Bibliographic record
Abstract
One's weight is the outcome of a complex interplay of factors within which the choices we make about diet and activity are constrained and shaped by systemic forces - biological, social and economic - that fall increasingly beyond our control. "Simple" solutions that ignore the complex, systems-level characteristics of the obesity epidemic will generally fail as counter-veiling forces act to negate and undermine whatever action is taken. Selling the prevention message is not enough if politicians can choose conservative options that give the appearance of action but fail to tackle the issue. They need instead to be convinced that there is no alternative other than the multi-sector, multi-level, whole-of-government approach that is being adopted by enlightened jurisdictions such as California and the United Kingdom. As Dr. Havala Hobbs argues, this requires transparency, public participation, accountability and politically astute leadership of the sort demonstrated in the fight against tobacco.
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.
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 | 0.021 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.069 | 0.093 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".