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Record W2560233315

Le logement locatif dans Villeray : la transformation du parc de logements locatifs et ses coûts sociaux

2016· article· fr· W2560233315 on OpenAlexaboutno aff
Antoine Guilbault-Houde

Bibliographic record

VenueEspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique) · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsGentrificationHumanitiesPolitical scienceEconomyEconomicsArtEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

Ce projet de recherche porte sur le marché du logement locatif et traite spécifiquement des effets ressentis \npar les ménages locataires dans un contexte de gentrification. Le terrain d’étude est le quartier montréalais \nde Villeray. Nous posons l’hypothèse que Villeray subit des changements associés à un contexte de \ngentrification et que ces changements imposent des couts aux locataires fragilisés et les force à quitter leur \nlogement. Deux études seront présentées. La première porte sur la progression du mode de tenure de la \ncopropriété (divise et indivise). Elle est basée sur une lecture minutieuse et sur l’analyse des registres de \ntaxes foncières de la ville de Montréal. La seconde, basée sur les dossiers de l’Association des locataires \nde Villeray (depuis 2001), traite des situations vécues menant à un déménagement forcé et établit les \ntrajectoires résidentielles de locataires délocalisés. This research deals primarily with the rental market of Villeray. The main hypothesis guiding our field \nresearch is that Villeray is undergoing a series of changes associated with gentrification and that these \nchanges force disadvantaged renters to move out at great personal costs. We present two field studies \nundertaken this year that evaluate the effects of changes occurring in the rental market on renter \nhouseholds. The first study examines co-ownership titles, specifically looking at owner occupancy and \ntenure through the analysis of municipal property assessment registries. The second study is based on \ndocumented cased of evictions. The descriptive data (gathered by a local housing advocacy group since \n2001) informs us of the situations leading to forced mobility and presents the residential trajectories of \ndisadvantaged renter households.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.552

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.083
GPT teacher head0.348
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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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