Does public health advocacy seek to redress health inequities? A scoping review
Bibliographic record
Abstract
The public health (PH) sector is ideally situated to take a lead advocacy role in catalysing and guiding multi-sectoral action to address social determinants of health inequities, but evidence suggests that PH's advocacy role has not been fully realised. The purpose of this review was to determine the extent to which the PH advocacy literature addresses the goal of reducing health and social inequities, and to increase understanding of contextual factors shaping the discourse and practice of PH advocacy. We employed scoping review methods to systematically examine and chart peer-reviewed and grey literature on PH advocacy published from January 1, 2000 to June 30, 2015. Databases and search engines used included: PubMed, CINAHL, PsycINFO, Social Sciences Citation Index, Google Scholar, Google, Google Books, ProQuest Dissertations and Theses, Grey Literature Report. A total of 183 documents were charted, and included in the final analysis. Thematic analysis was both inductive and deductive according to the objectives. Although PH advocacy to address root causes of health inequities is supported theoretically and through professional practice standards, the empirical literature does not reflect that this is occurring widely in PH practice. Tensions within the discourse were noted and multiple barriers to engaging in PH advocacy for health equity were identified, including a preoccupation with individual responsibilities for healthy lifestyles and behaviours, consistent with the emergence of neoliberal governance. If the PH sector is to fulfil its advocacy role in catalysing action to reduce health inequities, it will be necessary to address advocacy barriers at multiple levels, promote multi-sectoral efforts that implicate the state and corporations in the production of health inequities, and rally state involvement to redress these injustices.
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 | 0.034 | 0.137 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.025 | 0.031 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".