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Record W3121371707

Preferences for Enhancement Pharmaceuticals: The Reluctance to Enhance Fundamental Traits

2008· article· en· W3121371707 on OpenAlexfundno aff
Jason Riis, Joseph P. Simmons, Geoffrey P. Goodwin

Bibliographic record

VenueScholarly Commons (University of Pennsylvania) · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsnot available
FundersPrinceton UniversityYork UniversityYale University
KeywordsTraitPreferencePsychologySocial psychologyIdentity (music)Self-enhancementCognitionEconomicsComputer scienceMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Four studies examined the willingness of young, healthy individuals to take drugs intended to enhance their own social, emotional, and cognitive traits. We found that people were much more reluctant to enhance traits believed to be more fundamental to self-identity (e.g., social comfort) than traits considered less fundamental to self-identity (e.g., concentration ability). Moral acceptability of a trait enhancement strongly predicted people’s desire to legalize the enhancement but not their willingness to take the enhancement. Ad taglines that framed enhancements as enabling rather than enhancing the fundamental self increased people’s interest in a fundamental trait enhancement and eliminated the preference for less fundamental over more fundamental trait enhancements. Advances in medical technology are providing people with increasingly powerful ways to improve themselves. These technologies are not just used to restore health and youth, as increasing numbers of healthy young people are using them as well. More than a million young men

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.156
GPT teacher head0.351
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2008
Admission routes1
Has abstractyes

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