On the Move: Trajectories of Stressors and Rewards Among Relocating Couples
Bibliographic record
Abstract
Partnered relocation—when couples move to support one partner’s career—is increasingly common and involves unique stressors and rewards. In a longitudinal study of 206 couples ( N = 383, 177 dyadic, 29 individual reports) surveyed 2-months pre-relocation and 3-, 6-, 9-, and 12-months post-relocation, we examined how stressors and rewards change over time, comparing experiences of partners who initiate (relocators) versus support the move (accompanying partners). Using dyadic latent growth curve modeling of stressors and rewards across 12 domains (e.g., careers, social networks, living arrangements, and logistics), we found that most stressors declined, and several rewards increased over time, with some differences between relocators and accompanying partners. We also explored the role of gender, COVID timing, move distance, socioeconomic status, and relationship satisfaction as covariates of the trajectories. This study highlights how couples adapt during relocation depending on relational and contextual factors.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".