Is there really a backlash against multiculturalism policies? New evidence from the multiculturalism policy index
Bibliographic record
Abstract
In much of the western world, and particularly in Europe, there is a widespread perception that multiculturalism has ‘failed’ and that governments who once embraced a multicultural approach to diversity are turning away, adopting a strong emphasis on civic integration. This reaction, we are told, “reflects a seismic shift not just in the Netherlands, but in other European countries as well” (JOPPKE 2007). This paper challenges this view. Drawing on an updated version of the Multiculturalism Policy Index introduced earlier (BANTING and KYMLICKA 2006), the paper presents an index of the strength of multicultural policies for European countries and several traditional countries of immigration at three points in time (1980, 2000 and 2010). The results paint a different picture of contemporary experience in Europe. While a small number of countries, including most notably the Netherlands, have weakened established multicultural policies during the 2000s, such a shift is the exception. Most countries that adopted multicultural approaches in the later part of the twentieth century have maintained their programs in the first decade of the new century; and a significant number of countries have added new ones. In much of Europe, multicultural policies are not in general retreat. As a result, the turn to civic integration is often being layered on top of existing multicultural programs, leading to a blended approach to diversity. The paper reflects on the compatibility of multiculturalism policies and civic integration, arguing that more liberal forms of civic integration can be combined with multiculturalism but that more illiberal or coercive forms are incompatible with a multicultural approach.
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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 | 0.033 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".