Multiculturalism and Interculturalism
Bibliographic record
Abstract
Explores the critical debate between multicultural and intercultural approaches in both political theory and practice Both interculturalism and multiculturalism address the question of how states should forge unity from ethnic, cultural and religious diversity. But what are the dividing lines between interculturalism and multiculturalism? This volume brings together some of the most prominent scholars in the field to address these two different approaches. With a Foreword by Charles Taylor and an Afterword by Bhikhu Parekh, this collection spans European, North-American and Latin-American debates. Key Features Discusses cases from Australia, Belgium, Great Britain, Canada, Québec, Spain, Catalonia, Québec and several Latin American cases Combines policy analysis and theoretical analysis Contributors Gérard Bouchard • Ted Cantle • Alain-G. Gagnon • Raffaele Iacovino • Will Kymlicka • Geoffrey Brahm Levey • Patrick Loobuyck • Nasar Meer • Tariq Modood • Bhikhu Parekh • Ana Solano-Campos • Charles Taylor • Ricard Zapata-Barrero Find Out More Visit the editors' webpages to learn more about their work Nasar Meer Tariq Modood Ricard Zapata Barrero "
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".