Making it Politic(al): closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health
Bibliographic record
Abstract
The anniversary of the publication of Closing the Gap in a Generation (CGG) offers a moment to reflect on the report’s contributions and shortcomings, as well as to consider the political waters ahead. The issuance of CGG was not the first time the World Health Organization (WHO) raised the problem of global inequalities in health. Numerous analysts and advocates have compared CGG to the 1978 Declaration of Alma-Ata. Some see CGG as a continuation of Alma-Ata; others malign it for paying insufficient attention to the principles, background documents, and lines of action proposed in the Alma-Ata declaration. We might understand the two reports as bookends to 30 years of brutal global capitalism, punctuated by the “lost decade” of the 1980s, the end of the Cold War, and, more recently, the implosion of global finance. This period saw the publication of two seminal neoliberal health manifestos –the World Bank’s 1993 World Development Report and the WHO’s 2002 Commission on Macroeconomics and Health report. Both feature the term “investing in health” in their title, conveying “a double meaning—investing [through “cost-effective,” narrow, technical interventions] to improve health, economic productivity, and poverty; and investing capital, especially private capital, as a route to private profit in the health sector.”
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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".