Motivated free will belief: The theory, new (preregistered) studies, and three meta-analyses.
Bibliographic record
Abstract
Clark et al. (2014) proposed a theory of motivated free will beliefs, according to which at least part of free will beliefs and attributions are caused by a desire to hold moral transgressors responsible. Recently, this theory has been challenged. In the following article, we examine the evidence and conclude that, although not dispositive, much of the evidence seems to support the motivated account. For example, in 14 new (seven preregistered) studies (n = 4,014), results consistently supported the motivated theory; and these findings consistently replicated in studies (k = 8) that tested an alternative (counternormative) hypothesis. In addition, three meta-analyses of the existing data (including eight vignette types and eight free will judgment types) found support for motivated free will attributions (k = 22; n = 7,619; r = .25, p < .001) and beliefs (k = 27; n = 8,100; r = .13, p < .001), which remained robust after removing all potential confounds (k = 26; n = 7,953; r = .12, p < .001). However, the size of these effects varied by vignette type and free will belief measurement. We discuss these variations and the implications for different theories of free will beliefs and attributions. And we end by discussing the relevance of these findings for past and future research and the significance of these findings for human responsibility. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".