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Record W4388913883 · doi:10.4000/echogeo.25453

La rivière Magpie-Mutehekau shipu en personne

2023· article· fr· W4388913883 on OpenAlexaboutno aff
Fabienne Joliet, Azou Joliet-Bidet

Bibliographic record

VenueEchoGéo · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtGeography

Abstract

fetched live from OpenAlex

La Mutehekau Shipu ou Magpie est la troisième rivière du monde à devenir une personne morale selon le droit international. Celle-ci traverse la Côte Nord du Québec (Canada) pour se jeter dans le fleuve Saint Laurent. En réaction au sort de sa « grande sœur » la rivière Romaine qui, non loin de là, vient d’être harnachée de quatre grands barrages hydroélectriques, le destin de la Magpie en a voulu autrement : elle est protégée au titre de personne juridique depuis 2021. À l’échelle régionale et du Québec, c’est une première qui témoigne d’une synergie entre autochtones (Innu) et allochtones, d’une stratégie environnementale et de décolonisation ; à l’échelle internationale, c’est une troisième qui renvoie à un changement de paradigme et un véritable tournant ontologique environnemental. Cette étude de cas est éclairée par le terrain et les récits recueillis.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.044
GPT teacher head0.289
Teacher spread0.246 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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