Identity construction of Black Canadian youth in multicultural settings
Bibliographic record
Abstract
The question of what does it mean to be black in Canada has been approached from many different perspectives. In this thesis, I explore several different narratives of blackness in light of narratives of authenticity for black youth, narratives of acceptable blackness, and nation-building discourses in the institutions of media and education. I interview four youth who have participated in race-based cultural groups. I contend that these groups offer particular narratives of blackness that resist the limits placed on black identities by current stereotypes that are continually referenced in popular culture and nation-building discourses. Using an antiracist framework informed by critical race studies and diasporic perspectives of identity, I examine the ways in which the discourses the respondents access in the interviews challenge, confirm or resist the nation-building discourses within media and education and the stereotypes of blackness circulated via popular culture.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.047 | 0.013 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".