The Link Between Self-Dehumanization and Immoral Behavior
Bibliographic record
Abstract
People perceive morality to be distinctively human, with immorality representing a lack of full humanness. In eight experiments, we examined the link between immorality and self-dehumanization, testing both (a) the causal role of immoral behavior on self-dehumanization and (b) the causal role of self-dehumanization on immoral behavior. Studies 1a to 1d showed that people feel less human after behaving immorally and that these effects were not driven by having a negative experience but were unique to experiences of immorality (Study 1d). Studies 2a to 2c showed that self-dehumanization can lead to immoral and antisocial behavior. Study 3 highlighted how self-dehumanization can sometimes produce downward spirals of immorality, demonstrating initial unethical behavior leading to self-dehumanization, which in turn promotes continued dishonesty. These results demonstrate a clear relationship between self-dehumanization and unethical behavior, and they extend previous theorizing on dehumanization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".