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Record W2767348782 · doi:10.4000/books.pum.3322

Chapitre 3. Aménagement du territoire et gouvernance métropolitaine : l’agglomération de Québec

2016· book-chapter· fr· W2767348782 on OpenAlexaboutno aff
Francis Roy, Guy Mercier

Bibliographic record

VenuePresses de l’Université de Montréal eBooks · 2016
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceGeography

Abstract

fetched live from OpenAlex

La Communauté métropolitaine de Québec (CMQ) date de 2002. Son principal mandat est de planifier, sous le mode de la gouvernance, l’aménagement du territoire, en collaboration avec les institutions municipales régionales et locales qui la composent. L’exercice de planification métropolitaine, marqué par de nombreux délais et reports, s’est d’abord révélé difficile, car la structure institutionnelle mise sur pied en 2002 n’était pas optimale et a dû être adaptée. D’un point de vue légal, l’étude de l’évolution du cadre législatif relatif aux communautés métropolitaines, entre 2002 et 2010, révèle que leur création ne fut pas un événement spontané, mais plutôt le résultat d’un processus de maturation étalé sur près de dix ans. Puis, d’un point de vue pratique, l’examen des phases d’élaboration de son premier plan démontre que le caractère métropolitain des enjeux et des objectifs d’aménagement était une nouveauté avec laquelle les acteurs politiques et la population devaient se familiariser. Il en ressort que la conscience métropolitaine est toujours en voie de développement à Québec, avec une CMQ qui prend progressivement sa place comme organe de gouvernance et de coordination.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.001

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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