Migrant selectivity in risk orientation and language proficiency: A comparative study of recent refugees and other immigrants in Germany
Bibliographic record
Abstract
Classical notions suggest that immigrants tend to be more risk-taking than those who remain in their country of origin, but conditions of forced migration may limit this selectivity. Identifying systematic personality differences between refugees and other immigrants is crucial, as traits such as risk orientation may contribute to differences in integration behavior. This study investigates selectivity in risk orientation among refugees from the IAB-BAMF-SOEP Survey of Refugees in Germany and other immigrants from the IAB-SOEP Migration Sample, and examines its role in language acquisition through growth curve models. The selectivity measures are based on data from the World Values Survey for the population in immigrants’ countries of origin. The findings show no systematic differences in selectivity in risk orientation by migration motive; instead, the degree of selectivity varies by country of origin. In terms of language proficiency growth, the longitudinal findings indicate that individuals selected in risk-taking demonstrate greater improvements in language skills, as increased exposure to German through daily interactions, language courses, and labor market participation accumulates throughout their stay in the receiving country.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".