Not all Disclosures are Created Equal: Employee Ratings of Leader Effectiveness After Disclosure
Bibliographic record
Abstract
Most empirical research on voluntary disclosures of concealable stigmatized identities in the workplace has focused on employee populations of stigma holders. Early leader-focused results suggest employee evaluations of leaders are negatively affected when leaders disclose a concealable stigmatized identity. The current research aims to improve our understanding of factors that may attenuate or reverse these negative perceptions. Using experimental vignettes, I examined employee reactions to leader disclosures of concealable stigmatized identities. Independent variables including leader gender and disclosure content (Study 1a, n = 478), discloser identity (Study 1b, n = 422), and group prototypicality (Study 1c, n = 365) were manipulated to determine how differing disclosure contexts affected employee ratings of leadership effectiveness. Across studies, leader gender and discloser identity did not play a significant role in follower ratings of leader effectiveness, but disclosure content and group prototypicality did. Post-hoc testing showed that leaders who disclosed minority sexual orientation received the highest ratings of leadership effectiveness - higher than leaders who did not disclose a stigmatized identity. Leaders who disclosed substance abuse received the lowest ratings of leadership effectiveness. In terms of group prototypicality, highly prototypical leaders received the highest ratings of leadership effectiveness. Theoretical and practical implications are discussed.
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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 | 0.004 | 0.023 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".