Political differences in free will belief are driven by differences in moralization
Bibliographic record
Abstract
In fourteen studies, we tested whether political conservatives’ stronger free will beliefs aredriven by stronger and broader tendencies to moralize, and thus a greater motivation to assign responsibility. In Study 1 (meta-analysis of five studies, n = 308,499) we show that conservatives have stronger tendencies to moralize than liberals, even for moralization measures containing zero political content (e.g., moral badness ratings of faces and personality traits). In Study 2, show that conservatives report higher free will belief, and this is mediated by the belief that people should be held morally responsible for their bad behaviour (n = 14,707). In Study 3, we show that political conservatism is associated with higher attributions of free will for specific events. Turning to experimental manipulations of our hypothesis, we show that when conservatives and liberals see an action as equally wrong there is no difference in free will attributions (Study 4); that when conservatives see an action as less wrong than liberals, they attribute less free will (Study 5); and that specific perceptions of wrongness mediate the relationship between political ideology and free will attributions (Study 6a and 6b). Finally, we show that political conservatives and liberals even differentially attribute free will for the same action depending on who performed it (Studies 7a-d). Together, our results suggest political differences in free will are largely explicable through motivated reasoning and differing desires to blame, rather than reflecting some genuine disagreement about the metaphysical nature of human freedom. Higher free will beliefs among conservatives may be explained by conservatives’ tendency to moralize, which strengthens motivation to justify blame with stronger belief in free will and personal accountability.
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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 | 0.022 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".