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Record W4408041384 · doi:10.1080/0145935x.2025.2469683

Confronting Afrophobia: A Phenomenological Inquiry on the Marginalization of African-Canadian Youth in Canadian Institutions

2025· article· en· W4408041384 on OpenAlexaffabout
Kuir ë Garang, Justin Nembhard, Uzo Anucha

Bibliographic record

VenueChild & Youth Services · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsToronto Metropolitan UniversityYouth Research and Evaluation eXchangeUniversity of TorontoYork University
Fundersnot available
KeywordsLived experienceSociologyPsychologyPedagogyPolitical sciencePsychotherapist

Abstract

fetched live from OpenAlex

In this qualitative paper, we address, from the perspectives of youth workers, how Afrophobia marginalizes African-Canadian youth in youth-serving organizations and institutions. Using phenomenology and online data from Youth Research and Evaluation Exchange (YouthREX’s)Footnote1 Virtual Café, we therefore interrogate from the above perspectives, how youth sector professionals (YSPs) including youth workers themselves, challenge or enable Afrophobia-caused youth marginality within the Ontario youth sector. With 1790 registered members, the Virtual Café is an online Community of Practice (CoP) forum hosted and moderated by YouthREX. Our findings show that culturally and socially conscious YSPs are vital in combating Afrophobia at the frontline and at the policy levels. The findings also highlight systemic obstacles faced by YSPs combating Afrophobia and the strategies they use to push back on these obstacles. Using these findings and phenomenology (as a self-responsible beginning), we highlight effective intervention strategies already used by some YSPs, and from our analysis.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.050
GPT teacher head0.305
Teacher spread0.255 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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