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 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 | 0.004 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".