Reactive Adjustment or Proactive Embedding? Multistudy, Multiwave Evidence for Dual Pathways to Expatriate Retention
Bibliographic record
Abstract
The dominant perspective on expatriation characterizes the process as a continuing adaptation to existing job demands on an international assignment. Another, less studied perspective, emphasizes that expatriates can initiate tactics to acquire task, interpersonal, and affective resources for shaping their assignment experiences. Adopting a positive organizational scholarship lens and drawing on the job demands–resources model, we simultaneously examine both of these reactive demand‐based and proactive resource‐based pathways to expatriate retention. We propose that cross‐cultural uncertainty demands and expatriate‐initiated resource acquisition tactics both influence adjustment and embeddedness. Thus embeddedness works alongside adjustment to drive expatriates’ plans to remain in the international position, which in turn leads to actual retention. Using evidence from 2 separate panel studies (one with 2 waves and the other with 4 waves of data), we demonstrate the importance of the resource‐based pathway for expatriate assignments.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".