INGRESO Y ESTATUS SOCIAL COMO DETERMINANTE DE LA SALUD DE LA POBLACIÓN
Bibliographic record
Abstract
The health of the population not only depends on health care, but a/so on other determinants such as Jite style, environment and human biology. These were described by La/onde in 1974, who as Minister of Health and We/1-being of Ganada questioned the role of healthcare organizations as the only determinant of the health of populations, considering differences found related to the context of lite, biologica/ factors, social and environmental fa ctors. The analysis of the determinants of health is currently important for health professionals , in order to influence the leve/ of health of people and communities. The objective of the present paper is to analyze income and social status as one of the most powerful determinants of health. This analysis includes the conceptualization of poverty , its quantification , evolution and characterization in Chile, vulnerable groups, and its relation to health and other determinants. Poverty , determined mainly by low leve/ of income, is related to bad health, and bad health to poverty. lt is not on/y associated with low leve/ of income, but a/so with a global lack of fundamental needs and to the scarce possibility of overcoming it. lt is associated with most of the social determinants of health, and qua/ity of education is one of the main factors which contribute to overcoming poverty and social mobility. In Chile, the groups most affected by poverty and therefore the most exposed to health problems are children , women and the elderly. Key words: income, social c/ass, health leve/.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".