A systematic scoping review evaluating sugar-sweetened beverage taxation from a systems perspective
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
Systems thinking can reveal surprising, counterintuitive or unintended reactions to population health interventions (PHIs), yet this lens has rarely been applied to sugar-sweetened beverage (SSB) taxation. Using a systematic scoping review approach, we identified 329 papers concerning SSB taxation, of which 45 considered influences and impacts of SSB taxation jointly, involving methodological approaches that may prove promising for operationalizing a systems informed approach to PHI evaluation. Influences and impacts concerning SSB taxation may be cyclically linked, and studies that consider both enable us to identify implications beyond a predicted linear effect. Only three studies explicitly used systems thinking informed methods. Finally, we developed an illustrative, feedback-oriented conceptual framework, emphasizing the processes that could result in an SSB tax being increased, maintained, eroded or repealed over time. Such a framework could be used to synthesize evidence from non-systems informed evaluations, leading to novel research questions and further policy development.
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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it