The role of urban municipal governments in reducing health inequities: A meta-narrative mapping analysis
Bibliographic record
Abstract
BACKGROUND: The 1986 Ottawa Charter for Health Promotion coincided with a preponderance of research, worldwide, on the social determinants of health and health inequities. Despite the establishment of a 'health inequities knowledge base', the precise roles for municipal governments in reducing health inequities at the local level remain poorly defined. The objective of this study was to monitor thematic trends in this knowledge base over time, and to track scholarly prescriptions for municipal government intervention on local health inequities. METHODS: Using meta-narrative mapping, four bodies of scholarly literature - 'health promotion', 'Healthy Cities', 'population health' and 'urban health' - that have made substantial contributions to the health inequities knowledge base were analyzed over the 1986-2006 timeframe. Article abstracts were retrieved from the four literature bodies using three electronic databases (PubMed, Sociological Abstracts, Web of Science), and coded for bibliographic characteristics, article themes and determinants of health profiles, and prescriptions for municipal government interventions on health inequities. RESULTS: 1004 journal abstracts pertaining to health inequities were analyzed. The overall quantity of abstracts increased considerably over the 20 year timeframe, and emerged primarily from the 'health promotion' and 'population health' literatures. 'Healthy lifestyles' and 'healthcare' were the most commonly emphasized themes in the abstracts. Only 17% of the abstracts articulated prescriptions for municipal government interventions on local health inequities. Such interventions included public health campaigns, partnering with other governments and non-governmental organizations for health interventions, and delivering effectively on existing responsibilities to improve health outcomes and reduce inequities. Abstracts originating from Europe, and from the 'Healthy Cities' and 'urban health' literatures, were most vocal regarding potential avenues for municipal government involvement on health inequities. CONCLUSIONS: This study has demonstrated a pervasiveness of 'behavioural' and 'biomedical' perspectives, and a lack of consideration afforded to the roles and responsibilities of municipal governments, among the health inequities scholarly community. Thus, despite considerable research activity over the past two decades, the 'health inequities knowledge base' inadequately reflects the complex aetiology of, and solutions to, population health inequities.
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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 | 0.068 | 0.196 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.034 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".