Bibliographic record
Abstract
Abstract In light of the magnitude of interpersonal harm and the risk of greater harm in the future, Ingmar Persson and Julian Savulescu have argued for pharmacological enhancement of moral behaviour. I discuss moral bioenhancement as a set of collective action problems. Psychotropic drugs or other forms of neuromodulation designed to enhance moral sensitivity would have to produce the same or similar effects in the brains of a majority of people. Also, a significant number of healthy subjects would have to participate in clinical trials testing the safety and efficacy of these drugs, which may expose them to unreasonable risk. Even if the drugs were safe and effective, a majority of people would have to co-operate in a moral enhancement programme for such a project to succeed. This goal would be thwarted if enough people opted out and decided not to enhance. To avoid this scenario, Persson and Savulescu argue that moral enhancement should be compulsory rather than voluntary. But the collective interest in harm reduction through compulsory enhancement would come at the cost of a loss of individual freedom. In general, there are many theoretical and practical reasons for scepticism about the concept and goal of moral enhancement.
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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 | 0.019 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.040 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".