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Record W2733790652

Biotechnology Unglued: Science, Society, and Social Cohesion By Michael D. Mehta, ed. (Vancouver: UBC Press, 2005)

2005· article· en· W2733790652 on OpenAlexaboutno aff
Chidi Oguamanam

Bibliographic record

VenueeYLS (Yale Law School) · 2005
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)SociologyMedia studiesChemistry
DOInot available

Abstract

fetched live from OpenAlex

In Biotechnology Unglued, Mehta and his thirteen-member interdisciplinary team, comprising mainly of social scientists using a number of ‘‘case studies’’, explore in nine essays ‘‘how advances in agricultural, medical, and forensic biotechnology may threaten the social cohesiveness of different kinds of communities and at different scales’’. In a way, the project is a successful attempt to underscore the theme of (and imperative for) social accountability of science and bio/technological innovations. This 208-page collection of nine essays in a corresponding number of chapters is a remarkable effort. It is a departure from the traditional concerns regarding biotechnology innovations which, hitherto, emphasized ethics, environmental sustainability, safety, human rights, equity, and global geo-political tensions. These concerns are, however, not completely glossed over. They are implicated in the essayists’ analyses, but not at the expense of the book’s central theme.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.999

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0040.003
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 head0.006
GPT teacher head0.238
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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
Published2005
Admission routes1
Has abstractyes

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