Canadian University Acknowledgment of Indigenous Lands, Treaties, and Peoples
Bibliographic record
Abstract
At many Canadian universities it is now common to publicly acknowledge Indigenous lands, treaties, and peoples. Yet, this practice has yet to be considered as a subject of scholarly inquiry. How does this practice vary and why? In this paper we describe the content and practice of acknowledgment, linking this content to treaty relationships (or lack thereof). We show that acknowledgment tends to be one of five general types: of land and title (British Columbia), of specific treaties and political relationships (Prairies), of multiculturalism and heterogeneity (Ontario), of no practice (most of Quebec), and of people, territory, and openness to doing more (Atlantic). Based on these results, we conclude that the fluidity of acknowledgment as a practice, including changing meanings depending on the positionality of the acknowledger, need to be taken into account. Plusieurs universités Canadien pratique une reconnaissance des territoires, des traités, et des peoples autochtone en publique. Cette pratique, cependant, n'a jamais été considérée comme une enquête savante. Dans ce projet nous regardons comment les reconnaissances varie par institution et pourquoi. Nous trouvons qu'il y a un lien entre le contenu des reconnaissances et les relations traité. On démontre cinq forme des reconnaissances: territoire et titre (Colombie britannique); traité spécifique and les relations politiques (Prairies); multiculturalisme et hétérogénéité (Ontario); l'absence (la majorité du Québec); et des peoples, territoire et volonté a plus faire (Atlantique). Nous concluons que la fluidité de la reconnaissance, comme pratique, est fluide et doit prendre en considération la position de la personne qui le fait.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.013 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".