Analysis of Health and Drug Access Associated with the Purchasing Power of the Ecuadorian Population
Bibliographic record
Abstract
OBJECTIVE: To determine whether there is a relationship between access to health systems and out-of-pocket spending with socio demographic characteristics in Ecuador.METHODS: Retrospective analysis of national level data on household medical expenditure from the National Survey of Household Income and Expenditure in Urban and Rural Houses conducted by the Ecuadorian National Institute of Statistics and Census Databases as well as other scientific, institutional, technical-administrative datasets.RESULTS: Families in the lowest percentile of poverty spend proportionally more out-of-pocket on pharmaceutical drugs than wealthier families. Furthermore, the lowest income deciles have no access to private health coverage. Populations from the bigger cities have more access to health care services than smaller rural cities. In Ecuador, 71% of pharmaceutical products are imported and 8% of the total of drugs are generic.CONCLUSIONS: Despite efforts by the current government, health access remains uneven, as indicated by drug access and out-of-pocket expenses per family. Poorer families have higher relative health expenditures for drugs than families with higher incomes, although poorer families have no access to private insurances.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".