Bibliographic record
Abstract
Creative geniuses’ deviant behaviors have drawn scholarly attentions for centuries. Plato, for instance, claimed that, “all the greatest benefits of Greece have sprung from madness.” Recent studies have found that creativity and immoral behaviors do seem to be highly correlated and concluded that deviant behaviors stimulate creative behaviors or vice versa. The current investigation raises the possibility that in addition to the effects of deviant behaviors on creativity, the moral reasoning processes behind the behaviors may also increase creativity. Across four studies, we investigated the effect of utilitarian reasoning on creativity. Study 1 showed a positive correlation between utilitarian reasoning and creativity. Study 2 found positive causal effect of utilitarian reasoning on creativity. We argued that utilitarian reasoning increases cognitive flexibility and willingness to deviate from norms because of the need to make conditional or contingent judgments. Indeed, we found that utilitarian reasoning increases creativity through the mediation of cognitive flexibility and willingness to deviate from norms (Study 3, 4). These findings suggest that instead of searching for “immoral geniuses” perhaps scholars could direct their attention more towards “utilitarian geniuses.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".