Where Are We Now? A Content Analysis of Canadian Master of Public Health Course Descriptions and the Public Health Agency of Canada's Core Competencies
Bibliographic record
Abstract
OBJECTIVE: To examine the degree to which Master of Public Health (MPH) programs' course descriptions align with the Public Health Agency of Canada's (PHAC's) core competency categories in order to identify strengths and training gaps in such programs across Canada. METHODS: A content analysis of MPH programs in Canada was conducted from July 2019 to November 2019. A sampling frame of programs was obtained from a list from the PHAC Web site. Program information, including mandatory and elective course descriptions, was extracted from each program's Web site and analyzed in NVivo 12. Course descriptions were independently categorized by 2 researchers into 1 or more of the 7 categories of the core competencies outlined by the PHAC. RESULTS: We identified 18 universities with MPH programs with 267 courses across Canada. Thematic analysis revealed that 100% of programs had coursework that addressed the "Public Health Sciences" and "Assessment and Analysis" categories; 93% addressed "Policy and Program Planning, Implementation, and Evaluation"; 67% addressed each of "Communication," "Leadership," and "Partnerships, Collaboration, and Advocacy"; and only 56% had course descriptions addressing "Diversity and Inclusiveness." CONCLUSIONS: We find that Canadian MPH programs may lack course offerings addressing core competency categories relating to diversity and inclusiveness, communication, and leadership. Our findings were limited in scope as we relied on program Web sites; thus, further research should explore course content in more depth than this course description analysis allowed and identify ways to close the MPH curricular gaps we identified.
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How this classification was reachedexpand
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 | 0.024 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".