Perceived loneliness: Why are Syrian refugees more lonely than other newly arrived migrants in Germany?
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
Abstract Migration often impacts the mental and emotional health of those needing to move from their home countries. Studies have focused on migrants’ levels of distress or well-being, and recent research looks at older migrants’ experience with loneliness. What has yet to be researched is how different migrant groups experience loneliness, and how these feelings are affected by the contexts of leaving one country and reception in another. Drawing on the theoretical framework of integration, this article asks whether newly arrived refugees in Germany differ in their perception of loneliness from other newly arrived migrants. It examines these perceptions as related to social contacts and the context—and interplay—of exit and reception. Using OLS regressions with data from the Recent Immigration Processes and Early Integration Trajectories in Germany (ENTRA) project, we find that Syrian refugees have higher levels of loneliness than migrant groups from Poland, Italy, and Turkey. The difference is largely attributable to Syrians not having local German contacts, surviving traumatic experiences at home, and migrating specifically for physical safety. We also find that discrimination and not being in the labor force are determinants of loneliness across all four groups, and that even when considering migrant origins and other effects, having local social contacts lowers levels of loneliness. Our results point to migration policies, such as those related to family reunification and labor market access, for producing inequalities in loneliness between Syrian refugees and other migrants in Germany.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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