Direct and indirect freedom in addiction: Folk free will and blame judgments are sensitive to the choice history of drug users
Bibliographic record
Abstract
People view addiction as a source of diminished free will and free will as a requisite to moral responsibility. Accordingly, people should judge addicts as less blameworthy when they act immorally. Yet, people are also sensitive to the personal histories of moral actors, such that the way by which people became addicted may influence these judgments. That is, people’s intuitions may track two types of choices: directly free acts are volitionally unconstrained during the moment of action, whereas indirectly free acts result from temporally prior directly free acts. Across two studies (N=806), we compare people’s moral intuitions about cases in which the actor becomes addicted by force or by choice. We find that perceptions of reduced free will partially mediate an association between choice (vs. no choice) in addiction and moral blame for a bad act (Study 1). We replicate this pattern with another case, and show that blame judgments are stronger when the bad act is related (vs. unrelated) to obtaining the addictive substance (Study 2). Our work highlights that lay people evince relatively nuanced intuitions about the role of free will in addiction and morality, tracking direct and indirect freedom when doling out moral blame.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".