Legal Integration of Islam: A Transatlantic Comparison
Bibliographic record
Abstract
The status of Islam in Western societies remains deeply contentious. Countering strident claims on both the right and left, Legal Integration of Islam offers an empirically informed analysis of how four liberal democracies—France, Germany, Canada, and the United States—have responded to the challenge of integrating Islam and Muslim populations. Demonstrating the centrality of the legal system to this process, Christian Joppke and John Torpey reject the widely held notion that Europe is incapable of accommodating Islam and argue that institutional barriers to Muslim integration are no greater on one side of the Atlantic than the other. While Muslims have achieved a substantial degree of equality working through the courts, political dynamics increasingly push back against these gains, particularly in Europe. From a classical liberal viewpoint, religion can either be driven out of public space, as in France, or included without sectarian preference, as in Germany. But both policies come at a price—religious liberty in France and full equality in Germany. Often seen as the flagship of multiculturalism, Canada has found itself responding to nativist and liberal pressures as Muslims become more assertive. And although there have been outbursts of anti-Islamic sentiment in the United States, the legal and political recognition of Islam is well established and largely uncontested. Legal Integration of Islam brings to light the successes and the shortcomings of integrating Islam through law without denying the challenges that this religion presents for liberal societies.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".