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Record W2011153353 · doi:10.1177/0963662513490466

Understanding attitudes towards the use of animals in research using an online public engagement tool

2013· article· en· W2011153353 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

VenuePublic Understanding of Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWorryOpposition (politics)Animal welfareDemographicsPublic engagementIntervention (counseling)WelfarePsychologyPublic relationsSocial psychologyPolitical scienceSociologyBiologyDemographyLaw

Abstract

fetched live from OpenAlex

Using an online public engagement experiment, we probed the views of 617 participants on the use of pigs as research animals (to reduce agricultural pollution or to improve organ transplant success in humans) with and without genetic modification and using different numbers of pigs. In both scenarios and across demographics, level of opposition increased when the research required the use of GM corn or GM pigs. Animal numbers had little effect. A total of 1037 comments were analyzed to understand decisions. Participants were most concerned about the impact of the research on animal welfare. Genetic modification was viewed as an intervention in nature and there was worry about unpredictable consequences. Both opponents and supporters sought assurances that concerns were addressed. Governing bodies for animal research should make efforts to document and mitigate consequences of GM and other procedures, and increase efforts to maintain a dialogue with the public around acceptability of these procedures.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.005
Science and technology studies0.0010.004
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.000
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 head0.905
GPT teacher head0.431
Teacher spread0.474 · 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