Perceptions of Undereaters: A Matter of Perspective?
Bibliographic record
Abstract
We assume that people, to convey positive impressions of themselves, use the amounts eaten by others as limits beyond which their eating may be deemed excessive. One should, therefore, prefer eating partners who eat a lot because others' large intake renders one's own eating nonexcessive. Two studies were conducted to test this hypothesis. As predicted, participants liked confederates who ate more than they did better than those who ate less than they did, and they also rated their own intake as more appropriate when it had been exceeded by confederates than they did when it had been undercut by confederates. Noneating observers, instead, did not display a preference for eaters who ate more. Both noneating observers and active participants, however, rated eaters who ate less more positively than eaters who ate more on self-control-related items. We conclude that the nature of the behavior-impression association depends critically on the perspective of the rater.
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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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 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".