Bibliographic record
Abstract
This book compares immigrant integration across key Western countries. Focusing on low-status newcomers and their children, it examines how they are making their way in four critical European countries—France, Germany, Great Britain, and the Netherlands—and, across the Atlantic, in the United States and Canada. This comparison reveals their progress and the barriers they face in an array of institutions—from labor markets and neighborhoods to educational and political systems—and considers the controversial questions of religion, race, identity, and intermarriage. The book sheds new light on questions at the heart of concerns about immigration. They analyze why immigrant religion is a more significant divide in Western Europe than in the United States, where race is a more severe obstacle. They look at why, despite fears in Europe about the rise of immigrant ghettoes, residential segregation is much less of a problem for immigrant minorities there than in the United States. They explore why everywhere, growing economic inequality and the proliferation of precarious, low-wage jobs pose dilemmas for the second generation. They also evaluate perspectives often proposed to explain the success of immigrant integration in certain countries, including nationally specific models, the political economy, and the histories of Canada and the United States as settler societies. This book delves into issues of pivotal importance for the present and future of Western societies, where immigrants and their children form ever-larger shares of the population.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.241 | 0.096 |
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".