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Record W2923904961 · doi:10.1007/s13280-019-01167-0

Governing evolution: A socioecological comparison of resistance management for insecticidal transgenic Bt crops among four countries

2019· review· en· W2923904961 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAMBIO · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsUniversity of Waterloo
FundersCollege of Engineering, Michigan State UniversityNational Institute of Food and AgricultureUniversidade de São PauloUniversity of WaterlooNational Socio-Environmental Synthesis CenterMichigan State UniversityRoyal Swedish Academy of SciencesCorteva AgriscienceDepartment of Entomology, College of Agriculture and Natural Resources, Michigan State UniversityStockholms UniversitetNorth Carolina State UniversityU.S. Department of AgricultureNational Science Foundation
KeywordsCorporate governanceContext (archaeology)Resistance (ecology)Government (linguistics)Bacillus thuringiensisIntegrated pest managementBusinessBiotechnologyEnvironmental resource managementVariety (cybernetics)Environmental planningGenetically modified cropsBiologyGeographyEconomicsEcologyTransgene

Abstract

fetched live from OpenAlex

Cooperative management of pest susceptibility to transgenic Bacillus thuringiensis (Bt) crops is pursued worldwide in a variety of forms and to varying degrees of success depending on context. We examine this context using a comparative socioecological analysis of resistance management in Australia, Brazil, India, and the United States. We find that a shared understanding of resistance risks among government regulators, growers, and other actors is critical for effective governance. Furthermore, monitoring of grower compliance with resistance management requirements, surveillance of resistance, and mechanisms to support rapid implementation of remedial actions are essential to achieve desirable outcomes. Mandated resistance management measures, strong coordination between actors, and direct linkages between the group that appraises resistance risks and growers also appear to enhance prospects for effective governance. Our analysis highlights factors that could improve current governance systems and inform other initiatives to conserve susceptibility as a contribution to the cause of public good.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.878
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.046
GPT teacher head0.341
Teacher spread0.296 · 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