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Record W4298007154 · doi:10.1505/146554822835941823

Power-sharing between the Cree and Québec governments in Eeyou Itschee (Québec, Canada): sovereignties, complexity, and equity under the Adapted Forestry Regime of the Paix des Braves

2022· article· en· W4298007154 on OpenAlexaffabout
François-Xavier Cyr, Stephen Wyatt, Martin Hébert

Bibliographic record

VenueThe International Forestry Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité de MonctonUniversité Laval
Fundersnot available
KeywordsEquity (law)IndigenousGovernment (linguistics)PoliticsPolitical scienceState (computer science)ForestryForest managementPublic administrationGeographyBusinessEnvironmental resource managementEcologyEconomicsLawComputer science

Abstract

fetched live from OpenAlex

The Adapted Forestry Regime (AFR) of the Paix des Braves agreement is an important stepping-stone in the long process of involving Indigenous Peoples in state management of forestlands in Canada. This paper explores the challenges raised by a process involving the Cree nation and the Québec provincial government in the implementation of a collaborative approach to forest management on Cree traditional lands. We present three key processes that have contributed to the AFR since 2002, each of which led to further agreements, committees and processes. While the Crees have obtained additional powers for forestland management through the AFR, our analysis reveals the complexity of these processes that must deal with both political and technical issues that are often closely intricated one with the other. Ultimately, it is the Crees who bear the heaviest burden of the compromises that must be made implementing this collaborative process.

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)0.006
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.832

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.008
Scholarly communication0.0060.002
Open science0.0020.002
Research integrity0.0010.002
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 head0.101
GPT teacher head0.307
Teacher spread0.206 · 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

Citations8
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueThe International Forestry ReviewSame topicFrench Urban and Social StudiesFrench-language works237,207