“Canadian-First”: Mixed Race Self-Identification and Canadian Belonging
Bibliographic record
Abstract
Not being read or identified by others as “Canadian” was a common thread in semi-structured in-depth interviews I conducted with 19 young adults of mixed race in a Western Canadian urban context. In this paper, I address moments of (in)ability for people of mixed race to claim “Canadian.” Mixed race people have a complex relationship with identifying and narrating their identities as “Canadian” through the operation of race and ethnicity in the Canadian context, and because of ambivalent and contradictory readings of their bodies. I found that they deploy the term in three ways: by expressing a sense of being “Canadian-first,” by stating that there exists an understanding that “Canadian means white,” and by strategically using the term “Canadian” in their interactions with others, signaling an active appropriation of the term. However, none of these deployments are mutually exclusive: they overlap and bleed into each other, playing off and impacting one another. This paper adds to nascent Canadian Critical Mixed Race studies and also redresses a gap in the literature on “Canadian identity” by examining how the ability to claim “Canadian” is racialized through a consideration of the experiences of mixed race people. Le fait de ne pas être lus ou identifiés par d’autres comme “Canadiens” était le dénominateur commun dans les entrevues semi-structurés que j’ai menées en profondeur avec 19 jeunes adultes de races mixtes dans un contexte urbain de l’Ouest Canadien. Dans cet article, je mets en exergue les moments d’ (in)aptitude des personnes de races mixtes de se réclamer “Canadiens”. Les gens de races mixtes ont une relation complexe avec l’identification et la narration de leurs identités en tant que “Canadiens”, à cause des perceptions ambivalentes et contradictoires de leurs corps. J’ai trouvé que ceux-ci déploient leur terme de trois façons: en exprimant le sens d’être “Canadien en premier”, en affirmant qu’il existe une compréhension du “Canadien qui veut dire Blanc” et en usant stratégiquement du terme “Canadien” dans leur interactions avec les autres, signalant une appropriation active du ce terme. Cependant, aucuns de ces déploiements ne s’excluent mutuellement: ils se chevauchent et s’empiètent entre eux, jouant au large et s’impactant l’un de l’autre. Ce papier s’ajoute aux études critiques canadiennes naissantes sur les races mixtes et répare aussi une lacune dans la littérature des “identités canadiennes”, en examinant comment l’aptitude de se réclamer “Canadien” est radicalisée à travers une considération des expériences des personnes de races mixtes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".