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
The obesity epidemic has provoked considerable concern along with suggestions and demands for corrective measures. After surveying the basic features of the epidemic, we turn our attention to self‐regulation, which is at the heart of most of the proposed solutions to the epidemic. Information, incentives, and most other tactics to get people to eat less and exercise more all rely on self‐regulatory processes. More attention should be paid to the distinction between interventions that depend on individual self‐regulation and interventions that bypass self‐regulation. A detailed examination of self‐regulatory and legislative regulatory alternatives, along with a detailed examination of the causes of the epidemic, leads to the conclusion that we should adopt a cautious and even skeptical approach to intervention. We scrutinize some of the principal proposed solutions to the obesity problem, few if any of which inspire optimism. The severity of the problem does not justify implementing unproven interventions in the absence of reliable evidence of their effectiveness.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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