I’ll scratch your back if you give me a compliment: Exploring psychological mechanisms underlying compliments’ effects on compliance
Bibliographic record
Abstract
Although compliments can be an effective compliance tactic, little is known about the reasons for their effectiveness. Two studies tested three potential mechanisms underlying the use of compliments as a compliance tactic: reciprocity, positive mood, and liking. In both studies, participants were either primed with the reciprocity norm or not, then received either complimentary or neutral feedback from a stranger. Participants were later faced with a request from the stranger. Mood, liking for the requestor, and compliance were measured. As predicted, compliments increased compliance in both studies. Neither study found evidence for positive mood nor liking as a mediator of the compliment effect. However, reciprocity priming was found to moderate the compliment effect in both studies, suggesting that compliments are effective, at least in part, because they invoke the reciprocity norm.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".