Equity, Diversity, and Inclusion in Organizations: What Impact does Leader Identity Have?
Bibliographic record
Abstract
Leader role schemas as well as aspirations for leadership are shaped by stereotypes embedded and reinforced in a cultural context often at an unconscious level. Efforts towards gender equality in leader roles are generally targeted either at the organizational level or at the individual level, but rarely is an integrated approach used. Leader identity offers such an integrated approach where mechanisms of individual leader identity development are understood within the stereotype embedded context. Steele (2010) suggests that environments are organized by social identities and that contingencies and cues about a setting’s inclusivity can add or counter identity threats that speak to marginality. The papers presented in this symposium offer organizations and individuals new narratives of leader identity by focusing on aspects of leader identity that are not primed by gender, race, age, or other social identities: critical mass, leader uniqueness, leader character, leader moral identity, and granted versus claimed leader identity. Critical Mass and the Multiplicity of Gender in Leadership Presenter: Yvonne Benschop; Radboud U. Nijmegen Diversifying Leadership through Leaders Development of Others Identity Uniqueness Presenter: Amy Randel; San Diego State U. Presenter: Kim Jaussi; Binghamton U.-State U. of New York Developing Leader Character: Does Gender or Context Matter? Presenter: Marlene Janzen Le Ber; Brescia U. College Presenter: Lucas Monzani; Ivey Business School Team Age Diversity, Leader Moral Identity, and Perceived Team Outcomes Presenter: Yang Yang; Rowan U. Presenter: Xinhui Wu; China U. of Political Science and Law The Double-Edged Sword of Being Both a Woman and a Leader An Identity Perspective Presenter: Alyson Byrne; Memorial U. of Newfoundland Presenter: Ingrid Chadwick; Concordia U.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".