The Other(’s) Toronto Public Art: The Challenge of Displaying Canadians’ Narratives in a Multicultural/Diasporic City
Bibliographic record
Abstract
Cet article explore les controverses sévissant autour de quelques oeuvres permanentes d’art public commémoratif, commandées ou financées par le public ou le privé, qui ont été érigées à Toronto afin de représenter des récits nationaux et extranationaux associés à des communautés ethnoculturelles. À travers l’analyse de plusieurs études de cas, nous démontrons comment et pourquoi la population immigrante au Canada, en pleine augmentation et diversification, a une incidence sur la gestion de l’art public commémoratif dans ce pays. En conclusion, nous recommandons l’adoption de pratiques contemporaines en art public comme un moyen de commémorer autrement et de maintenir la cohésion sociale dans une ville multiculturelle et diasporique comme Toronto.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.026 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".