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Record W2151144872 · doi:10.1177/03063127030333002

The Drugs Don't Work

2003· article· en· W2151144872 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Studies of Science · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsInstitute of Genetics
Fundersnot available
KeywordsVisionPharmacogeneticsEmerging technologiesEngineering ethicsSociologySet (abstract data type)Computer scienceBiologyEngineeringGenetics

Abstract

fetched live from OpenAlex

This article examines one particular set of technologies arising from developments in human genetics, those aimed at improving the targeting, design and use of conventional small molecule drugs-pharmacogenetics. Much of the debate about the applications and consequences of pharmacogenetics has been highly speculative, since little or no working technology is yet on the market. This article provides a novel analysis of the development of pharmacogenetics, and the social and ethical issues it raises, based on the sociology of technological expectations. In particular, it outlines how two alternative visions for the development of the technology are being articulated and embedded in a range of heterogeneous discourses, artefacts, actor strategies and practices, including: competing scientific research agendas, experimental technologies, emerging industrial structures and new ethical discourses. Expectations of how pharmacogenetics might emerge in each of these arenas are actively shaping the trajectory of this nascent technology and its potential socio-economic consequences.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.170
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.338
Teacher spread0.325 · 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