Conflicting internal and external eating cues: Impact on food intake and attributions.
Bibliographic record
Abstract
OBJECTIVE: Social factors have a powerful influence on people's food intake but people typically fail to acknowledge the influence of such external cues, instead explaining their food intake in terms of factors such as how hungry they are. We examined whether the tendency to explain one's food intake in terms of internal cues (i.e., hunger) rather than external cues (i.e., other people's behavior) would be apparent when those cues are in conflict with one another. METHOD: Female participants (n = 104) took part in a pizza taste test after having been food deprived for 18-hr or after consuming a meal-replacement preload. Half of the participants were also exposed to a social norm that conflicted with their deprivation condition: deprived participants were exposed to a low-intake norm, whereas preloaded participants were exposed to a high-intake norm. After completing the taste test, participants indicated the extent to which their food intake was influence by how hungry they were and how much other people ate. RESULTS: Deprived participants ate less when exposed to a low-intake norm than when no norm was present, but reported that the behaviors of others had no impact on their food intake. In contrast, preloaded participants did not eat significantly more when exposed to a high-intake norm, but reported that the behavior of others made them eat more. CONCLUSIONS: Participants are generally inaccurate in the attributions they make for their food intake, and we suggest that these inaccuracies may be because of motivated misreporting. (PsycINFO Database Record
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".