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Record W7014878658

Réinventer le village! Les pratiques participatives comme levier de développement local en milieu rural : le cas de l'écoquartier de Petit-Saguenay

2024· other· fr· W7014878658 on OpenAlexaboutno aff

Bibliographic record

VenueArchipelago (University of Quebec in Montreal) · 2024
Typeother
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionResearch methodologyNewspaper
DOInot available

Abstract

fetched live from OpenAlex

Sous la forme d’un essai libre, ce travail porte sur la démarche de planification participative du projet d’écoquartier de Petit-Saguenay. L’approche narrative, basée sur l’observation participante de la directrice du développement de la municipalité de Petit-Saguenay, permet de faire état des freins et leviers à la mise en oeuvre de cette initiative. À travers cette étude de cas, l’attention est portée sur la latitude de l’administration municipale dans la mise en oeuvre de son développement au moyen des pratiques participatives; la contribution de la néoruralité au sein de ces dynamiques; ainsi que l’expérimentation du renouvellement des pratiques démocratiques. Ces considérations soulignent la pertinence de porter notre regard sur les potentialités du pouvoir municipal, territorialisé à l’échelle provinciale, comme « vecteur de changement ». De plus, cette expérience est riche en savoirs expérientiels qui peuvent être mobilisés pour repenser les pratiques d’aménagement du territoire et des milieux de vie, avec une attention particulière aux usagers et aux capacités du territoire. \n_____________________________________________________________________________ \nMOTS-CLÉS DE L’AUTEUR : Ruralité, Néoruralité, Développement local, Écoquartier, Participation citoyenne, Institution municipale

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 score0.916
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0150.009
Scholarly communication0.0040.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.025
GPT teacher head0.289
Teacher spread0.264 · 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
Published2024
Admission routes1
Has abstractyes

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