An Interactive Governance and Fish Chain Approach to Fisheries Rebuilding: A Case Study of the Northern Gulf Cod in Eastern Canada
Bibliographic record
Abstract
Rebuilding collapsed fisheries is a multifaceted problem, requiring a holistic governance approach rather than technical management fixes. Using the Northern Gulf cod case study in eastern Canada, we illustrate how a "fish chain" framework, drawn from the interactive governance perspective, is particularly helpful in analyzing rebuilding challenges. The analysis demonstrates that factors limiting rebuilding exist along the entire fish chain, i.e., the pre-harvest, harvest, and post-harvest stages. These challenges are embedded in both the ecological and social systems associated with the Northern Gulf cod fisheries, as well as in the governing systems. A comparative analysis of the pre- and post-collapse of the cod fisheries also reveals governance opportunities in rebuilding, which lie in policy interventions such as integrated and ecosystem-based management, livelihood transitional programs, and cross-scale institutional arrangements. Lessons from the Northern Gulf cod case study, especially the missed opportunities to explore alternative governing options during the transition, are valuable for rebuilding other collapsed fisheries.
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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 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".