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From Mad Scientist to Bad Scientist: Richard Seed as Biogovernmental Event

2005· article· en· W2139497269 on OpenAlexaff
Neil Gerlach, Sheryl N. Hamilton

Bibliographic record

VenueCommunication Theory · 2005
Typearticle
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsCarleton UniversitySocial Sciences and Humanities Research Council
Fundersnot available
KeywordsJournalismEvent (particle physics)SociologyMedia studiesCorporate governanceLibrary scienceManagementComputer scienceEconomics

Abstract

fetched live from OpenAlex

In 1998, Chicago physicist Richard Seed's announcement that he would clone a human being set off an international media furor that revealed important insights into our understandings of biotechnology, scientists, and governmental regulation of genetic research. This study examines English-language media coverage of Seed over a 5-year period, tracing how his initial framing as a “mad scientist” was quickly contained and managed by the scientific community through his reframing as a “bad scientist.” Amid media calls for a response from government regulators, it became apparent that the state has failed to adequately prepare itself and the public for the eventuality of human cloning, a failure of biogovernance. This article discusses how three tensions in current biogovernmental practice were made visible once Seed was read as a biogovernmental event.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.024
Scholarly communication0.0100.008
Open science0.0010.004
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.383
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations9
Published2005
Admission routes1
Has abstractyes

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