International Migration and the Economics of Language
Bibliographic record
Abstract
This paper provides a review of the research on the economics of language' as applied to international migration. Its primary focuses are on: (1) the effect of the language skills of an individual on the choice of destination among international (and internal) migrants, both in terms of the ease of obtaining proficiency in the destination language and access to linguistic enclaves, (2) the determinants of destination language proficiency among international migrants, based on a model (the three E's) of Exposure to the destination language in the origin and destination, Efficiency in the acquisition of destination language skills, and Economic incentives for acquiring this proficiency, (3) the consequences for immigrants of acquiring destination language proficiency, with an emphasis on labor market outcomes, and in particular earnings. Factors that are considered include age, education, gender, family structure, costs of migration, linguistic distance, duration in the destination, return migration, and ethnic enclaves, among others. Analyses are reported for the immigrant experiences in the US, Canada, Australia, the UK, Germany, Israel and Spain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".