From Coastal Timber Supply Area to Great Bear Rainforest: Exploring Power in a Social-ecological Governance Innovation
Bibliographic record
Abstract
"As the 2005 Millennium Ecosystem Assessment revealed, many social-ecological systems around the world are currently being governed unsustainably. Consequently, social innovation is needed to transform current governance regimes and introduce new more resilient arrangements. Although dominant institutions and social groups may resist such innovations which threaten the status quo and their interests, groups on the margins of the established social order can often trigger governance transformations, despite a lack of conventional financial and institutional resources. In particular, there are numerous cases of marginalized groups initiating processes of radical change to establish sustainable governance practices for threatened social-ecological systems. We investigate one such case, and introduce a typology of power developed by Barnett and Duvall (2005) to illuminate the role that nongovernmental organizations and indigenous nations played in the transformation of a social-ecological governance regime for an area known as the Great Bear Rainforest, located in British Columbia, Canada. The analysis shows the interplay of compulsory, structural, institutional, and productive forms of power as the four key interest groups in this case enacted the governance transformation. The conclusions draw lessons about how the use and distribution of certain types of power can shape the course and outcomes of social-ecological governance transformations."
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".