Cognitive enhancement with methylphenidate and modafinil: conceptual advances and societal implications
Bibliographic record
Abstract
Veljko DubljeviÄ,1 Christopher James Ryan2 1Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada; 2Discipline of Psychiatry and the Centre for Values, Ethics and the Law in Medicine, University of Sydney, Sydney, NSW, Australia Abstract: “Cognition enhancement” (CE) drugs are pharmaceuticals taken by healthy people with the aim of sustaining attention, augmenting memory, or improving other cognitive capacities. This paper focuses on two CE drugs – methylphenidate and modafinil. It analyzes their mechanism of action, the evidence for their efficacy in nonsleep deprived individuals, and reviews their adverse effects. It then addresses the normative stances and social issues surrounding CE drug use. Currently, there is little evidence that either methylphenidate or modafinil provide any useful cognitive enhancement to well-rested users. However, it is very possible that future research may reveal cognitive benefits for these agents or for other pharmaceuticals. Public attitudes on CE mirror those evident in academic debate. Even though the majority seem to be opposed to enhancement based on issues of authenticity, utility, and fairness, a steady minority take the view that cognitive enhancer usage is both acceptable and fair. Current legal regimes do not adequately address the social phenomenon of CE use. While the United Nations Convention on Psychotropic Substances defines limits of methylphenidate use across the globe, no such guide exists for modafinil. Keywords: cognitive enhancement, psychopharmacological neuroenhancement, Ritalin, Provigil, neuroethics
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.026 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| 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 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".