A proposed core model of the new public health for a healthier collectivity: how to sustain transdisciplinary and intersectoral partnerships
Bibliographic record
Abstract
At present, there is no conceptual model by which public health could be represented as intersectoral governance collaborating with society and the state, and acting as a collective on the determinants of health. In this article, our interdisciplinary group, representing core competencies in public health, suggest two complementary conceptual models as frameworks for a diverse public concerned with public health and its core functions. The first conceptual ‘core model’ roots from the Ottawa Charter for Health Promotion. It represents the interrelationships of the three main poles united at the biopower level: the collectivity (entire population), the contemporary state and public health. In the second conceptual model, we present the various components in the meta-network of public health governance. We also present the roles of heterogeneous actors and how they can collaborate within a prominent process of capacity building and development of practice in public health. Thus, we emphasize the importance of intersectoral partnerships the contemporary state can make with public health without inducing any rupture with the social fabric. Our two complementary models can help actors from all sectors better understand the most frequent questions in public health governance (functions, roles, ingredients) and the challenges that intersectoral actors may very likely encounter in the implementation of these frameworks. The sustainability of well-balanced transdisciplinary and intersectoral partnerships contribute to a successful implementation of public health governance, and most importantly to a good health status for the collectivity.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.039 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".