Response to Open Peer Commentaries on “Prohibition or Coffee Shops: Regulation of Amphetamine and Methylphenidate for Enhancement Use by Healthy Adults”
Bibliographic record
Abstract
In my target article (Dubljevic 2013a), I analyzed available information and policy options for the two of the most commonly used cognitive enhancement (CE) drugs: Adderall and Ritalin. I concluded that for all forms of amphetamine, including Adderall, and for instant-release forms of methylphenidate, any form of sale beyond prescription for therapeutic purposes needs to be prohibited, while some form of a taxation approach (Dubljevic 2012a) and the economic disincentives model (EDM) in particular (Dubljevic 2012b) could be an option for public policy on extended-release forms ofmethylphenidate (like RitalinSR). However, not everyone agreed with my conclusions. There has been a considerable amount of constructive criticism regarding my proposal. Some neuroethicists objected to my favoring prohibitive policies to dangerous CE drugs such as amphetamine and argued for laissez-faire or even mandatory use of enhancements. Others took issuewith the conclusion that the economic disincentives model (EDM) could be an option for public policy on extended release forms ofmethylphenidate. Furthermore, there are those that think my argument in general and EDM in particular are failing to address the relevant issues in regulation of CE, such as social justice and real autonomy. Finally, there are those who offer suggestions on how the argument and the model of public policy for CE drugs can be improved. Since it makes sense to respond to similar commentaries together, I first review and respond to the objections coming from the Oxford “pro-enhancement group”: Anders Sandberg (2013), Neil Levy (2013), and Julian Savulescu (2013). Then I explore and answer several objections from neu-
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".