The Commission on Social Determinants of Health: mainstreaming social inequalities in public health education in India.
Bibliographic record
Abstract
The final report of the Commission on Social Determinants of Health (SDH) has been the subject of analysis and policy discussions since its release in August 2008. Keeping in mind some of the early reviews of this report, the time has come to evaluate the pathways, both academic and political, that need to be mobilized to address this report in its fullest measure. As the dissemination of the report enters a new phase, its interpretation and reception in diverse policy arenas gains in importance, and its prioritization by key state and non-state agencies will need to be critically mapped and advocated in the near future. To address this, we need to recapitulate the strengths and implications of the report, as well as its national pathways. 1 The report focuses on the importance of achieving health equity at a time when inequalities have increased within and across countries. Several western European countries, Canada and even the US have expressed concern over the rising inequalities in health. Among the developing countries, economic liberalization over the past 3 decades has impacted socioeconomic and health opportunities differentially across regions and social groups. While the upper middle classes have clearly benefited from the twin processes of globalization and liberalization, other sections of the middle class and the organized and unorganized working classes have not benefited to a similar degree. Given the variations in the levels of inequality within and across countries, this report reaffirms the need to acknowledge the relationship between society and health, and upholds the principles of social justice. It states that the ‘commission’s vision is a world in which all people have the freedom to lead lives they have reason to value. This is a matter of social justice. Health and its key determinants are an issue of human rights. Politically, it is vital, as the success of a society can be judged from the quality and fair distribution of its population’s health’. 2 As a first step towards achieving equity in health, the commission offers a conceptual framework drawn on the basis of a review of the theoretical frameworks that have informed this area of inquiry. In addition, it has commissioned papers on nine themes—early child development, globalization, employment conditions, social exclusion, health systems, priority public health conditions, measurement and evidence, women and gender equity, and the urban setting. These nine themes are called the knowledge networks and under each of them there is a position paper that reviews the existing literature and also offers suggestions. 3
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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 | 0.027 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".