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Record W7162071916 · doi:10.82308/49013

Perceived Racism and Mental health: A look at the role of Gender and Socio-Economic-Status as potential moderators of this link in Canadian Caribbean Adolescents

2005· dissertation· en· W7162071916 on OpenAlexaboutno aff
Steven Michael Green

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsRacismMental healthModerationPsychometrics of racismPrejudice (legal term)Suicide prevention

Abstract

fetched live from OpenAlex

The present investigation had two main objectives (1) to assess the effects of socio-economic-status, perceived racism & gender on Caribbean adolescent mental health and (2) to examine the moderator effect of S.E.S and gender on the link between perceived racism and mental health. (N=118) Caribbean families from Montreal participated in the study. Racism and adolescent mental health was assessed using the Personal Experience of Racism Scale, Youth Self Report & Child Behavior Check-List. Results highlighted the complex relationship between perceived racism and mental health as the model associated with gender and perceived racism predicted 22% of the variance on internalizing symptoms (R2=0.22). Specifically, results revealed that males externalized while females both internalized and externalized their experiences of racism. It is hypothesized that females may be more affected because parents may spend more time racially socializing their sons, as they are believed to be more heavily targeted for racism than black females.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.322
Teacher spread0.309 · 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 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

Citations0
Published2005
Admission routes1
Has abstractyes

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