Governing enclosure for coastal communities: Social embeddedness in a Canadian shrimp fishery
Bibliographic record
Abstract
Critical analyses of neoliberalism׳s influence on fisheries governance have documented how enclosure, quota leasing and renting, and commodification can precipitate negative social consequences for fishing communities. By contrast, this paper draws on the concept of embeddedness to argue that certain policies and social relations can regulate enclosure, quota renting, and commodification in ways that empower community-based groups to facilitate the anchoring of fishery resources and wealth in coastal communities. It does so through an analysis of northern shrimp fisheries in Newfoundland and Labrador , Canada, between the 1970s and the early 2000s. This case study illustrates how fisheries enclosure policies informed by geographically and morally defined principles of access and equity and limits on commodification can meaningfully embed fishery resources and benefits in rural and remote coastal regions that depend on small-scale fishing. Although the application of social principles continues to be marginalized in the context of neoliberal policy regimes that privilege individual economic efficiency over distributive concerns, this paper provides new insight into the conditions under which principles of ethical allocation and distribution of resources are able to persist through an era of neoliberalism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.029 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".