Bibliographic record
Abstract
Newcomers should give up their cultural traditions and become more like everybody else. Thls was the position of a majority of Québecers polled by Leger Marketing for the Association for Canadian Studies1 a year after Bouchard and Taylor released their report. Further, the trend line of anxiety about and resistance to incorporating other cultures became worse in the year after the B-T Report came out. Forty per cent of francophones viewed non-Christian immigrants as a threat to Québec society, compared with 32 per cent in 2007, while only 32 per cent of non-francophones harboured the same fears, a figure that declined compared with 34 per cent in 2007. B-T clearly did not change the attitudes of francophone, allophone, or anglophone Québecers, except perhaps to exacerbate Québécois' fears. Why did this occur? Why the enhanced anxiety? Some explain minority fears in terms of group economic insecurity. Antonius Rachad argued that 'Focusing on cultural differences is the wrong approach.'' What minorities really want and need is both equality of opportunity and results. Economic integration produces change. But the polls suggest other more important factors -age, for example. Fifty-six per cent of 18-to 24-year-olds polled approved wearing hijabs in public schools, but only 30 per cent of those 55 and over agreed. The linguistic group to which an individual belongs also counts. Sixty-three per cent of non-francophones approve wearing headscarves in public schools, but only 32 per cent of French-speakers agreed. And only 25 per cent of francophones thought they had a responsibility to make a greater effort to accept minority groups' customs, while 74 per cent of non-francophones thought they should make a greater effort.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.066 | 0.008 |
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".