UNESCO Biosphere Reserves Towards Common Intellectual Ground
Bibliographic record
Abstract
The chapter also builds upon findings from a preliminary study (Mitchell, 2011a) with a new aim of establishing common theoretical ground for cross-scale adaptation of this research by stakeholders within UNESCO's current constellation of 564 Biosphere Reserves.The authors draw upon a transdisciplinary selection of resources including a synopsis from a two-day experts' workshop with Swedish and Canadian collaborators that analyzed socioecological inventories (SEIs) in two biosphere reserves (Schultz, Folke, and Olsson, 2007;Armitage and Plummer, 2010;Gafarova, May and Plummer, 2010; Mitchell, 2011b;Velaniškis, 2010), and pedagogical resources from a senior undergraduate assignment.These resources have been organized utilizing principles from international frameworks that underpin the UN Decade of Education for Sustainable Development (see also Lundholm and Plummer, 2010;Krasney, Lundholm and Plummer, 2010;Plummer, 2010;Schultz and Lundholm, 2010), and UNESCO's Man and the Biosphere Program (UNESCO, 2010).The following sections move to an overview of contemporary thinking within sustainability research alongside teaching and service initiatives being taken up at this mid-sized southern Ontario institution.Beginning with theoretical and institutional developments that www.intechopen.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 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 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".