Complexity: a potential paradigm for a health promotion discipline
Bibliographic record
Abstract
Health promotion underpins a distancing from narrow, simplifying health approaches associated with the biomedical model. However, it has not yet succeeded in formally establishing its theoretical, epistemological and methodological foundations on a single paradigm. The complexity paradigm, which it has yet to broach head-on, might provide it with a disciplinary matrix in line with its implicit stances and basic values. This article seeks to establish complexity's relevance as a paradigm that can contribute to the development of a health promotion discipline. The relevance of complexity is justified primarily by its matching with several implicit epistemological and methodological/theoretical stances found in the cardinal concepts and principles of health promotion. The transcendence of ontological realism and determinism as well as receptiveness in respect of the reflexivity that complexity encompasses are congruent with the values of social justice, participation, empowerment and the concept of positive health that the field promotes. Moreover, from a methodological and theoretical standpoint, complexity assumes a holistic, contextual and transdisciplinary approach, toward which health promotion is tending through its emphasis on ecology and interdisciplinary action. In a quest to illustrate our position, developmental evaluation is presented as an example of practice stemming from a complexity paradigm that can be useful in the evaluation of health promotion initiatives. In short, we argue that it would be advantageous for health promotion to integrate this paradigm, which would provide it with a formal framework appropriate to its purposes and concerns.
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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 | 0.025 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.010 | 0.091 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".