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Record W2143315962 · doi:10.1177/0042098013493479

The Spatial Puzzle of Mobilising for Car Alternatives in the Montreal City-region

2013· article· en· W2143315962 on OpenAlexaffabout
Sophie L. Van Neste, Laurence Bhérer

Bibliographic record

VenueUrban Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsEconomic geographyFetishismContext (archaeology)PoliticsRegionalism (politics)SociologyScale (ratio)Regional scienceDiversity (politics)Focus (optics)Spatial contextual awarenessPolitical scienceGeographyCartographyAnthropologyLaw

Abstract

fetched live from OpenAlex

Scholars have recently advocated going beyond a fetishism for one spatiality to consider a diversity of socio-spatial relations in the study of political mobilisation. The objective of this article is to propose an operationalisation of the four spatialities framework (networks, scale, place and territory) and use it in an investigation of the mobilisation for car alternatives in the Montreal city-region. The approach is to start with the spatiality and structure of the network, to identify brokers and focus on them for the detailed analysis of scale, territory and place. The article sheds light on the particular assets which the use of each spatiality, and their combination, offers for mobilisation in the city-regional context. The findings also illustrate how city-regionalism is experienced by civic actors building coalitions to defend specific causes.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.591

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.081
GPT teacher head0.320
Teacher spread0.239 · 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

Citations2
Published2013
Admission routes2
Has abstractyes

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