Judgments of body weight based on food intake: A pervasive cognitive bias among restrained eaters
Bibliographic record
Abstract
OBJECTIVE: Two studies examined the influence of meal-size information on restrained and unrestrained eaters' judgments of body weight and size. METHOD: In Study 1, restrained and unrestrained eaters made body-weight and body-size judgments of a woman who had eaten either a small meal or a large meal. In Study 2, participants watched a video of a woman eating a small or large meal, and selected from two photographs of women's bodies (a heavier one and a thinner one), the woman whom they had seen in the video. RESULTS: Restrained eaters were influenced by meal-size information, judging women who had eaten a smaller meal as being thinner and weighing less (Study 1), and also choosing the thinner body to represent the woman who had eaten a smaller meal (Study 2). Unrestrained eaters were not influenced by food-intake information. CONCLUSION: Restrained eaters' (but not unrestrained eaters') judgments of others appear to be biased by meal-size information, suggesting that restrained eaters' food- and weight-related cognitive biases might be more pervasive than has previously been assumed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 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".