Culture and identity and success in school: educating African Canadian youth
Bibliographic record
Abstract
This thesis examines the role of cultural identity in the education of minority students in the Ontario school system and how cultural identity impacts their scholastic success. The study focuses on the examination of the vast body of existing literature on cultural identity and the education of minority students within the Euro-American school system. It explores and identifies ways in which a strong cultural identity can enhance the learning outcomes for minority students. Educational research has shown that cultural identity plays a significant role in students' learning and academic achievement and that minority students who have strong cultural ties develop a strong sense of self and that these ties are important assets as they navigate their way through the Euro-American school system. The study has given major consideration to the relationship between language, culture and identity and success in school; it examines the effects of factors such as colonization on the identity of a large segment of students considered "minority" with a legacy of the Trans-Atlantic Slave Trade; the dominant culture; power, knowledge hegemonism/Eurocentrism on a global level as well as factors of the more immediate personal level of the home environment and theories and ideologies surrounding school; it examines an alternative approach to education and suggests strategies for enhancing the learning outcomes for minority students---i.e., the specified "some."
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".