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New Insights into the Role of Virtue in Leadership Emergence and Effectiveness

2024· article· en· W4400444144 on OpenAlexaffabout
Addison Maerz, Pauline Schilpzand, Christian Kiewitz, Nate Zettna, Yashuo Chen, Yanhong Li, Su Kyung Kim, Patrick Liborius, Anna Faber, Helena Nguyen, Anya Johnson, Nicky Cheung, Lei Zhu, Chunjiang Yang, Jane O’Reilly, Laurent Lapierre, Yujie Zhan

Bibliographic record

VenueAcademy of Management Proceedings · 2024
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsWilfrid Laurier UniversityUniversity of Manitoba
Fundersnot available
KeywordsVirtuePsychologyPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

This symposium presents new insights into the role of virtue in leadership. Despite increased attention on moral-based leadership in both academic research and popular press, important questions remain about how virtues such as courage and humility inform leader practices as well as perceptions of existing and emergent leaders. Our symposium aims to expand our understanding of virtues in leadership contexts by 1) exploring how virtues such as courage shape proximal antecedents of leader emergence (e.g., expected leader effectiveness, perceived leader-like qualities), 2) identifying antecedents of virtuous leader behaviors (e.g., expressed humility), 3) extending research on the outcomes of virtuous leader behaviors to team-level outcomes (e.g., team silence), 4) testing boundary conditions that enhance or constrain the extent to which leaders exhibit humility (e.g., psychological closeness), and 5) integrating research on organizational virtuousness and follower moral identity. Leveraging multiple theories, methods, analytical levels, and perspectives of leaders and employees from four continents, these papers contribute to an expanded view of effective leadership that emphasizes both competence (being a good motivator of people) and virtue (pursuing worthy goals, in the right way, for the right reasons). Are the Powerful Behaving (Un)humbly? It Depends on How Close They Feel to their Team Author: Patrick Liborius; - Author: Christian Kiewitz; U. of Dayton Author: Anna Faber; Justus-Liebig-U. Giessen How Teams Can Overcome Silence: The Roles of Humble Leadership and Team Commitment Author: Nate Zettna; The U. of Sydney Author: Helena Nguyen; U. Of Sydney Author: Pauline Schilpzand; Oregon State U. Author: Anya Madeleine Johnson; U. Of Sydney The Moral Fabric of Meaningful Work: A Study of Workplace Virtuousness and Moral Identity Author: Yashuo Chen; School of Business, Sun Yat-sen U. Author: Nicky Cheung; Schulich School of Business, York U. Author: Lei Zhu; U. of Manitoba Author: Chunjiang Yang; Yanshan U. The ‘Hero’ among Us: Acts of Moral Courage and Emergent Leadership Author: Yanhong Li; Odette School of Business, U. of Windsor Author: Jane O'Reilly; Telfer School of Management, U. of Ottawa Author: Laurent Lapierre; Telfer School of Management, U. of Ottawa Author: Addison Maerz; California Polytechnic State U., San Luis Obispo Does Breaking Rules Make You a Good Leader? Pro-Coworker Rule Breaking and Leadership Potential Author: Su Kyung Kim; U. of Manitoba Author: Yujie Zhan; Wilfrid Laurier U.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0060.006
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.040
GPT teacher head0.308
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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