Public Attitudes Towards Moral Enhancement. Evidence that Means Matter Morally
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To gain insight into the reasons that the public may have for endorsing or eschewing pharmacological moral enhancement for themselves or for others, we used empirical tools to explore public attitudes towards these issues. Participants ( N = 293) from the United States were recruited via Amazon’s Mechanical Turk and were randomly assigned to read one of several contrastive vignettes in which a 13-year-old child is described as bullying another student in school and then is offered an empathy-enhancing program. The empathy-enhancing program is described as either involving taking a pill or playing a video game on a daily basis for four weeks. In addition, participants were asked to imagine either their own child bullying another student at school, or their own child being bullied by another student. This resulted in a 2 × 2 between-subjects design. In an escalating series of morally challenging questions, we asked participants to rate their overall support for the program; whether they would support requiring participation; whether they would support requiring participation of children who are at higher risk to become bullies in the future; whether they would support requiring participation of all children or even the entire population ; and whether they would be willing to participate in the program themselves. We found that people were significantly more troubled by pharmacological as opposed to non-pharmacological moral enhancement interventions. The results indicate that members of the public for the greater part oppose pharmacological moral bioenhancement, yet are open to non-biomedical means to attain moral enhancement. [248 words].
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.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it