Defining the role of digital public health in the evolving digital health landscape: policy and practice implications in Canada
Bibliographic record
Abstract
<sec> <title>Introduction</title> In this article, we argue that current digital health strategies across Canada do not appropriately consider the implications of digital technologies (DTs) for public health functions because they adopt a primarily clinical focus. We highlight differences between clinical medicine and public health, suggesting that conceptualizing digital public health (DPH) as a field distinct from, but related to, digital health is essential for the development of DTs in public health. Focussing on DPH may allow for DTs that deeply consider fundamental public health principles of health equity, social justice and action on the social and ecological determinants of health. Moreover, the digital transformation of health services catalyzed by the COVID-19 pandemic and changing public expectations about the speed and convenience of public health services necessitate a specific DPH focus. This imperative is reinforced by the need to address the growing role of DTs as determinants of health that influence health behaviours and outcomes. Making the distinction between DPH and digital health will require more specific DPH strategies that are aligned with emergent digital strategies across Canada, development of intersectoral transdisciplinary partnerships and updated competencies of the public health workforce to ensure that DTs in public health can improve health outcomes for all Canadians. </sec>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".