The Anatomy of Leadership: From Aspirational to Dark Side Leadership Traits
Bibliographic record
Abstract
Leadership is all about others on your team and in your organization. Surgical professionals are most likely to follow leaders they trust to care about their professional and personal well-being and are aligned with their values while setting and implementing organizational strategy. Ironically, in order to lead others well, it is best and most effective if leaders are humble, vulnerable, and willing to learn more about themselves, specifically their behavioral tendencies when they both are at their best and when they are under duress. For us as leaders, this includes understanding our own predominant leadership style(s) and learning how to expand our leadership-preferred tendencies to other styles that may be more effective in certain situations. The POSNA Leadership Program enables participants and faculty to study effective leadership principles and theories; evaluate published examples of exceptional and disastrous leadership in volatile, uncertain, complex, and ambiguous real-life situations; and have an in-depth dialog on how pediatric orthopaedic surgery leaders can learn from and positively model exemplary leadership characteristics and behaviors. Although our operating rooms, clinics, research, and administrative areas are not battlefields, and we are healers, not warriors, we and the teams we lead do face uncertain, ambiguous, complex, and even volatile situations, often enough to require the implementation of those refined, high-level skills. Key concepts: (1)Like all leaders, surgeons have preferred leadership styles. Learning about, expanding, and adapting leadership style(s) to specific situations is important and impactful.(2)The most effective leaders are humble, have high integrity, think strategically, and are decisive decision makers after input from their trusted professional teams.(3)Trust is the essential ingredient of leading successful teams and organizations. Building trust requires empathy, high task competency, and the ability to actively listen and engage in dialog before and during implementation of plan(s).(4)Volatile, uncertain, complex, and ambiguous dilemmas and challenges occur. Leaders and teams who can manage stress, mobilize necessary resources, and respond in a timely fashion to each volatile, uncertain, complex, and ambiguous situation are most effective.(5)Disruptive behaviors in our profession are more common than ideal. Responding to unprofessional acts, managing perceptions, and redirecting to acceptable behavior lessen safety risks for patients and improve team performance and professional well-being.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".