Income-Related Health Inequalities under COVID-19 in Greece
Why this work is in the frame
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Bibliographic record
Abstract
This paper focuses on income-related health inequalities amid COVID‑19 in Greece. The prolonged crisis and the pandemic have exacerbated the socioeconomic risks in the country. A major implication is the sharp decline in incomes, which has worsened the health status and the access and use of healthcare, especially among low and middle income individuals. We analyze the theoretical background on health inequalities and describe the dual shock to Greek society, both with the ongoing fiscal consolidation and the COVID-19 pandemic. By utilizing EU-SILC data through alternative techniques, we offer empirical estimates of the extent of health inequalities ranked by incomes. The empirical findings indicate a certain increase in income-based health inequalities over a critical period for Greece’s population.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.011 |
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 it