El modelo de la OMS como orientador en la salud pública a partir de los determinantes sociales
Bibliographic record
Abstract
Public health has developed based on multiple approaches, including the guidelines of the health systems, the community or the individuals. This paper intends to identify the conceptual models of public health that arise after analyzing health or disease categories, as well as the level at which social response occurs: the individual or a family, biophysical and social environment; hygienist or preventive mode. Considering that the concept of model is not only a representation of reality, but an ontological position that allows to understand society and the State, all models are part of a theory and converge with other theories to create a framework of analysis. In consequence, three models of the health-disease process are presented. First, the Canadian model that establishes four determinants -lifestyle, environment, biological factors and health services-. Second, the social determinants model of the World Health Organization (WHO) that establishes three determinants based on risk approach: structural, intermediate and proximal. Finally, the historical-social or social determination model, which looks for the roots of social inequalities that affect health. The development of the Colombia Health System has considered these health models. Today, the Comprehensive Health Care Policy, and its Comprehensive Health Care Model, bases its approach within a model of determinants established by the PAHO.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".