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Record W7128893898

Participatory Processes and Town Planning at the Metropolitan Scale : A Comparative Perspective between Lyon and Montreal

2012· article· fr· W7128893898 on OpenAlexaboutno aff
Lila Combe

Bibliographic record

Venuetheses.fr (ABES) · 2012
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaParticipatory planningParticipatory democracyCitizen journalismPublic investmentContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Cette thèse interroge le lien entre la participation et l’urbanisme à l’échelle métropolitaine. Il s’agit de comprendre comment les dispositifs participatifs mis en place dans les territoires contribuent à l’élaboration des politiques urbaines. Nous interrogeons en particulier la manière dont la participation permet la prise en compte, dans le processus d’élaboration des politiques, des enjeux portés par le public. Nous nous demandons également dans quelle mesure elle génère une plus grande coordination des acteurs, des dispositifs et des échelles qui interviennent dans cette élaboration. Nous abordons ces questions à l’échelle de la métropole, qui induit un ensemble de spécificités relatives à l’action sur les territoires et au public participant. Notre étude met en évidence plusieurs apports de la participation : sa contribution porte essentiellement sur l’énonciation des enjeux des politiques urbaines, et moins sur la formulation des solutions, qui s’avère source de désaccords. La participation génère de nouvelles coordinations entre acteurs, dispositifs et échelles d’action publiques, mais ces coordinations apparaissent souvent fragiles et éphémères. Si les étapes de la concertation et du débat public produisent chacune des effets propres, notre travail donne à voir une construction cumulative des effets au fil du processus participatif. Les transferts d’acteurs, la répétition d’enjeux et le raffinement des recommandations permettent, dans certains contextes, d’élargir le champ d’impact de la participation, qui s’étend alors de la formulation des enjeux jusqu’à la logique de mise en œuvre des politiques.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.620

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0130.012
Scholarly communication0.0090.003
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.166
GPT teacher head0.364
Teacher spread0.198 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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