Immigration policy, assimilation of immigrants, and natives' sentiments towards immigrants: evidence from 12 OECD countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
'As in the U.S. and Canada, migration is a controversial issue in Europe. This paper explores the possibility that immigration policy may affect the labor market assimilation of immigrants and hence natives' sentiments towards immigrants. It first reviews the assimilation literature in economics and the policy approaches taken in Europe and among the traditional immigration countries. Second, a new analysis of individual data from the OECD countries studies sentiments concerning immigration and the determinants of these sentiments is presented. Natives in countries that receive predominantly refugee migrants are relatively more concerned with immigrations impact on social issues such as crime than on the employment effects. Natives in countries with mostly economic migrants are relatively more concerned about loosing jobs to immigrants. However, the results also suggest that natives may view immigration more favorably if immigrants are selected according to the needs of the labor markets. Possible benefits of such a policy are that it may moderate social tensions in regards to migration and contribute to a better economic performance of the respective countries.' (author's abstract)
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it