Redefining the Prototypical Leader: Exploring Non-Traditional Leaders at Work
Bibliographic record
Abstract
This presenter symposium focuses on non-traditional leaders at work while highlighting the need for research to go beyond the prototypical leader characteristics (e.g., white, male, able-bodied). The five papers in this symposium cover a range of non-traditional leader characteristics, including low socioeconomic status, women in the Middle Eastern/North African region, neurodivergence, presence of tattoos, and mental illness. The management field often neglects non-traditional leader characteristics such as these in favor of the prototypical leader stereotypes, which limits our understanding of how to promote more diversity in leadership roles by helping those with characteristics outside of the prototypical emerge as leaders and enhance their experiences and effectiveness as leaders. The research in this symposium covers not only a range of non-traditional leader characteristics but also a range of methods – archival data, interviews, focus groups, and experimental vignettes – and leadership experiences – leader emergence, relationships with followers, and followers’ perceptions of their leaders. Taken together, these papers and discussion led by Dr. Kara Arnold aim to extend leadership research beyond the prototypical leader characteristics to work towards more diverse and inclusive leaders and leadership. Early Life Socioeconomic Status Shapes Leadership Role Emergence in Adulthood Author: Steve Granger; Concordia University Author: Nick Turner; University of Calgary Barriers to Women’s Leadership in Iraq’s STEM Sector Author: Patil Yessayan; University of Ottawa Neurodivergent Leaders: Insights from LMX Theory Author: Joanna Szulc; Gdansk University of Technology Author: Douglas Renwick; Tattooed Employees: Does Hierarchical Position Matter for Observer Perceptions and (Mis)treatment? Author: Alyssa Grocutt; Author: Julian Barling; Queen's University The Consequences of Mental Illness Stigma in the Workplace: Does Organizational Role Matter? Author: Michaela Scanlon; Queen's University Author: Julian Barling; Queen's University
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".