Are Muslim immigrants assimilating? Cultural assimilation trajectories in immigrants’ attitudes toward gender roles in Europe
Bibliographic record
Abstract
As public attitudes toward gender roles in Western societies become increasingly liberal, Muslim immigrants and their children in Europe are regarded as conservative and unassimilated. This study treats acculturation as a process by which immigrants and their children shift from the attitude distribution in their origin country to that of their settlement country, and distinguishes the influence of Islam and origin-country gender norms on Muslim immigrants’ and their children’s gender role attitudes. Using data on gender role attitudes from 32 European settlement countries and 98 origin countries, the study models the relative influence of origin and settlement contexts on 25,220 first- and second-generation immigrants in Europe. Similar to previous studies, this study finds that Muslim immigrants have more traditional gender role attitudes than non-Muslim immigrants when controlling for the effect of origin-country gender norms. However, there is no evidence that Muslims are more attached to their origin country’s gender norms than non-Muslims. Instead, Muslim immigrants’ attitudes about gender norms are more similar to those in the settlement society than those of non-Muslim immigrants: Unlike their foreign-born parents, second-generation Muslims are as liberal as non-Muslim populations. Taken together, these results suggest that second-generation Muslims are adopting mainstream European gender norms.
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.
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 | 0.003 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".