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Record W3119827990 · doi:10.1080/14636778.2020.1868985

Assessing public opinions on the likelihood and permissibility of gene editing through construal level theory

2021· article· en· W3119827990 on OpenAlexafffund
Derek So, Robert Sladek, Yann Joly

Bibliographic record

VenueNew Genetics and Society · 2021
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsMcGill University and Génome Québec Innovation CentreMcGill University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsConstrual level theoryPublic opinionPsychologySocial psychologySample (material)Political sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Anticipatory policy for gene editing requires assessing public opinion about this new technology. Although previous surveys have examined respondents’ views on the moral acceptability of various hypothetical uses of CRISPR, they have not considered whether these scenarios are perceived as plausible. Research in construal level theory indicates that participants make different moral judgments about scenarios seen as likely or near and those seen as unlikely or distant. Therefore, we surveyed a representative sample of 400 Americans and Canadians about both the likelihood and the permissibility of 23 commonly discussed uses of gene editing. Respondents with more knowledge of gene editing generally thought these applications would be more likely within the next 20 years. There was a strong positive relationship between the perceived likelihood and permissibility of most CRISPR applications. Our results suggest that ongoing public engagement efforts for gene editing could be improved by taking its perceived time-frames into account.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.431

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.223
GPT teacher head0.435
Teacher spread0.213 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2021
Admission routes2
Has abstractyes

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