of local and Indigenous peoples are respected while conservation scientists have endorsed the need for platforms for international research and practice. For 40 years, a growing international network of sites support such research and practice, yet, it has been underutilized and largely ignored by scientists and decision‐makers alike. To better understand this paradox, this article explores the evolution of the World Network of UNESCO Biosphere Reserves internationally and its application in Canada. Analysis of archived materials, a national survey of practitioners, and interviews with past and present members of Canada's national committee reveals an expanded mandate for biosphere reserves beyond conservation science and biodiversity protection. The article recommends that to support the expanded conservation agenda, biosphere reserves work with governments and conservation scientists to connect more effectively with global concerns and initiatives such as the Convention on Biological Diversity and Sustainable Development Goals; establish appropriate, reliable, and active transdisciplinary partnerships; and meaningfully engage a broader range of knowledge holders.
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".