The relationship between work‐role characteristics and intercultural transitional adjustment domain patterns among a sample of US and Canadian expatriates on assignment in Ireland
Bibliographic record
Abstract
Borrowing from earlier contributions in the cross‐cultural management and international human resource management literatures, firstly we conceptualise expatriate adjustment as a multifaceted construct encompassing work, general, interaction and overall adjustment and then we examine the impact of work‐role characteristics in the form of role novelty, role ambiguity, role conflict and role overload on these different domains of adjustment. With respect to adjustment, while our data, drawn from a postal survey of US and Canadian expatriates on assignment in Ireland, show some variations in work, general, interaction and overall adjustment, the composite measure of overall adjustment reveals that, on the whole, respondents are well adjusted to working and living in Ireland. Turning to the impact of work‐role characteristics on adjustment domains, role novelty is positively correlated with work adjustment. Both role ambiguity and role conflict are negatively correlated with work adjustment. Multiple regression results reveal that, combined, role novelty, role ambiguity, role conflict and role overload account for 31.1 per cent of the variance in work adjustment, 13.4 per cent of the variance in general adjustment, 17.2 per cent in the case of interaction adjustment and 17.5 per cent of the variance in overall adjustment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".