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Record W2025530500 · doi:10.7202/043770ar

Organisational Design for Co-Management : Comparing Four Committees in Nunavik

2005· article· en· W2025530500 on OpenAlexafffundvenueabout
Evelyn J. Peters

Bibliographic record

VenueLes Cahiers de droit · 2005
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGovernment (linguistics)Political scienceWildlife managementEnvironmental resource managementWildlifeEnvironmental planningPublic administrationPublic relationsBusinessGeographyEcologyEnvironmental science

Abstract

fetched live from OpenAlex

The Brundtland Report focused on the importance of institutional arrangements in solving pressing resource problems. Co-management arrangements have been an important avenue for Aboriginals to participate in the management of country foods, and the environments that support them. The James Bay and Northern Quebec Agreement, signed in 1975, created several co-management bodies that focus on environments and wildlife. This paper draws on the extensive body of literature on co-management to develop three principles to evaluate these arrangements. These principles have to do with the ability of committees to adapt to changing environments and demands, their effectiveness in influencing government decision-making, and their ability to represent Aboriginal cultures and values. Each of the co-management bodies created by the Agreement is evaluated according to these criteria.

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)0.040
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.767

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0150.010
Scholarly communication0.0080.002
Open science0.0030.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.054
GPT teacher head0.343
Teacher spread0.290 · 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 designQualitative
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

Citations2
Published2005
Admission routes4
Has abstractyes

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