Mode of Difference and Resource for Resilience: How Religion Shapes Experiences of Discrimination of the Second Generation in France
Bibliographic record
Abstract
There are two sides to cultural practices such as religion: on the one hand, they connect families across generations and space and can embed resources. On the other, as is the case with Muslim immigrants in Europe, they can become markers of difference and create social distance. Drawing on data on the schooling experiences of children of immigrants in France and on information concerning their religious and linguistic family context when growing up, this article maps these two aspects. Although those growing up in Muslim families are significantly more likely to report discrimination than those from Christian or nonreligious families, neither the degree of religiosity nor the presence of parental home-country language was associated with the probability of reporting discrimination. However, for those growing up in Muslim families, a religious family environment seems to protect against negative reactions such as losing interest in academic matters, whereas no such effects are found in Christian families or for home-country language. These findings show that religion is not only a consequential symbolic barrier that Muslims encounter in Europe but also, for those who are religious, a resource to cope with experiences of exclusion — a constellation that may prove consequential for dynamics of integration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".