Effects of exposure to unrealistic promises about dieting: Are unrealistic expectations about dieting inspirational?
Bibliographic record
Abstract
OBJECTIVE: The false-hope syndrome suggests that unrealistic expectations about dieting set dieters up for failure and then promote renewed efforts at weight loss. Many dieters believe the inflated promises typical of diet advertisements, which may be the source of at least some of their unrealistic expectations. Diet advertisements promoting unrealistic expectations were expected to inspire restrained eaters to diet and lead to enhanced self-perceptions, relative to more circumspect advertisements. METHOD: Female undergraduates rated their expectations in response to a control advertisement or to advertisements containing realistic, moderately unrealistic, or highly unrealistic promises of dieting. Participants then rated their self-perceptions and participated in an apparent "taste-test". RESULTS: Restrained eaters had higher expectations for themselves than did unrestrained eaters, and restrained and unrestrained eaters had similar expectations concerning dieting for others. Those who viewed the advertisements containing unrealistic expectations ate fewer cookies ad libitum than did those who viewed the realistic or control advertisements. DISCUSSION: This finding is consistent with the suggestion that unrealistic expectations contribute to the decision to change oneself.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".