How can a cooperative‐based organization of indigenous fisheries foster the resilience to global changes? Lessons learned by coastal communities in eastern Québec
Bibliographic record
Abstract
Abstract Halieutic resources and small‐scale fisheries are globally under stress due to global changes. This phenomenon has very strong impacts on the socioeconomic situation of vast coastal areas worldwide and of the communities living there, whose economies rely on the ocean. In the current context of a decrease of several halieutic stocks, there is a need of understanding what could be the avenues for fisheries‐dependent communities to adapt to global changes whilst preserving both local biodiversity and their ability to develop themselves. In this paper, we explore how a cooperative fisheries organizational model could allow coastal communities to foster their development without increasing the pressure on the resource they harvest. Through the analysis of the example of northern shrimp (Pandalus borealis) indigenous fisheries in eastern Québec, we expose how a cooperative‐based organization of fisheries that is oriented towards community development can foster resilience against the current decline of the resource in a socially vulnerable context at a micro and macro level. Furthermore, we show how collaboration between diverse types of fisheries organizations can allow socially innovative practices to scale up.
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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 | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".