The Social Determinants of Health: Why Should We Care?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A growing body of empirical research examines the effects of the so-called "social determinants of health" (SDH) on health and health inequalities. Several high-profile publications have issued policy recommendations to reduce health inequalities based on a specific interpretation of this empirical research as well as a set of normative assumptions. This article questions the framework defined by these assumptions by focusing on two issues: first, the normative judgments about the (un)fairness of particular health inequalities; and second, the policy recommendations issued on this basis. We argue that the normative underpinnings of the approach are insufficiently supported and that the policy recommendations do not necessarily follow from the arguments provided. Furthermore, while many of the policies recommended-such as improving people's living conditions and reducing inequalities in wealth and power-are justified in their own right, the way these recommendations are tied to health is problematic.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it