Weight Loss Is Not the Answer: A Well‐being Solution to the “Obesity Problem”
Bibliographic record
Abstract
Abstract Americans have been gaining weight in recent decades, prompting widespread concern about the health implications of this change. Governments, health practitioners, and the general public all want to know: What is the best way to reduce the health risks associated with higher body weight? The dominant weight‐loss solution to this “obesity problem” encourages individuals to lose weight through behavior change. This solution rests on the assumptions that higher body weight causes health problems, that permanent weight loss is attainable, and that weight loss improves health. But comprehensive reviews of the scientific evidence find mixed, weak, and sometimes contradictory evidence for these premises. We suggest that a different solution to the “obesity problem” is needed – a solution that acknowledges both the multifaceted nature of health and the complex interaction between person and situation that characterizes the connection between weight and health. Thus, we use the lens of social psychological science to propose an alternative, well‐being solution to the “obesity problem”. This solution has the potential to improve health by encouraging eating and exercising for optimal health rather than weight loss, by developing interventions to reduce weight stigma and discrimination, and by helping higher body‐weight people cope with the stress of stigma and discrimination.
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 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 | 0.004 | 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 | 0.005 | 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) | 0.001 | 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 teacher head, 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".