The dimensions and degree of second-generation incorporation in US and European cities: A comparative study of inclusion and exclusion
Bibliographic record
Abstract
This research compares cities between and within the United States and Europe with respect to their dimensionality and degree of immigrant incorporation. Based on theoretical perspectives about immigrant incorporation, structural differentiation and national incorporation regimes, we hypothesize that more inclusionary (MI) cities will show more dimensions of incorporation and more favorable incorporation outcomes than less inclusionary (LI) places, especially in regard to labor market and spatial variables. We use data from recent major surveys of young adult second-generation groups carried out in Los Angeles, New York, and 11 European cities to assess these ideas. The findings indicate that second-generation immigrants in New York (MI) and in European MI places (i.e. cities in the Netherlands, Sweden and France) show greater dimensionality of incorporation (and thus by implication more pathways of advancement) respectively than is the case in Los Angeles (LI) or in European LI places (i.e. cities in Austria, Germany, and Switzerland). We discuss the significance of these results for understanding how the structures of opportunity confronting immigrants and their children in various places make a difference for the nature and extent of their 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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".