Come abroad with me: the role of partner characteristics and couple acculturation gaps on individual psychological adjustment
Bibliographic record
Abstract
Although many individuals migrate to a new country with their romantic partner, most acculturation research has focused on individual factors related to migration-related psychological adjustment without considering couple influences. The current research investigates traditional predictors of psychological adaptation – mainstream and heritage acculturation, motivation to migrate, and perceived discrimination – from the perspective of both migrants and their partners. Participants were 151 French migrant couples (n = 302) living in Canada. We conducted mixed-effects regression analyses (HLM) predicting psychological adaptation within an actor-partner interdependence modelling framework. In line with past results, actors’ motivation to migrate and mainstream acculturation were positively associated with psychological adaptation, whereas perceived discrimination was negatively associated with it. Contrary to our hypotheses, the actor’s heritage acculturation was negatively associated with psychological adaptation. Above and beyond these individual-level predictors, our results revealed a positive effect of partner’s motivation to migrate and a negative effect of partner’s perceived discrimination. Finally, acculturation gaps were significantly associated with psychological adaptation. Mainstream acculturation gaps seem to be detrimental to migrants’ psychological adaptation, whereas heritage acculturation gaps were associated with greater psychological adaptation. These findings underscore the necessity to better understand how romantic relationship dynamics following migration play out in individual-level migration outcomes.
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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 | 0.002 | 0.005 |
| 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) | 0.002 | 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".