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Record W1672096170 · doi:10.1111/ropr.12057

Examining the <scp>C</scp> anadian Government's Resistance to Including Socioeconomic Concerns in Genetically Modified Seeds Regulation: A Policy Transfer and Multilevel Approach

2014· article· en· W1672096170 on OpenAlex
Jean‐Michel Marcoux, Lyne Létourneau

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

VenueReview of Policy Research · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCoercion (linguistics)Policy transferParliamentCompetition (biology)Government (linguistics)TypologyHarmPublic economicsResistance (ecology)EconomicsPolitical sciencePoliticsSociologyPublic administrationBiologyLawEcology

Abstract

fetched live from OpenAlex

Abstract In 2011, C anadian Members of Parliament refused to transfer a regulatory initiative taken from A rgentina that would have required an analysis of potential harm to export markets before authorizing the sale of any new genetically modified seed. This was the purpose of B ill C ‐474, which was defeated in the H ouse of C ommons. After exploring A rgentina's regulatory framework as a source of transfer, this paper combines a multilevel analysis with a typology of policy transfer mechanisms in order to address the complexities underlying this unsuccessful attempt. We explore how the mechanisms of competition and coercion might have impeded the transfer of such an initiative at the international and the macro‐state levels. Moreover, while a policy transfer network in support of the bill called on previous experiences with genetically modified seeds, their efforts appear to have been outweighed by another network using arguments based on the mechanisms of competition, coercion, and mimicry.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.173
GPT teacher head0.430
Teacher spread0.257 · 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