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Record W4385707066 · doi:10.1080/10714413.2023.2240686

“It’s not a system that’s built for me”: Black youths’ unbelonging in Ontario schools

2023· article· en· W4385707066 on OpenAlexfundaboutno aff
Charlotte Akuoko-Barfi, Henry Parada, Laura González Pérez, Marsha Rampersaud

Bibliographic record

VenueThe Review of Education Pedagogy & Cultural Studies · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council
KeywordsFeelingDisadvantagedRacismGender studiesGeneral partnershipCritical race theorySociologyFocus groupQualitative researchPsychologyPedagogyPolitical scienceSocial psychologySocial science

Abstract

fetched live from OpenAlex

Through exploration of Black Caribbean youths’ feelings of unbelonging and exclusion in Ontario schools, this paper argues that how Whiteness is systemically engrained in the education system negatively affects the learning experiences of Black youth due to predetermined measures of belonging. The present article draws on data from 32 qualitative interviews and four focus groups with 23 Black Caribbean youth. Findings reveal challenges youth commonly face when navigating relationships with peers and educators that hinder their academic success. These challenges are exacerbated for youth who are also involved in the state’s child protection system. Participants described feeling disadvantaged in the education system due to perceptions that they are academically unprepared and thus unable to excel. Through a Critical Race Theory and Anti-Black Racism analytical framework, the findings illustrate how systemic barriers coupled with the normalization of low expectations impact the educational success and opportunities of Black Caribbean youth in Ontario schools.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.169
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.303
GPT teacher head0.539
Teacher spread0.236 · 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 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

Citations3
Published2023
Admission routes2
Has abstractyes

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