Psychological Adjustment of Expatriate Children in Cultural Transitions
Bibliographic record
Abstract
The aim of the current study was to define the factorial structure of the psychological adjustment (PA) of Finnish expatriate children (EC) and to construct a model consisting of three child-level variables (age, school success, and attitude toward moving). Survey data concerning Finnish EC (N = 324) who had lived temporarily abroad were gathered from the EC’s parents. The mean age of the children was 4.8 years in the expatriation context and 8.2 years in the repatriation context. PA was examined using the Zung Self-Rating Depression Scale (ZSDS). Survey data were subject to a confirmatory factor analysis (CFA) and structural equation modeling (SEM). A hypothesized two-factor structure (physiological and affective factors) of PA was fitted for the sample using the CFA. A SEM of PA was presented, where the child-level explanatory variables were the age of the child, school success, and attitude toward moving. The main findings were the following: First, there is a two-factor structure of Finnish EC’s PA with both physiological and affective factors. Second, a model of PA with three child-level variables (age, school success, and attitude toward moving) was constructed. The results contribute to the understanding of PA in general and EC’s PA in particular. This study increases our understanding of EC’s PA in unique and novel contexts of dual cultural transitions. This comprehension is important in an increasingly globalized world, especially in clinical and other support contexts, where professionals work for children’s mental well-being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".