Bibliographic record
Abstract
To those who study the integration of immigrants in Western countries, both Muslims and Canada are seen to be exceptions to the rule. Muslims are often perceived as unable or unwilling to integrate, mostly due to their religious beliefs; Canada is portrayed as a model for successful integration. This book addresses the intersection of these two types of exceptionalism through an empirical study of the experiences of Muslims in Canada. Drawing on data from large-scale surveys as well as face-to-face interviews, Kazemipur draws a detailed picture of four major domains of immigrant integration: institutional, media, economic, and social/communal. His findings indicate that the integration of Muslims in Canada is not problematic in the institutional and media domains. However, there are serious problems the economic and social domains, which need to be addressed. A fresh account of the lives and experiences of Muslim immigrants in Canada, this book gets at the roots of the so-called Muslim question in Canada. Replete with practical implications, the analysis shows that instead of fixating on religion, the focus should be on economic and social challenges faced by Muslims in Canada.
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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 | 0.037 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".