The Influence of Multiculturalism and Assimilation on Work-Related Outcomes: Differences Between Ethnic Minority and Majority Groups of Workers
Bibliographic record
Abstract
This study aims at acquiring knowledge on how to manage ethnic diversity at work in order to promote work-outcomes in minority and majority groups of workers. We tested a model on how assimilation and multiculturalism, endorsed at an organizational level, predict job satisfaction and intention to quit through a mediation role played by the identification of workers with both the organization and their ethnic group simultaneously (i.e., dual identity). We hypothesized that the indirect effects of multiculturalism on work outcomes via dual identity are stronger for minority and those of assimilation are stronger for majority. Data came from 261 employees who responded to an online survey. 77 were of foreign origin (minority group) and 184 were of Belgian origin (majority group). Both assimilation and multiculturalism relate positively to work-related outcomes for both groups. However, multiculturalism through dual identity has the most beneficial outcomes for workers of the minority group. Our findings highlight the need to take ethnic and identity issues in account when studying work outcomes in culturally diverse organizations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".