Linking institutional context to the community and career embeddedness of skilled migrants: The role of destination and origin country identifications
Bibliographic record
Abstract
Abstract \n \nMigration is one of the most pressing global issues of our time. However, relatively little is known about the factors and mechanisms that govern the post-migration experiences of skilled migrants. We adopt an acculturation- and social identity-based approach to examine how differences between institutional characteristics in the destination and origin country, as well as migrants’ experiences with formal and informal institutions shape their identification with the destination and origin country and contribute to their community and career embeddedness. Our study of 1709 highly skilled migrants from 48 origin countries in 12 destination countries reveals that the institutional environment migrants encounter provides both sources of opportunity (potential for human development and value-congruent societal practices) and sources of disadvantage (experienced ethnocentrism and downgrading). These contrasting dynamics affect migrants’ destination-country identification, their origin-country identification and, ultimately, their embeddedness in the destination country. Our results have important implications for multinational enterprises and policy makers that can contribute to enhancing skilled migrants’ community and career embeddedness. For example, these actors may nurture a work environment and provide supportive policies that buffer against the institutional sources of disadvantage we identified in this study, while helping migrants to leverage the opportunities available in the destination country. \n \nPlain language summary \n \nMigration is a pressing worldwide issue, yet there is limited understanding of the factors that influence the experiences of skilled migrants (individuals who move from one country to another, often for work or education) after they relocate. This study investigates how differences between institutional characteristics (the characteristics of a country's social, economic, and political systems) in the destination (the country to which a person migrates) and origin country (the country from which a person migrates), as well as migrants' experiences with these institutions, influence their identification (feeling of belonging or association) with the destination and origin country and contribute to their community and career embeddedness (the degree to which they feel integrated and established in their community and profession). The study involved 1709 highly skilled migrants from 48 origin countries in 12 destination countries. The researchers used datasets from the UNDP’s Human Development Index (a summary measure of average achievement in key dimensions of human development) and the GLOBE database (a research program studying cross-cultural management) to measure institutional and societal influences. They also developed new measures to capture migrants’ experiences and their identification with the destination and origin countries. The results revealed that migrants who moved to a country that offered better opportunities for human development and societal practices (the way a society behaves, operates, and functions) that were more aligned with their values had higher destination-country identification and were more embedded in their communities and careers. However, migrants who experienced occupational downgrading (reduction in job status or pay) or ethnocentrism (belief in the superiority of one's own ethnic group) in the destination country had lower destination-country identification and were less embedded. The researchers concluded that while destination-country identification is crucial for achieving high levels of community and career embeddedness, origin-country identification also matters, but not in the way predicted by acculturation research (study of how individuals adopt the cultural traits of another group). They suggested that future research should investigate the experiences of migrants moving from an economically developed to a less developed country and test the proposed relationships between opportunities for development and country identifications. This study has significant implications for migration policies and practices. It suggests that governments and organizations need to consider not only the economic opportunities they offer to migrants but also the societal practices and experiences that shape migrants' identification with the destination country. This could help to enhance skilled migrants' community and career embeddedness and increase their retention in the destination country.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".