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

2005· article· en· W2139497269 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

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0330.028

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