The Relations of Immigrant‐Specific and Immigrant‐Nonspecific Daily Hassles to Distress Controlling for Psychological Adjustment and Cultural Competence<sup>1</sup>
Bibliographic record
Abstract
In separating immigrant‐specific daily hassles (out‐group, family, and in‐group) from immigrant‐nonspecific general hassles, the relations of hassles to depression and physical symptoms were examined. The respondents were 79 female and 85 male Iranian immigrants to Canada. In Block 1 of a hierarchical multiple regression analysis, the experience of out‐group hassles and of general hassles both contributed to the prediction of depression. In Block 2, psychological adjustment and perceived cultural competence in the host society, along with out‐group hassles, predicted depression. General hassles were the only predictor of physical symptoms. Psychological adjustment, as a buffer, interacted with hassles in enhancing the prediction of distress. The importance of distinguishing and accounting for both immigrant‐specific and immigrant‐nonspecific hassles in predicting outcome measures was considered, as was the importance of assessing dispositional variables in this context.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".