Bibliographic record
Abstract
This chapter explores several cases where the constitution and/or constitutional policy specifically denigrates or stigmatises a people by defining them as &s;other&s;, as non-citizens, as unworthy of possessing or incapable of handling civic rights. European imperialism was the classic example of non-recognition applied on a global scale. It assumed the cultural superiority of the imperial overlord, and the cultural inferiority of the subject people. It would be incorrect to convey the impression that Euro-Canadians invariably look down upon Indians, but it would be equally misleading to pretend that Indians are not a stigmatised people within Canadian society. The strong constitutional affirmation of Britishness was reinforced by the assimilating doctrine of anglo-conformity outside Quebec that assumed the absorption of immigrants into the English-speaking majority in terms of both language and cultural norms. Searchers for the counter-case in Canada of demeaning, or stigmatic, or negative recognition find their example in the status Indian population.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".