The implementation of Health in All Policies initiatives: a systems framework for government action
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There has been a renewed interest in broadening the research agenda in health promotion to include action on the structural determinants of health, including a focus on the implementation of Health in All Policies (HiAP). Governments that use HiAP face the challenge of instituting governance structures and processes to facilitate policy coordination in an evidence-informed manner. Due to the complexity of government institutions and the policy process, systems theory has been proposed as a tool for evaluating the implementation of HiAP. METHODS: Our multiple case study research programme (HiAP Analysis using Realist Methods On International Case Studies - HARMONICS) has relied on systems theory and realist methods to make sense of how and why the practices of policy-makers (including politicians and civil servants) from specific institutional environments (policy sectors) has either facilitated or hindered the implementation of HiAP. Herein, we present a systems framework for the implementation of HiAP based on our experience and empirical findings in studying this process. RESULTS: We describe a system of 14 components within three subsystems of government. Subsystems include the executive (heads of state and their appointed political elites), intersectoral (the milieu of policy-makers and experts working with governance structures related to HiAP) and intrasectoral (policy-makers within policy sectors). Here, HiAP implementation is a process involving interactions between subsystems and their components that leads to the emergence of implementation outcomes, as well as effects on the system components themselves. We also describe the influence of extra-governmental systems, including (but not limited to) the academic sector, third sector, private sector and intergovernmental sector. Finally, we present a case study that applies this framework to understand the implementation of HiAP - the Health 2015 Strategy - in Finland, from 2001 onward. CONCLUSIONS: This framework is useful for helping to explain how, why and under what circumstances HiAP has been successfully and unsuccessfully implemented in a sustainable manner. It serves as a tool for researchers to study this process, and for policy-makers and other public health actors to manage this process.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it