Mexican Immigrant Political and Economic Incorporation
Bibliographic record
Abstract
As the United States begins the twenty-first century, it remains the world's leading immigration country. In 2000 (the latest year for which migration data are available on a global basis) the United States was home to almost 35 million legal and unauthorized migrants, or 2.7 times as many as any other country. Although other nations have higher proportions of foreign-born residents (e.g., nearly 25 percent in Australia and 20 percent in Canada), the globally dominant position of the United States in regard to numbers of new immigrants reinforces its self-image as a “nation of immigrants,” as does the fact that immigration is generally seen as contributing to the country's economic and demographic strength. However, over the past three decades, more and more new arrivals with non-European origins have come to the country (more than four-fifths are Latino and Asian), many with very low levels of education and illegal status at entry. These changes have fueled public concerns and led to heated debates over whether U.S. admissions and settlement-related policies ought to be modified.Frank D. Bean is Professor of Sociology (fbean@uci.edu), Susan K. Brown is Assistant Professor of Sociology (skbrown@uci.edu),and Rubén G. Rumbaut is Professor of Sociology at University of California, Irvine (rrumbaut@uci.edu). Some of the research results reported in this paper come from a research project entitled “Immigration and Intergenerational Mobility in Metropolitan Los Angeles” and supported by a grant from the Russell Sage Foundation.
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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 | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".