Kulturell tilpasning og karriereoppnåelse. En studie om sammenhengen mellom psykologiske faktorer og høyt utdannede innvandrere sin karriereoppnåelse
Bibliographic record
Abstract
Statistics and research indicates that immigrants experience more challenges advancing their careers than Norwegian-born in work life. The purpose of this study was to investigate predictors for career advancement amongst immigrants with higher education. Cultural distance, acculturation (orientation towards Norwegian culture), and so-called multicultural personality traitswere used as predictors. Career advancement was operationalized as satisfaction with own career, income and leadership. The sample consisted of 199 former and current participants of Global Future, which is a career development program for highly educated immigrants. The participants answered an online questionnaire consisting of the measurement instruments: Vancouver Index of Acculturation and Multicultural Personality Questionnaire. Cultural distance was measured according to Schwartz's cultural value orientations for the respondents’ country of origin. The results of the regression analysis showed that the value orientations hierarchy and embeddedness were negatively related to respectively career satisfaction and income. The personality trait social initiative was positively related to leadership. The results suggest that cultural distance is more important for career advancement among immigrants with higher education than orientation towards Norwegian culture and multicultural personality.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".