Health Equity’s Missing Substance: (Re)Engaging the Normative in Public Health Discourse and Knowledge Making
Bibliographic record
Abstract
Abstract Since 1984, the idea of health equity has proliferated throughout public health discourse with little mainstream critique for its variability and distance from its original articulation signifying social transformation and a commitment to social justice. In the years since health equity’s emergence and proliferation, it has taken on a seemingly endless range of invocations and deployments, but it most often translates into proactive and apolitical discourse and practice. In Margaret Whitehead’s influential characterization (1991), achieving health equity requires determining what is inequitable by examining and judging the causes of inequalities in the context of what is going on in the rest of society. However, it also remains unclear how or if public health actors examine and judge the causes of health inequality. In this article, we take the concept of health equity itself as an object of study and consider the ways in which its widespread deployment has entailed a considerable emptying of its semantic and political content. We point toward equity’s own discursive productivity as well as the quantifying imperative embedded within evidentiary norms that govern knowledge making, and performance management regimes that govern public health practices. Under current conditions of knowledge making and performance evaluation, a range of legitimate action and inaction is produced at the same time that more socially transformative action is legitimately curtailed—not merely by politics, but by the rules of the field in which public health actors work. Ultimately, meaningful progress on a normative ethical idea like health equity will require both substantial philosophical content and an analysis of what is going on in the rest of society.
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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 | 0.078 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.015 | 0.197 |
| Scholarly communication | 0.037 | 0.038 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 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".