Why Do Racial Slurs Remain Prevalent in the Workplace? Integrating Theory on Intergroup Behavior
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Racial slurs are prevalent in organizations; however, the social context in which racial slurs are exchanged remains poorly understood. To address this limitation, we integrate three intergroup theories (social dominance, gendered prejudice, and social identity) and complement the traditional emphasis on aggressors and targets with an emphasis on observers. In three studies, we test two primary expectations: (1) when racial slurs are exchanged, whites will act in a manner more consistent with social dominance than blacks; and (2) this difference will be greater for white and black men than for white and black women. In a survey (n = 471), we show that whites are less likely to be targets of racial slurs and are more likely to target blacks than blacks are to target them. We also show that the difference between white and black men is greater than the difference between white and black women. In an archival study that spans five years (n = 2,480), we found that white men are more likely to observe racial slurs than are black men, and that the difference between white and black men is greater than the difference between white and black women. In a behavioral study (n = 133), analyses showed that whites who observe racial slurs are more likely to remain silent than blacks who observe slurs. We also find that social dominance orientation (SDO) predicts observer silence and that racial identification enhances the effect of race on SDO for men, but not for women. Further, mediated moderation analyses show that SDO mediates the effect of the interaction between race, gender, and racial identification on observer silence.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it