Pathways of Black immigrant youth in Québec from secondary school to university: Cumulative racial disadvantage and compensatory advantage of resilience
Bibliographic record
Abstract
This article analyzes the educational pathways of Black Canadian immigrant students in Québec with Sub-Saharan African and Caribbean backgrounds. Both racialized groups have been targets of educational and social discrimination and segregation, which compromise their educational pathways. The results obtained from the longitudinal data however, show that some of these students are able to overcome such obstacles. Although they are more susceptible to experiencing major academic difficulties and lag due to grade repetition, and less likely to attend private institutions or to be admitted to enriched programs in public schools, these students have access to college in a proportion comparable to that of their peers whose parents are non-immigrants. This supports the hypothesis of resilience put forward by some authors such as Krahn and Taylor (2005) regarding Canadian students from Sub-Saharan African and Caribbean immigrant families. However, the situation is somewhat reversed with regard to obtaining a college diploma and access to university. They are less likely to have entered university and obtained a postsecondary diploma 10 years after entering secondary school. From this perspective, the resilience hypothesis should be nuanced. In short, their educational pathways are characterized by a dynamic of interaction between the cumulative disadvantage of belonging to a racialized minority and the compensatory benefit of resilience.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".