Public health leadership: Competencies to guide practice
Bibliographic record
Abstract
In 2013, the Community Health Nurses of Canada in partnership with the Canadian Institute of Public Health Inspectors and the Manitoba Public Health Managers Network received funding from the Public Health Agency of Canada to develop a set of interdisciplinary leadership competencies for seven public health disciplines. The Leadership Competencies for Public Health Practice in Canada project comprised a multimethod research approach that included a scoping literature review, on-line survey, webinar-based focus groups, and a modified Delphi process. The 49 leadership competencies for public health practice were organized according to the LEADS Canada capabilities. The leadership competencies extend the core public health competencies and discipline-specific competencies and reflect foundational values of public health. The leadership competencies can be applied to professional development pathways, mentoring programs, and performance appraisals to advance public health practice. How these competencies have been enacted by public health leaders during the COVID-19 pandemic is discussed.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".