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Record W4296103555 · doi:10.3390/socsci11090420

Banishment through Branding: From Montréal’s Red Light District to Quartier des Spectacles

2022· article· en· W4296103555 on OpenAlexafffundabout
Rhianne Fiolka, Zack Marshall, Anna Kramer

Bibliographic record

VenueSocial Sciences · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of CalgaryMcGill University
FundersShandong Academy of SciencesMcGill University
KeywordsExpropriationSolidaritySex workAgency (philosophy)SociologyPublic spaceAutonomyResistance (ecology)Work (physics)Political sciencePublic relationsLawEngineeringSocial science

Abstract

fetched live from OpenAlex

This paper analyzes how the City of Montréal employed tools of urban planning—including a district plan, street redesign, rezoning, selective public consultation, expropriation, policing and surveillance—to spatially banish sex work from its historic district, using the red light symbol as a branding strategy. This coincided with a change in federal law (Bill C-36) and a policy shift to reposition sex workers as passive victims of sex trafficking. Using a case study design, this work explores the state’s refusal to recognize the agency of those engaged in embodied socio-economic exchanges and the safety and solidarity possible in public space. In interviews, sex workers described strategies of collective organizing, resistance and protest to hold the city accountable during this process of displacement. We consider how urban planning might support sex work, sex workers and economic autonomy.

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)0.002
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 score0.100
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.017
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.036
GPT teacher head0.319
Teacher spread0.283 · 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
Published2022
Admission routes3
Has abstractyes

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