Perceived ethnic discrimination and social exclusion: Newcomer immigrant children in Canada.
Bibliographic record
Abstract
This article examines relationships between perceived ethnic discrimination, social exclusion, psychosocial functioning, and academic performance among newcomer immigrant children from the People's Republic of China, Hong Kong, and the Philippines using a subsample from the New Canadian Children and Youth Study of children aged 11-13 years (1,053) living in Montreal, Toronto, Vancouver, and the Prairies. Bivariate analysis showed that 25% of children reported being treated unfairly by peers and 14% by teachers because of who they are. Regression analyses revealed that perceived ethnic discrimination by peers and teachers was negatively related to children's sense of social competence in peer relationships. Children's self-esteem and sense of academic competence were negatively related to perceived discrimination by teachers. One in 5 children reported feeling like an outsider, with boys revealing higher levels of psychological isolation than girls. More than 1 in 10 were socially isolated and reported never participating in organized activities. This may reflect economic exclusion, as over one third of respondents belonged to families living below the Canadian Income Adequacy Measure. Psychological isolation, social isolation, and economic exclusion were significant predictors of children's sense of academic competence and actual academic grades. Variations exist across age, sex, ethnicity, family structure, parental education, region of settlement, and length of time since arrival in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".