Addressing the policy cacophony does not require more evidence: an argument for reframing obesity as caloric overconsumption
Bibliographic record
Abstract
BACKGROUND: Numerous policies have been proposed to address the public health problem of obesity, resulting in a policy cacophony. The noise of so many policy options renders it difficult for policymakers to determine which policies warrant implementation. This has resulted in calls for more and better evidence to support obesity policy. However, it is not clear that evidence is the solution. This paper argues that to address the policy cacophony it is necessary to rethink the problem of obesity, and more specifically, how the problem of obesity is framed. This paper argues that the frame "obesity" be replaced by the frame "caloric overconsumption", concluding that the frame caloric overconsumption can overcome the obesity policy cacophony. DISCUSSION: Frames are important because they influence public policy. Understood as packages that define issues, frames influence how best to approach a problem. Consequently, debates over public policy are considered battles over framing, with small shifts in how an issue is framed resulting in significant changes to the policy environment. This paper presents a rationale for reframing the problem of obesity as caloric overconsumption. The frame "obesity" contributes to the policy cacophony by including policies aimed at both energy output and energy input. However, research increasingly demonstrates that energy input is the primary cause of obesity, and that increases in energy input are largely attributable to the food environment. By focusing on policies that aim to prevent increases in energy input, the frame caloric overconsumption will reduce the noise of the obesity policy cacophony. While the proposed frame will face some challenges, particularly industry opposition, policies aimed at preventing caloric overconsumption have a clearer focus, and can be more politically palatable if caloric overconsumption is seen as an involuntary risk resulting from the food environment. SUMMARY: The paper concludes that policymakers will be able to make better sense of the obesity policy cacophony if the problem of obesity is reframed as caloric overconsumption. By focusing on a specific cause of obesity, energy input, the frame caloric overconsumption allows policymakers to focus on the most promising obesity prevention policies.
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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 | 0.110 | 0.141 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.012 | 0.114 |
| Scholarly communication | 0.017 | 0.036 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.044 | 0.038 |
| 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".