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Record W3016668023 · doi:10.1515/9782766301430

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2023· article· fr· W3016668023 on OpenAlexaboutno aff
Bertrand Gervais

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Dans les dernières années, des actes de vandalisme « antigentrification » visant des petits commerces ont considérablement tendu le débat public montréalais, désormais polarisé entre les tenants d’une revitalisation des quartiers en déclin et une mouvance critique cherchant à attirer l’attention sur les inégalités de classes dans l’appropriation de l’espace urbain. Ces événements parfois violents, médiatisés jusque dans la presse nationale, ont placé bien malgré eux les entrepreneurs visés dans un conflit de classes qui dépasse largement les frontières de leur quartier. Des rues qui changent rassemble les résultats de deux enquêtes menées entre 2012 et 2017 dans deux quartiers anciens du centre de Montréal, Hochelaga-Maisonneuve et Saint-Henri–Petite Bourgogne. À partir d’entretiens qualitatifs, de données d’archives et de statistiques, il reconstitue près de 50 années de transformations sociales et économiques de ces deux zones qui ont longtemps symbolisé, dans l’imaginaire montréalais, l’archétype du quartier ouvrier. Ce faisant, l’ouvrage permet de dépasser le caractère souvent manichéen des débats actuels pour offrir une analyse riche et nuancée de cette composante essentielle de la ville contemporaine.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.659
Threshold uncertainty score0.487

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0040.002
Scholarly communication0.0170.007
Open science0.0030.006
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.6590.480

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 head0.431
GPT teacher head0.335
Teacher spread0.096 · 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.

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
Published2023
Admission routes1
Has abstractyes

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