Health in All Policies: Management Model for the Comprehensive Transformation of the System
Bibliographic record
Abstract
he essay explores the components of the approach health in all policies as a management model based on primary health care and its basic principles for health promotion described in the Ottawa Charter and the Adelaide Declaration: citizen participation and community empowerment, intersectorality, personal skills development, timely technologies and governance processes on social determinants of health. In this sense, we propose the transformation of the health system based on the construction of a comprehensive program for the strengthening of the organization through mechanisms of collaboration between the State and the Society, privileging equity and justice in defense of human rights. The document collects lessons learned from practices on the development and strengthening of “Sistemas Locales de Salud” and the Project “Municipios Hacia la Salud” in Venezuela (1989-2000), as well as experiences in other countries. The proposal is presented as a management model for the design, implementation, and governance of redistributive policies with a perspective of multisectoral strategic plan. We conclude that to be effective and efficient, these initiatives need better processes of political and functional decentralization, strong political and executive leadership, inclusive citizen participation, integrality between health and social goals and objectives, consensual planning between society and governments and; continuous accompaniment, monitoring and evaluation.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".