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Record W4313532347 · doi:10.1007/978-3-031-10721-4_3

Social Acceptability of Cisgenic Plants: Public Perception, Consumer Preferences, and Legal Regulation

2023· book-chapter· en· W4313532347 on OpenAlexaboutno aff
Christian Dayé, Armin Spök, Andrew C. Allan, Tomiko Yamaguchi, Thorben Sprink

Bibliographic record

VenueConcepts and strategies in plant sciences · 2023
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsPublic opinionGlobePerceptionTourismPolitical sciencePublic economicsGeographyEconomicsPsychologyLaw

Abstract

fetched live from OpenAlex

Abstract Part of the rationale behind the introduction of the term cisgenesis was the expectation that due to the “more natural” character of the genetic modification, cisgenic plants would be socially more acceptable than transgenic ones. This chapter assesses whether this expectation was justified. It thereby addresses three arenas of social acceptability: public perception, consumer preferences, and legal regulation. Discussing and comparing recent studies from four geographical areas across the globe—Europe, North America, Japan, and Australia and New Zealand—the chapter shows that the expectation was justified, and that cisgenic plants are treated as being more acceptable than other forms of genetic modification. Yet, there are considerable differences across the three arenas of social acceptability. In Australia, Canada, and the United States of America, the legal regulation of cisgenic plants is less restrictive than in Europe, Japan, and New Zealand. Also, the public perceptions are rather diverse across these countries, as are the factors that are deemed most influential in informing public opinion and consumer decisions. While people in North America appear to be most interested in individual benefits of the products (improved quality, health aspects), Europeans are more likely to accept cisgenic plants and derived products if they have a proven environmental benefit. In New Zealand, in contrast, the potential impact of cisgenic plants on other, more or less related markets, like meat export and tourism, is heavily debated. We conclude with some remarks about a possible new arrangement between science and policy that may come about with a new, or homogenized, international regulatory regime.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · 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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.119
GPT teacher head0.307
Teacher spread0.188 · 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.

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

Citations17
Published2023
Admission routes1
Has abstractyes

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