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Record W2322006537 · doi:10.1177/1466138113513526

‘You’re making our city look bad’: Olympic security, neoliberal urbanization, and homeless youth

2013· article· en· W2322006537 on OpenAlexafffundabout
Jacqueline Kennelly

Bibliographic record

VenueEthnography · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEthnographySociologyUrbanizationNeoliberalism (international relations)ReputationGender studiesCriminologyEconomic growthPolitical economySocial scienceAnthropology

Abstract

fetched live from OpenAlex

Drawing on ethnographic research with homeless and street-involved youth in Vancouver before, during, and after the 2010 Olympic Games, this article offers a portrait of neoliberal urbanization as experienced by a city’s most marginalized residents. Taking as paradigmatic the aspirational goals of Olympic host cities to enhance their reputation as ‘global cities’, the article explores what this means for homeless youth through three processes: city cleansing, city marketing, and self-regulation. Examining how each of these are imbricated with policing and security practices, the article offers an in-depth look at how these abstractions are lived by homeless youth in the everyday. The article concludes by suggesting that marginalized young people are not the beneficiaries of Olympic legacies, despite promises made by organizing committees. In contrast, findings indicate that homeless young people are further marginalized by the Olympics, providing support for previous research that aligns mega-events with neoliberal outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.073
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.309
Teacher spread0.273 · 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 teacher head, 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

Citations40
Published2013
Admission routes3
Has abstractyes

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