Co‐creating obesity prevention policies with youth: Policy ideas generated through the CO‐CREATE project
Bibliographic record
Abstract
Despite growing recognition of the importance of applying a systems lens to action on obesity, there has only been limited analysis of the extent to which this lens has actually been applied. The CO-CREATE project used a youth-led participatory action research approach to generate policy ideas towards the reduction of adolescent overweight and obesity across Europe. In order to assess the extent to which these youth-generated policy ideas take a systems approach, we analyzed them using the Intervention Level Framework (ILF). The ILF ascribes actions to one of five system levels, from Structural Elements, the least engaged with system change, up to Paradigm, which is the system's deepest held beliefs and thus the most difficult level at which to intervene. Of the 106 policy ideas generated by young people during the CO-CREATE project, 91 (86%) were categorized at the level of Structural Elements. This emphasis on operational rather than systems level responses echoes findings from a previous study on obesity strategies. Analyzing the distribution of systems level responses using the ILF has the potential to support more effective action on obesity by allowing identification of opportunities to strengthen systems level responses overall.
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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 | 0.038 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".