Multiculturalism in crisis? Rhetoric vs, policy changes in the new century (cases of Canada and the United Kingdom)
Bibliographic record
Abstract
According to the recent speeches of David Cameron and some other European politicians, multiculturalism has failed and it is necessary to make significant changes in immigration and integration policies. In Canada, however, multiculturalism is still a state policy, which is widely supported by the general public. The bachelor's thesis Multiculturalism in crisis? Rhetoric vs. policy changes in the new century (cases of Canada and the United Kingdom) is trying to answer a question if the critical rhetoric of British politicians has triggered real policy changes towards ethnic minorities and immigrants or if it only follows the changes that were started before they came to power. In Canada, the thesis is trying to learn, if the rhetoric supporting multiculturalism does not omit some policy changes, that would be in contradiction towards the original idea of multiculturalism. The author claims that multiculturalism in Canada has much deeper roots than in the UK and that the Canadian model differs signifiantly from the one in Britain. These facts directly affect the rhetoric of politicians, for whom is the criticism of multiculturalism not advantageous. The current Canadian government therefore does not reflect in its rhetoric on its current policy changes, that are in contradiction towards the original...
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.041 | 0.046 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".