Preface and Acknowledgments
Bibliographic record
Abstract
Co-management is of growing interest among researchers, government, and non-government and community-based actors involved in natural resource management, conservation, and development activities.Co-management may be at a crossroads, however.Nearly twenty years have passed since Evelyn Pinkerton's influential volume on co-management, Co-operative Management of Local Fisheries: New Directions for Improved Management and Community Development, was published by UBC Press.Co-management has since entered the adaptive age.New concerns with adaptive processes, feedback learning, and flexible partnership arrangements are reshaping the co-management landscape.Increasingly, ideas about collaboration and learning are converging in the literature.There is a tremendous opportunity to examine co-management through additional perspectives, explore alternative directions and concepts, and critically examine the emergence of adaptive co-management as an innovative governance approach to social-ecological complexity.The chapters in this volume evolved over three meetings.They were selected from a commissioned set of papers presented at a two-day symposium, "Moving Beyond the Critiques of Co-Management: Theory and Practice of Adaptive Co-Management," held at Wilfrid Laurier University, Waterloo, Ontario, in February 2005.Researchers and practitioners from Canada, the United States, the Caribbean, and Europe were invited to explore the comanagement of natural resources from multiple perspectives.Symposium activities were guided by the following objectives: (1) to bring together researchers and practitioners to discuss the evolution of co-management; (2) to create an opportunity for the sharing of ideas and strategies for innovative governance approaches in the context of social, institutional, and ecological uncertainty; and (3) to explore new avenues and directions that may serve to advance the theory and practice of adaptive co-management.Two followup meetings provided an opportunity to share and reflect further upon comanagement ideas as they had evolved since the initial symposium: an
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.228 | 0.150 |
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".