Supporting a national public health workforce in obtaining core competencies
Bibliographic record
Abstract
Abstract The Core Competencies for Public Health in Canada: Release 2.0 are the knowledge, skills, attitudes and behaviors expected of all individuals working in any public health role, at any level, in Canada. The original competencies, released in 2008, recently underwent modernization, resulting in an updated set of 65 competencies across 10 categories, with applicability to public health in diverse countries and contexts. To support the development of these competencies across the public health workforce, ongoing professional development and workforce training will be needed. To support the public health community in achieving the modernized core competencies, the National Collaborating Centre for Methods and Tools (NCCMT) developed a curated list of learning resources mapped to the competency statements. An environmental scan was conducted to identify online courses, learning modules and workshops relevant to public health, and the Core Competencies for Public Health in Canada. These resources were then mapped to each of the competency statements. A web-based tool was developed, allowing users to quickly identify appropriate capacity-building resources related to specific competency categories or statements. This resource provides public health users with accessible opportunities for advancement toward achieving each core competency. A curated list of learning opportunities and resources to support competence achievement was developed to provide public health professionals with opportunities to build knowledge and skills toward each core competency. Rather than a comprehensive list of all available resources, resources were selected based on their accessibility, directness to the competency, and relevance to public health practice. The NCCMT's core competency self-assessment and curated resources list support public health professionals in achieving each core competency. Together, these resources support the advancements of quality and equitability of public health in Canada. Key messages • Core competency resources support achieving each core competency, to advance public health in Canada. • The Canadian public health core competencies and supporting resources are applicable to public health practice around the world.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".