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Record W2025126101 · doi:10.3167/092012906780646343

GMOs in the laboratory

2006· article· en· W2025126101 on OpenAlexaffabout
Christina Holmes

Bibliographic record

VenueFocaal · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsDalhousie University
FundersRoyal Society
KeywordsPoliticsSociologyObject (grammar)Sociology of scientific knowledgeResponsible Research and InnovationEngineering ethicsEpistemologyPerceptionPolitical sciencePublic relationsSocial scienceLawEngineeringComputer science

Abstract

fetched live from OpenAlex

This article explores the lack of controversy over genetically modified objects (GMOs) in the daily life of a research laboratory in Canada. Scientific perceptions of GMOs and the types of knowledge valued in scientific research contribute toward an absence of discussion on the wider social implications of GMOs. Technical and epistemic knowledge are crucial for the success of a scientific project, whereas discussion of the social values involved may be allocated to particular settings, people, or research stages. GMOs, within scientific circles, are seen as many individual projects with different goals, rather than as a single object. Therefore, according to this view, it is inappropriate to be opposed to or to support GMOs in general, without first ascertaining the specifics of a particular project. How then are scientists engaged in seemingly local, distinct projects seen as globally defending this technology? Scientific expertise unevenly translates into political voice, transforming into silences as well as debates.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.244
Threshold uncertainty score0.485

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.047
Scholarly communication0.0110.006
Open science0.0010.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.011
GPT teacher head0.202
Teacher spread0.191 · 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.

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

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

Citations7
Published2006
Admission routes2
Has abstractyes

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