Facing Cancelation: Bias Confrontation Strategy Impacts Interpersonal Perceptions and Behaviors
Bibliographic record
Abstract
Four talks explore antecedents and consequences of various prejudice confrontation strategies, for the victims, offenders, and observers. The first talk explores the political divide in rank-and-file employee support for psychological safety in organizations, which has implications for support for organizational policies aimed at confronting prejudice and maintaining organizational psychological safety. The next talk describes how two common confrontation strategies, calling in versus canceling an offender, can affect organizational psychological safety and resulting employee voice. The third talk explores how, when, and why high-profile people make professional comebacks following their cancelations, and finds that such individuals attempt to destigmatize themselves by testing the waters for a comeback in several distinct ways. Finally, the fourth talk discusses how perceived power is impacted when harassers apologize (vs. deny) their sexual misconduct and demonstrates how perpetrator apologies can shift power from the perpetrator to the victim and impact willingness to advocate for the victim. Together, these talks highlight potentially unexpected consequences and tradeoffs to various methods of confronting prejudice. Political Ideology, Purpose of Business Beliefs, & Support for Psychological Safety Author: Rajen Anderson; University of Leeds Author: Krishnan Nair; Boise State University Author: Maryam Kouchaki; Northwestern University Confronting Workplace Prejudice: Calling In Increases Psychological Safety More Than Canceling Author: Michael Rosenblum; Author: Zachariah Berry; University of Southern California Author: Juliana Schroeder; University of California Berkeley Shifting the Spotlight: How Workers Attempt Comebacks After Public Stigmatization Author: Samantha Martinez; Author: Erin Frey; Yale University Author: Gabrielle Adams; University of Virginia Author: Scott Wiltermuth; University of Southern California Transferring Powerfrom the Victimizer to the Victimized Author: Rachael Goodwin; Not Associated Author: Samantha Dodson; University of Calgary Author: Kristina Diekmann; The University of Utah
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".