MétaCan
Menu
Back to cohort
Record W1601280612 · doi:10.1111/1468-2427.12215

Claiming Rights To Mobility Through The Right To Inhabitance: Discursive Articulations from Civic Actors in Montreal

2015· article· en· W1601280612 on OpenAlexaffabout
Sophie L. Van Neste, Gilles Sénécal

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité de Montréal
Fundersnot available
KeywordsFraming (construction)SociologyOpposition (politics)Community organizingCentralityMobilitiesRight to the cityContext (archaeology)Political scienceGender studiesMedia studiesLawPoliticsSocial scienceEngineeringGeography

Abstract

fetched live from OpenAlex

Abstract How do claims for rights to mobility intersect with grievances pertaining to spatial justice in the city? This article addresses the issue by studying the concrete connections made by activists promoting car alternatives in Montreal. The activists' discursive categories point to the centrality of their conditions of inhabitance in their claims for certain rights to mobility. The discourses are analysed in the context of demands for safe spaces to walk and cycle in Montreal, and in the context of opposition to the rebuilding of the Turcot highway interchange. The article discusses internal dynamics of collective action, as well as the external influences and controls on activists contesting automobility to various degrees and with different spatially grounded priorities. The claims for rights to mobility rely on locally articulated priorities for better conditions of inhabitance, yet with a transversal reliance on a shared sense of threat and vulnerability, and on the representations of a community (whether local or multi‐scalar), enabling changes in the physical framing of mobility.

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)0.009
metaresearch head score (Gemma)0.013
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 score0.115
Threshold uncertainty score0.603

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0260.058
Scholarly communication0.0130.004
Open science0.0030.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.136
GPT teacher head0.410
Teacher spread0.274 · 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

Citations13
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Urban and Regional ResearchSame topicFrench Urban and Social StudiesFrench-language works237,207