Shifts in Research on Global Mobility
Bibliographic record
Abstract
Abstract This chapter provides a brief historical review and discusses seven major shifts that reflect contemporary expatriation research. The first shift concerns changing conceptualizations of the expatriation construct itself. Second, the portfolio of mobility options has been widening, with a matching shift in terminology from “managing expatriation” to “managing global mobility.” Third, there is a notable shift from research that centers on expatriates themselves to research that accounts for other stakeholders, notably expatriate family members and members of the local community. Fourth, the definition of “expatriate success” has evolved to encompass a much more diverse set of variables going beyond traditional indicators, such as expatriate turnover. Fifth, what repatriation is and how repatriation is managed are also changing. The last two changes reflect shifts in, respectively, theory and methodological approaches, suggesting a widening pool of theoretical lenses and increasing methodological sophistication. Our chapter concludes with a discussion of key theoretical principles and practical implications derived from our review.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".