Health promotion as a systems science and practice
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
RATIONALE: Health promotion is where clinical practice and prevention science intersect to address complex or 'wicked' problems that have multiple sources and require a broad perspective to address. This means focusing on the social determinants of health and the complex individual, community and environmental interactions that influence health and wellbeing. Health promotion research and practice recognizes that social change is not linear and involves multiple communities of interest working together in a coordinated manner in order to address health problems. An approach that acknowledges this non-linear system of interaction in its data gathering, strategic planning, and program implementation is necessary to addressing this complexity in practice. METHODS: Concepts such as chaos theory, self-organization, social emergence can inform how health promotion is practiced at multiple levels. Evaluation approaches such as social network analysis, system dynamics modeling combined with social organizing strategies like communities of practice and unconferences provide opportunities to leverage social capital effectively to promote health in complex environments with diverse populations. CONCLUSION: Health promotion's focus on the multi-layered, complex interactions that create or limit health and wellbeing require knowledge and action that match this complexity. Approaches to engagement and evaluation that are based on systems theories and methodologies provide the means of addressing this complexity, while framing health promotion as a systems science and practice.
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.
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 | 0.223 | 0.424 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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