Embracing relational competencies in applying the LEADS framework for health-care leaders in transformational change and the COVID-19 pandemic
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The purpose of this paper is to assess the extent to which the LEADS Framework guided health-care leaders through organizational change and the COVID-19 pandemic in a western Canadian province. DESIGN/METHODOLOGY/APPROACH: A qualitative exploratory inquiry assessed the extent to which health leaders applied competencies that aligned with the LEADS Framework. A purposeful sample of 22 health-care leaders participated in the study representing senior, mid-level and front-line health-care leaders in various health-care organizations to ensure diverse representation of leader competencies. The authors conducted semi-structured interviews to collect the data and used Braun and Clarke's (2006) six-phase approach to guide data analysis. FINDINGS: The analysis suggests that health-care leaders found Engaging with Others and Developing Coalitions were the most critical themes of the LEADS Framework for change management and for navigating the COVID-19 pandemic. Findings reveal that during transformational change and a crisis context, leaders embrace relational approaches to adapt and improve performance in dynamic organizations. PRACTICAL IMPLICATIONS: These findings have implications for a relational approach to improve teamwork and decrease emotional strain; a focus on mobilizing and sharing power with nurses; and educational programs to advance relational and self-management skills, shared leadership, communication, change management, human resource and talent development as critical learning components for current and future health-care leaders. ORIGINALITY/VALUE: The LEADS Framework is used to examine how health-care leaders responded to transformational change in the organization while situated in a pandemic context.
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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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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 it