Organizational Leadership Competencies for Public Health System Governance: A Scoping Review
Bibliographic record
Abstract
CONTEXT: Organizational leadership is essential for adequate and stable financing, strong governance across jurisdictions and sectors, and a competent public health workforce for effective and resilient public health systems. While there have been some efforts to characterize leadership competencies at the individual level, more focus is needed to understand effective governance of public health organizations and systems through the lens of leadership competencies at the organizational level. OBJECTIVE: To identify organizational level leadership competencies for effective and equitable public health governance. DESIGN: This scoping review included published academic literature from Scopus, Web of Science, Medline, and ProQuest and grey literature from Google Scholar, Canadian Government websites, Trove, FedSys, and Open Grey, published between 2004 and 2023. The search strategy focused on the concepts of governance, leadership, and pub-lic health organizations. An inductive-deductive approach informed the analysis using reflexive thematic analysis and a framework outlining the six functions of public health governance. RESULTS: A total of 35 records were included for analysis; 22 academic and 13 grey literature records. This review identified 9 themes describing organizational leadership competencies for public health governance: 1) Systems thinking 2) Public policy development, implementation and evaluation, 3) Partnership and collaboration, 4) Equity and justice 5) Organizational learning, 6) Oversight, 7) Resource stewardship, 8) Legal authority, 9) Organizational ethics. CONCLUSIONS: This scoping review contributes to our understanding of the leadership competencies needed to enact and sustain effective governance at an organizational level. These identified themes and associated competencies can facilitate the creation of organizational culture and values that align with effective governance tenets in public health. Additional research is needed to further apply and contextualize these competencies in different countries and public health settings.
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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 | 0.016 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".