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Record W7134998133

Tracing the Roots of Racial Profiling: Gender Bias, Socio-Economic Factors, and Police Encounters With Black Youth in Toronto's Eglinton West

2025· other· en· W7134998133 on OpenAlexaboutno aff
Tenisha Keyana Noel

Bibliographic record

VenueYorkSpace (York University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsGentrificationCommunity organizingMasculinityMainstreamIntersectionalityRacializationNeighbourhood (mathematics)Police brutalityIndigenous
DOInot available

Abstract

fetched live from OpenAlex

This study critically investigates the intersection of race, gender, and socio-economic status in shaping the policing experiences of Black youth in Toronto’s Eglinton West, with a specific focus on the Toronto Police Service’s 13 Division. Drawing on Critical Race Theory and Intersectionality, this research explores how systemic biases, urban spatial politics, and institutional practices contribute to the over-policing and criminalization of Black youth in a historically Black neighbourhood undergoing rapid socio-economic transformation. Through a mixed-methods approach, including an in-depth conversation with a community worker and historical-spatial analysis of census data, this study provides insight into how enduring stereotypes of Black masculinity and the invisibilization of Black femininity produce distinct forms of state violence. These experiences are compounded by economic marginalization, racialized surveillance practices such as carding, and the erosion of community spaces due to gentrification. A comparative analysis with Jane and Finch highlights how policing dynamics and community experiences differ across historically Black neighbourhoods in Toronto. While Eglinton West has experienced significant gentrification and displacement pressures, Jane and Finch’s high-rise environment shapes distinct patterns of surveillance, social isolation, and community resilience. Contrasts in local infrastructure, social spaces, and cultural hubs reveal how the urban environment interacts with systemic biases to produce varied forms of state violence and community coping mechanisms. By situating these policing practices within broader historical and policy frameworks, the research identifies how racial profiling persists despite legal reforms and public scrutiny. Ultimately, the study offers evidence-based policy recommendations centred on equity, community empowerment, and transformative justice, highlighting the need for structural change in both policing and social investment to address the compounded vulnerabilities faced by Black youth in urban Canadian contexts.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.228
Teacher spread0.205 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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