Defining Clinical Public Health
Bibliographic record
Abstract
PURPOSE: To solve complex health issues, an innovative and multidisciplinary framework is necessary. The Clinical Public Health (CPH) Division was established at the University of Toronto (UofT), Canada to foster inte-gration of primary care, preventive medicine and public health in education, practice and research. To better understand how the construct of CPH might be applied, we surveyed clinicians, researchers and public health professionals affiliated with the CPH Division to assess their understanding of the CPH concept and its utility in fostering broad collaboration. METHODS: A two-wave anonymous survey of the active faculty of the CPH Division, UofT was conducted across Canada. Wave 1 participants (n = 187; 2016) were asked to define CPH, while Wave 2 participants (n = 192; 2017) were provided a synthesis of Wave 1 results and asked to rank each definition. Both waves were asked about the need for a common definition, and to comment on CPH. RESULTS: Response rates for the first and second waves were 25% and 22%, respectively. Of the six definitions of CPH from Wave 1, "the intersection of clinical practice and public health," was most highly ranked by Wave 2 participants. Positive perceptions of CPH included multidisciplinary collaboration, new fields and insights, forward thinking and innovation. Negative perceptions included CPH being a confusing term, too narrow in scope or too clinical. CONCLUSION: The concept of Clinical Public Health can foster multidisciplinary collaboration to address com-plex health issues because it provides a useful framework for bringing together key disciplines and diverse professional specialties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.009 | 0.069 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".