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 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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".