Shrimp Allocation Policies and Regional Development Under Conditions of Environmental Change: Insights for Nunatsiavutimmuit
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This report is part of a larger research program examining the relationship between fisheries policy and \nregional development in Atlantic Canada’s northern shrimp fisheries. Since the extension of Canadian jurisdiction over its 200 mile Exclusive Economic Zone in 1977, federal policy makers have allocated shrimp licenses and quotas to cooperatives, community based organizations, inshore fish harvesters, large fishing companies as well as Indigenous groups. However, our knowledge of the relationship between fisheries policy and regional development outcomes in this fishery remains very limited, with the exception of case studies of a few organizations and regions in southeast Labrador and in \nNewfoundland. Despite the long history of substantial allocations of shrimp in northern Labrador/Nunatsiavut, we know little about how effective allocation policies have been in meeting regional development goals for Indigenous communities in the region. The objective of this research is to build on and extend our larger research project by identifying allocation policies that have enabled Nunatsiavut communities, and people to benefit from the shrimp fishery and to identify those \ndevelopment benefits in a systematic way. The research findings help us meet two further practical objectives: to provide research evidence to inform federal, provincial, and municipal policymaking and decision-making and to assist regional bodies and community groups in their decision-making and activities aimed at improving social, economic, cultural, and environmental conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.019 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it