Opening Up: New Theory and Evidence on the Role of Self-Disclosure in Organizations
Bibliographic record
Abstract
Sometimes described as ‘opening-up’, self-disclosure, or the act of sharing personal/relevant information with another party is acknowledged in psychology as an important interpersonal behavior. Despite this evidence on the importance of self-disclosure, research on self-disclosure in organizations is sparse. In recent years there is rising interest in the study of self-disclosure in the workplace. Often viewed as a positive behavior to show goodwill, the effects of self-disclosure on organizational outcomes at various levels have received little empirical and theoretical attention from management scholars. This symposium explores the interpersonal and group effects of self-disclosure on employees at both the individual, interpersonal, and group levels. The symposium consists of four papers—one theory, two field studies, and one experimental study—that explore the effects of self-disclosure and its role in organizations. Specifically, the first paper offers new theoretical insights about the gendered effect of self-disclosure in the context of remote working and what that means for careers. Also fuelled by the use of remote working, the second paper investigates self-disclosure concerning individual leaders’ perceptions of loneliness. The third paper explores the effects of self-disclosing virtually, private medical information about suffering from remote work conditions during the COVID-19 pandemic, and a group of colleagues. It uses experimental vignettes to investigate the potential benefits of virtual self-disclosure to a group of colleagues regarding private medical information. The final paper delves deeper into employees’ position to self-disclose. It examines the role of self-stigmatization in the relationship between employee mental health disease diagnoses and employee decisions to self-disclose. These papers advance our understanding of the effects of self-disclosure at various levels in organizations. We believe the symposium is a step toward uncovering the importance of self- disclosure and will encourage future research. Self-Disclosure in Today’s Remote World of Work: Understanding the Consequences for Women’s Careers Author: Marie-Helene Elizabeth Budworth; York U. Author: Paolo Fragomeni; York U., Toronto Don’t Leave Accountable Leaders Alone: The Role of Self-Disclosure at Work Author: Hodar Lam; U. of Amsterdam Author: Shuai Yuan; U. of Amsterdam Author: Wang Zhuojun; Institute of Psychology, Chinese Academy of Sciences The Effects of Self-Disclosure on In-Group Identification: A COVID-19 Vignette Study Author: Avery Thomson; Epic Author: Emre Yetgin; Rider U. Author: Quinn Cunningham; Rider U. The Role of Self-Stigma in the Disclosure Decision of Employees with Mental Health Disabilities Author: Mahshid Khademi; U. of St. Gallen (HSG) Author: Sophie Theresa Schep; U. of St. Gallen Author: Nicola Glumann; U. of St. Gallen
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".