Shaping Public Policy and Population Health in the United States: Why is the Public Health Community Missing in Action?
Bibliographic record
Abstract
Renewed international interest in the structural determinants of health manifests itself in a focus on the social determinants of health and the public policy antecedents that shape their quality. This increased international interest in public policy in support of the structural determinants of health has had little traction in the United States. This should be surprising since the United States presents one of the worst population health profiles and public policy environments in support of health among wealthy developed nations. The U.S. position as a health status and policy outlier results from long-term institutional changes that are shaped by political, economic, and social forces. U.S. public health researchers' and workers' neglect of these structural and public policy issues conforms to the dominant ideological discourses that serve to justify these changes. The author presents some means by which public health researchers and workers can challenge these dominant discourses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.044 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.022 | 0.051 |
| Scholarly communication | 0.035 | 0.017 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.020 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 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".