Why do people tell the truth? Experimental evidence for pure lie aversion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A recent experimental literature shows that truth-telling is not always motivated by pecuniary motives, and several alternative motivations have been proposed. However, their relative importance in any given context is still not totally clear. This paper investigates the relevance of pure lie aversion, that is, a dislike for lies independent of their consequences. We propose a very simple design where other motives considered in the literature predict zero truth-telling, whereas pure lie aversion predicts a non-zero rate. Thus we interpret the finding that more than a third of the subjects tell the truth as evidence for pure lie aversion. Our design also prevents confounds with another motivation (a desire to act as others expect us to act) not frequently considered but consistent with much existing evidence. We also observe that subjects who tell the truth are more likely to believe that others will tell the truth as well.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it