The effect of portion size and unit size on food intake: Unit bias or segmentation effect?
Bibliographic record
Abstract
OBJECTIVE: The "unit bias" has been proposed as an explanation for the portion-size effect; people consider a single unit to be an appropriate amount to eat and thus eat more when served a larger unit than when served a smaller unit. We suggest that the unit bias might be better characterized as a "segmentation effect," such that people eat less when a unit of food is separated into smaller subunits, but may eat more than a single unit. Furthermore, we suggest that portion-size effects should be independent of this segmentation effect. METHOD: In Study 1, female participants (n = 87) were served either a small or large portion of food that was either presented in the form of a single unit or multiple individually wrapped units. In Study 2, female participants (n = 42) were served a fixed portion of food that was either presented in the form of a single unit or multiple units presented on separate plates. RESULTS: Across both studies, there was no evidence that participants prefer to eat a single unit. Participants served multiple smaller units did eat less than did participants served a single larger unit, even when the overall portion size was the same, but the amount eaten was consistently more than a single unit. Furthermore, perceived norms of appropriate intake mediated the effect of unit number on food intake. CONCLUSIONS: These findings suggest that a segmentation effect, rather than a unit bias, is driving people's food intake, with implications for designing interventions aimed at reducing excessive food intake.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".