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Record W7027056471

Beluga co-management : perspectives from Kuujjuarapik and Umiujaq, Nunavik

2007· dissertation· en· W7027056471 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2007
Typedissertation
Languageen
FieldArts and Humanities
TopicSchopenhauer and Stefan Zweig
Canadian institutionsnot available
FundersAustralian Government
KeywordsBeluga WhaleSubsistence agricultureWhalingBelugaBayPopulationWhaleCircumpolar star
DOInot available

Abstract

fetched live from OpenAlex

The Inuit of Nunavik have always harvested the beluga whale for subsistence purposes.This harvest is socially, culturally, and economically important to the Inuit of Nunavik.In the 1800s the Hudson Bay Company ran a commercial whaling post at the mouth of the Great Whale River.It was during this time that the eastern Hudson Bay beluga summer stock first began to decrease.In the i980s The Department of Fisheries and Oceans (DFO) first began to consider the subsistence harvest by the Inuit too high for the population to recover.They implemented a management strategy that consisted of harvest quotas and seasonal and regional closures.This strategy was implemented with very little Inuit consultation, and therefore is not agreeable to the Inuit of Nunavik.In December 2006 the Inuit and Federal Government signed the Nunavik Inuit Land Claims Agreement, which covers offshore areas not dealt with in the 1975 James Bay and Northern Quebec Agreement.This agreement created the Nunavik Marine Region Wildlife Management Board, a co-management board that allows for management decision-making by both the Federal Government and the Inuit.The purpose of this research is to identify Inuit perspectives on co-management for the eastern Hudson Bay beluga summer stock.Through this research 12 themes of co-management importance have been identified by Inuit community members in Kuujjuarapik and Umijuaq, Nunavik.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0260.008
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2007
Admission routes1
Has abstractyes

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