A systemic approach to developing frontline leaders in healthcare
Bibliographic record
Abstract
PURPOSE: The purpose of this case study is to extend the understanding of leadership development in healthcare by documenting the impact of a systemic approach to developing frontline leaders in a large Canadian healthcare organization. DESIGN/METHODOLOGY/APPROACH: A total of 92 participants working in acute and community settings participated in an eight-day certificate program that combined classroom instruction, practical skill development, and applied projects. Program content was based on a learning needs assessment conducted with potential participants and their supervisors. FINDINGS: Frontline leaders and their supervisors rated the program positively in terms of its impact on participants' confidence and willingness to lead, awareness of leadership opportunities, communication, problem solving, response to conflict, and the ability to support their teams through change. It was also found, however, that supervisors' ratings were generally lower than those of participants. PRACTICAL IMPLICATIONS: Systemic approaches to leadership development offer healthcare the best chance of addressing the current leadership crisis. The challenge is finding innovative ways to demonstrate sustainable benefits in an industry that is struggling to address cost pressures. In the present study, personal and supervisor evaluations were used in conjunction with completion of applied change projects to demonstrate a tangible return on investment. ORIGINALITY/VALUE: Leadership can be learned and there is no better point of entry for development than those in frontline leadership positions. However, developing future leaders requires the commitment of an entire leadership community. Healthcare organizations that are experiencing leadership gaps must be prepared to make a long term investment if they want to achieve lasting healthcare reforms.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".