Do White Women Gain Status for Engaging in Anti-black Racism at Work? An Experimental Examination of Status Conferral
Bibliographic record
Abstract
Abstract Businesses often attempt to demonstrate their commitment to diversity, equity, and inclusion (DEI) by showcasing women in their leadership ranks, most of whom are white. Yet research has shown that organizations confer status and power to women who engage in sexist behavior, which undermines DEI efforts. We sought to examine whether women who engage in racist behavior are also conferred relative status at work. Drawing on theory and research on organizational culture and intersectionality, we predicted that a white woman who expresses anti-Black racism is conferred more status in the workplace than a white woman who does not. A pilot study ( N = 30) confirmed that making an anti-Black racist comment at work was judged to be more offensive than making no comment, but only for a white man, not a white woman. Study 1 ( N = 330) found that a white woman who made an anti-Black racist comment at work was conferred higher status than a white woman who did not, whereas the opposite held true for a white man, with perceived offensiveness mediating these effects. Study 2 ( N = 235) revealed that a white woman who made an anti-racist/pro-Black Lives Matter comment was conferred lower status than a white woman who did not, whereas the opposite held true for a white man. Finally, Study 3 ( N = 295) showed that people who endorse racist and sexist beliefs confer more status to a white man than to a white woman regardless of speech, but that people low in racism and sexism confer the highest status to a white woman who engages in anti-Black racist speech. These studies suggest that white women are rewarded for expressing support for beliefs that mirror systemic inequality in the corporate world. We discuss implications for business ethics and directions for future research.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".