New Directions in Facilitating and Supporting Stigmatized Conversations in the Workplace
Bibliographic record
Abstract
Although concealable stigmatized identities are fundamental to individual identity and carry positive benefits for the individual when shared with others, individuals are still hesitant to disclose such identities in the workplace due to risk of social devaluation and negative stereotypes. As such, given the taboo nature of such identities, employees with concealable stigmatized identities often grapple with the decision whether to disclose their identity at work or keep their identity hidden, and how to effectively manage workplace relationships and social interactions at work. In an effort to further understand how people navigate such disclosures and subsequent relationships in the workplace, the papers in this symposium highlight various concealable stigmatized identities and examine: (a) what motivates individuals to disclose their concealable identities; (b) what disclosure strategies exist for specific identities; (c) how employees navigating work relationships in relation to their identities; and (d) how individuals engage in identity work to understanding one’s identity. Understanding Menstruation Motives and Disclosures in the Workplace: A Mixed Methods Investigation Author: Aqsa Dutli; Purdue U., West Lafayette Author: Allison S. Gabriel; Purdue U., West Lafayette Bipolar Disorder Disclosure: How Identity Management and Educational Affiliation Matter Author: Janice Yue-Yan Lam; Schulich School of Business, York U. Author: Jean-Marc Moke; York U. Author: Brent John Lyons; Schulich School of Business, York U. Author: Daniel S. Samosh; Queen's U. Lessons on How Social Interaction Norms Become Stigmatized Through the Lens of Workers with Autism Author: Tiffany Dawn Johnson; Georgia Institute of Technology Author: Aparna Joshi; Ross School of Business, U. of Michigan Author: Mary Eve Speach; U. of Georgia Caste System in North America: An Intersectional Examination of Overlapping Systems of Power at Work Author: Barnini Bhattacharyya; Ivey Business School Author: Aparna Joshi; Ross School of Business, U. of Michigan
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| 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".