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Record W4205685032 · doi:10.1017/s0032247421000747

Commercial fishing, Inuit rights, and internal colonialism in Nunavut

2022· article· en· W4205685032 on OpenAlexaffabout
Warren Bernauer

Bibliographic record

VenuePolar Record · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFisheryFishingColonialismPoliticsGovernment (linguistics)Fisheries managementSubmarine pipelineMarine conservationCommercial fishingGeographyBusinessPolitical scienceOceanographyLaw

Abstract

fetched live from OpenAlex

Abstract This paper considers the degree to which the concept of ‘internal colonialism’ accurately describes the political economy of Nunavut’s commercial fisheries. Offshore fisheries adjacent to Nunavut were initially dominated by institutions based in southern Canada, and most economic benefits were captured by southern jurisdictions. Decades of political struggle have resulted in Nunavut establishing a role for itself in both the management of offshore resources and the operation of the offshore fishing industry. However, key decisions about fishery management are made by the federal government, and many benefits from Nunavut’s offshore fisheries continue to accrue to southern jurisdictions. The concept of internal colonialism is therefore a useful concept for understanding the historical development and contemporary conflicts over offshore fisheries. By contrast, Nunavut’s inshore fisheries were established as community development initiatives intended to promote economic well-being and stability. While inshore fisheries primarily benefit Inuit community economies, the growth of inshore fisheries has been hampered by small profit margins, inadequate marine infrastructure, and a dearth of baseline data. The federal government’s failure to support the expansion of inshore fisheries is a manifestation of internal colonialism, insofar as it reflects an unequal distribution of public infrastructure and research.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.029
GPT teacher head0.348
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2022
Admission routes2
Has abstractyes

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