Bibliographic record
Abstract
Abstract Immigrants can face insurmountable odds in their acculturation to the new society, and subsequently suffer from poor emotional/mental health. Using immigrant data from the United States, Australia, and Western Europe, this paper tests the relationship between immigrant religious involvement and emotional well‐being. Results demonstrate that regular religious participation is associated with better emotional/mental health outcomes. Conversely, non‐religious group involvement (i.e., ethnic associations, leisure groups, work groups) do not have as equally a positive association with emotional well‐being. This pattern is consistent across all countries examined in this study, suggesting that religion has a unique relationship with immigrant emotional well‐being regardless of national context. Therefore, it is posited that in easing the emotional/mental adjustment of immigrants, religion is not an artifact of context or of a particular religious group, but a generality of immigrant adaptation. Policy implications for the study’s findings are discussed. Yet to him, in his troubled state, Christianity brought also the miracle of redemption. Poor thing that he was, his soul was yet a matter of consequence. For him the whole drama of salvation had been enacted: God had come to earth, had suffered as a man to make for all men a place in a life everlasting. Through that sacrifice had been created a community of all those who had faith, a kind of solidarity that would redress all grievances and right all wrongs, if not now, then in the far more important aftermath to life. ( Handlin, 1973 [1951]:93 )
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".