Multiculturalism and Interculturalism: debating the dividing lines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Explores the critical debate between multicultural and intercultural approaches in both political theory and practiceBoth 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 FeaturesDiscusses cases from Australia, Belgium, Great Britain, Canada, Québec, Spain, Catalonia, Québec and several Latin American casesCombines policy analysis and theoretical analysisContributorsGérard 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-BarreroFind Out MoreVisit the editors' webpages to learn more about their workNasar MeerTariq ModoodRicard Zapata Barrero
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it