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Record W2316528892 · doi:10.1386/ejac.32.3.249_1

Demonization and drug regulation: The state, culture and FDA regulators as villains in popular fiction, 1974–present

2013· article· en· W2316528892 on OpenAlexaff
Lucas Richert

Bibliographic record

VenueEuropean Journal of American Culture · 2013
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDemonizationBureaucracyGovernment (linguistics)State (computer science)Political scienceNarrativePublic administrationLawSociologyArtPoliticsLiterature

Abstract

fetched live from OpenAlex

Abstract Prescription drugs play an increasingly significant part in Americans’ lives. Therefore, undermining the process that safeguards the integrity of that drug armamentarium is particularly scandalous. This article critically considers three novels, The Third Patient, The Delta Factor and Strong Medicine, and attempts to locate them in a broader debate about the relationship between culture and the state. My analysis explores the development and implementation of a regulatory reform philosophy in the United States after 1974 and highlights the demonization of big government and specifically government bureaucrats like FDA officials. At the same time, the novels offer a specific critique of large bureaucracies, even as they acknowledge that such enormous entities provide opportunities for particular types of conspiracy narratives.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.094
GPT teacher head0.423
Teacher spread0.329 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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