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Record W2063494253 · doi:10.1080/14733285.2015.1026875

Young people's cartographies of school choice: the urban imaginary and moral panic

2015· article· en· W2063494253 on OpenAlexaboutno aff
Ee‐Seul Yoon

Bibliographic record

VenueChildren s Geographies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsnot available
Fundersnot available
KeywordsThe ImaginaryMoral panicScholarshipEthnographySociologyGender studiesSchool choiceCriminologyPsychologyPolitical scienceAnthropologyPsychoanalysisLaw

Abstract

fetched live from OpenAlex

A critical geography of school choice illuminates how parental school choice reproduces unequal urban conditions. This paper contributes to this scholarship by arguing that the reproduction of urban spaces is reinforced by the ways the dominant urban imaginary shapes how youths imagine and organise their school options. I draw from the fields of critical geography, school choice, and sociology of moral panic to theorise how children's geographies are informed by the dominant urban imaginary and reconstituted reiteratively by moral anxiety. Through this lens, I analyse ethnographic data collected on school choice policy, along with interviews with 59 youth (ages 11–19) in Vancouver, Canada. My analysis demonstrates that the dominant forms of classed stigmatisation of marginalised urban schools are important to young people's rejection of those schools. My analysis also shows that moral panic and rising fears of violence underwrite the spatial patterns of youth participation in school choice.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0130.036
Scholarly communication0.0100.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.286
Teacher spread0.260 · 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

Citations26
Published2015
Admission routes1
Has abstractyes

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