A new wave of leaders: Early evaluation of the interdisciplinary Foundations of Leadership in Radiation Oncology (FLiRO) program
Bibliographic record
Abstract
Purpose: Effective leadership across all areas of radiation oncology (RO) is vital to fully realise the benefits of radiation therapy in cancer care. We report outcomes of a novel interdisciplinary leadership program designed for RO professionals under a global joint society initiative. Methods: The Foundations of Leadership in RO (FLiRO) program was designed for aspiring RO leaders. Initially delivered in a blended learning format, it was adapted to fully virtual in 2021. It comprised a webinar tutorial, on-line modules and homework followed by 'live' in-person/virtual workshops over an approximately 6-week period. Topics included personal awareness, effective teamwork, quality improvement skills, leading change and conflict management. An immediate post-program online survey was performed using Likert scales to measure self-reported educational value, interaction with others and the likely application of learning to practice. Open comments were invited. Results: 170 participants from 36 countries and 6 continents took part from 2018 to 2021 (99 doctors, 36 physicists, 32 radiation therapists/RTTs and 3 others). 141 (83%) participants responded to the post-program survey. Average weightings for responders' views on whether pre-determined learning objectives were met ranged from 4.30 to 4.61 on a 5-point scale (1 = 'not met at all' and 5 = completely met). For the question addressing potential value of learning for application to their workplace, 124 of 130 (95%) of responders indicated that FLIRO would be 'very useful' or 'extremely useful'. Conclusion: Initial evaluation of the FLiRO program supports its continuation and expansion with ongoing evolution based on emerging evidence around leadership education and participant feedback.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".