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Record W3165582307 · doi:10.1177/00131245211004553

Safety and Inner City Neighborhood Change: Student and Teacher Perspectives

2021· article· en· W3165582307 on OpenAlexafffundabout
Sejal Patel, Miad Ranjbar, Tawnya C. Cummins, Natalie Cummins

Bibliographic record

VenueEducation and Urban Society · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of CanadaRyerson University
KeywordsRelocationMetropolitan areaSociologyInner cityPsychologyCriminologyPublic relationsPedagogyEconomic growthPolitical scienceSocioeconomicsGeography

Abstract

fetched live from OpenAlex

The introduction of mixed-income communities in public housing neighborhoods is a common revitalization strategy in metropolitan areas in North America. This study investigates student and teacher perspectives on safety in a Canadian inner city and marginalized neighborhood undergoing revitalization, alongside the redesign of a local school. The displacement of families and students, tied to housing relocation and student school mobility, resulted in increased concern around bullying, school safety, and displacement of place-based familiarity and social bonds. While most students felt safe at school, they were acutely aware of community level violence, criminal and gang activity in the neighborhood, and racial stereotyping. Students were also generally skeptical that revitalization would address the root causes of violence. The findings support the importance of including children's voices when planning, implementing, and evaluating policy initiatives that directly affect their lives.

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 score0.019
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.419
Teacher spread0.370 · 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

Citations4
Published2021
Admission routes3
Has abstractyes

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