Globalization and social determinants of health: Introduction and methodological background (part 1 of 3)
Bibliographic record
Abstract
Globalization is a key context for the study of social determinants of health (SDH). Broadly stated, SDH are the conditions in which people live and work, and that affect their opportunities to lead healthy lives.In this first article of a three-part series, we describe the origins of the series in work conducted for the Globalization Knowledge Network of the World Health Organization's Commission on Social Determinants of Health and in the Commission's specific concern with health equity. We explain our rationale for defining globalization with reference to the emergence of a global marketplace, and the economic and political choices that have facilitated that emergence. We identify a number of conceptual milestones in studying the relation between globalization and SDH over the period 1987-2005, and then show that because globalization comprises multiple, interacting policy dynamics, reliance on evidence from multiple disciplines (transdisciplinarity) and research methodologies is required. So, too, is explicit recognition of the uncertainties associated with linking globalization - the quintessential "upstream" variable - with changes in SDH and in health outcomes.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".