Host country nationals as socializing agents: a social identity approach
Bibliographic record
Abstract
Abstract A major challenge facing Multinational Enterprises (MNEs) is finding ways to increase the success rates of managers assigned overseas. Our paper draws upon social identity theory to develop a model that focuses on the role of host country nationals (HCNs) in determining the adjustment of expatriate managers. Specifically, our model proposes attributes of the expatriate and the HCN that can increase the salience of national identity and outgroup categorization of expatriates by the HCNs. We also suggest how outgroup categorization interacts with a number of situational factors to influence the role of HCNs as socializing agents for expatriate newcomers. Finally, we propose that the socializing behaviors HCNs may display or withhold from the expatriate will affect the adjustment of the expatriate. Our model highlights the often‐overlooked partners in the expatriate adjustment process and emphasizes the need for MNEs to be cognizant of the social dynamics between HCNs and expatriates in the host location. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".