Hypocrisy and Moral Justification: Do Consequences and Reasons Make a Difference?
Bibliographic record
Abstract
In this experiment, we examined if an act of hypocrisy would be judged as more morally justified if it (a) led to a lenient consequence versus a harsh consequence for another person and (b) was done for an other-focused versus self-focused reason. The experiment was implemented via an online study that used a 3 x 3 between-groups factorial design that manipulated the consequences of, and reasons for, an act of hypocrisy. We found that hypocrisy that led to a harsh consequence for another person was viewed as less morally justified than the same harsh act that occurred in the absence of hypocrisy, p < 0.001, Cohen’s d = 0.56, or when hypocrisy led to a lenient consequence for another person, p < 0.001, Cohen’s d = -.87. The reason given for the hypocritical act did not impact perceptions of moral justification, p = .67, η2 < .01, nor was there an interaction between consequences and reason, p = .49, η2 = .03. These results support the hypothesis that hypocrisy was judged negatively because it led to harsh consequences for others; however, our research leaves open the question of whether hypocrisy can be explained away with a compelling reason or not.
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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 | 0.001 |
| 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 | 0.002 |
| 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".