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Record W3025602363 · doi:10.1522/revueot.v29n1.1128

L' hydroélectricité du Québec et les grandes régions productrices

2020· article· fr· W3025602363 on OpenAlexaffvenueabout
Marie‐Claude Prémont, Marc‐Urbain Proulx

Bibliographic record

VenueRevue Organisations & territoires · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité de MontréalUniversité LavalUniversité du Québec à MontréalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La grande production hydroélectrique du Québec fait la fierté de la population et de ses élites. Trèslargement produite loin des territoires métropolitains de Montréal et de Québec, l’hydroélectricité des régions du Nord-du-Québec, de la Côte-Nord et du Saguenay–Lac-Saint-Jean laisse-t-elle, sur ces territoires, un bénéfice à la hauteur de sa contribution importante à la richesse du Québec? En d’autres termes, la répartition de la rente hydroélectrique, ou sa dissipation, bénéficie-t-elle aux grandes régions productrices, qui comprennent une large part de la ruralité du Québec? Les auteurs estiment que l’histoire du dernier siècle, et particulièrement des dernières décennies, démontre que les retombées locales se sont réduites comme une peau de chagrin.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.778
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.263
Teacher spread0.234 · 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 designNot applicable
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
Published2020
Admission routes3
Has abstractyes

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