Ecologically sustainable but unjust? Negotiating equity and authority in common-pool marine resource management
Bibliographic record
Abstract
Under appropriate conditions, community-based fisheries management can support sound resource stewardship, with positive social and environmental outcomes. Evaluating indigenous peoples’ involvement in commercial sea cucumber and geoduck fisheries on the central coast of British Columbia, Canada, we found that the current social-ecological system configuration is relatively ecologically sustainable according to stock assessments. However, the current system also results in perceived inequities in decision-making processes, harvesting allocations, and socioeconomic benefits. As a result, local coastal resource managers envision a transformation of sea cucumber and geoduck fisheries governance and management institutions. We assessed the potential robustness of the proposed institutions using Elinor Ostrom’s common-pool resource design principles. Grounded in the region’s legal, political, and historical context, our analysis suggests that greater local involvement in these invertebrate fisheries and their management could provide more benefits to local communities than the status quo while maintaining an ecologically sustainable resource. Our research highlights the importance of explicitly addressing historical context and equity considerations in social-ecological system analyses and when renegotiating the institutions governing common-pool resources.
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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 | 0.018 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.040 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| 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".