Complicating Non-Indigeneities and Other Considerations around Race in the Art and Design University
Bibliographic record
Abstract
Ce texte examine les complications de la nomenclature entourant la formation d’identités autochtones et non autochtones dans le milieu académique de l’art et du design. L’argument principal est que les contextes coloniaux historiques créent un système binaire où les non-Autochtones sont toujours perçus comme étant des colons blancs, effaçant ainsi les autres personnes racialisées et leur relation à l’autochtonéité. Ce texte historicise également la sous-représentation d’enseignant.e.s racialisé.e.s dans les écoles d’art et de design et cherche à identifier des modèles efficaces aptes à rectifier cette inégalité. Suivant les principes de la théorie critique raciale et intégrant une critique des études critiques blanches, ce texte aborde des possibilités d’actions en matière d’équité à la lumière de la Commission de vérité et de réconciliation, et s’achève avec de brefs exemples de projets pouvant illustrer une voie progressiste à suivre.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.053 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".