Fomentar la ciudadanía en una sociedad multicultural: El multiculturalismo canadiense como un modelo político
Bibliographic record
Abstract
Well-meaning assimilationists, as well as those threatened that the predominantly English culture in Canada and the United States will be overwhelmed by cultural elements brought by ethnocultural immigrant groups with them, have led the strident attacks against multiculturalism in both countries. Though apparently persuasive, close analysis of these attacks in Canada shows that they are based on lack of understanding or ignorance of the multiculturalism policy. The policy can be understood best by making a distinction between a multination state, with sovereignty rights claimed by national groups within it, and a polyethnic state, with polyethnic rights claimed by its cultural minority groups. The Canadian policy of multiculturalism pertains to the latter. Analysis of its intent and its constituent principles reveals that it is consistent with the democratic ethos of the country; as well, its philosophy has found expression not only in official pieces of legislation but also in the constitutionally entrenched Canadian Charter of Rights and Freedoms. Litigation in the courts sustains the view that Section 27 of the Charter, drawing from this philosophy, has given recognition to, and protection for, the rights of ethnocultural members in the country. Indeed, in light of court decisions, and the philosophy behind the policy, there is no need to worry about a kind of multicultural education in which citizenship education occupies a prominent role.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.040 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".