Psychological climate for diversity, racial/ethnic workplace discrimination, and prosocial voice behavior: the moderating role of social dominance orientation
Bibliographic record
Abstract
Purpose This study aims at expanding research on the antecedents, consequences, and boundary conditions associated with racial/ethnic discrimination in workplaces. Design/methodology/approach We collected longitudinal data from 826 employees affiliated with eight Canadian governmental organizations. Structural equation modeling was used to test the hypotheses through Mplus 7.4. Findings Social dominance orientation (SDO) moderated the relationship between psychological climate for diversity and perceived racial/ethnic workplace discrimination (REWD): the relationship was negative among low-SDO employees and turned positive among high-SDO employees. Additionally, perceived REWD was positively related to prosocial voice behavior among low-SDO employees but negatively among high-SDO employees. Furthermore, the indirect effect of climate for diversity on prosocial voice was positive for high-SDO employees but negative for low-SDO employees. Originality/value There has been little research examining the relationship between psychological climate for diversity and REWD. We show that a positive diversity climate lowers perceived REWD, with employee SDO as a key moderator. Additionally, we respond to calls to explore the behavioral implications of workplace discrimination and examine the relationship between perceived REWD and employee voice. We show that the nature of this relationship depends on employees’ SDO level.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".