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Record W3040524024 · doi:10.1522/revueot.v29n2.1148

L' urbanisme transitoire à Montréal : entre innovation et préservation

2020· article· fr· W3040524024 on OpenAlexaffvenueabout
Taïka Baillargeon, Jérémy Diaz

Bibliographic record

VenueRevue Organisations & territoires · 2020
Typearticle
Languagefr
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Longtemps associées à l’activisme et à la transgression, les initiatives d’occupation temporaire des sites vacants sont désormais utilisées par les municipalités dans leur stratégie de réaménagement ainsi qu’envisagées comme vecteur de l’économie créative et comme moteur d’innovation (Bishop et Williams, 2012; Colomb, 2012; Ginez, 2018; Mould, 2014; Pinard et Vivant, 2017). Plusieurs chercheurs envisagent d’ailleurs qu’elles deviennent monnaie courante, s’intégrant à la planification traditionnelle (Bishop et Williams, 2012; Zielh, Oßwald, Hasemann et Schnier, 2012). Dans ce contexte, on parle de plus en plus d’urbanisme transitoire : une pratique qui est autorisée, planifiée et perçue comme une étape de préfiguration pour des projets de requalification pérennes. Qu’est-ce que l’urbanisme transitoire? Comment se distingue-t-il des autres formes d’urbanisme temporaire et comment se déploie-t-il dans le contexte montréalais? Autant de questions auxquelles nous tenterons de répondre dans cet article.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.225
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0100.016
Scholarly communication0.0110.004
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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
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

Citations8
Published2020
Admission routes3
Has abstractyes

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