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Record W2417498326 · doi:10.1111/1477-9552.12171

Trends in Approval Times for Genetically Engineered Crops in the United States and the European Union

2016· article· en· W2417498326 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Economics · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
FundersFP7 Food, Agriculture and Fisheries, BiotechnologySeventh Framework ProgrammeQueen's UniversityQueen's University BelfastEuropean Commission
KeywordsEuropean unionBureaucracyMember stateMember statesPoliticsPolitical scienceAgricultural economicsInternational tradeBusinessLawEconomics

Abstract

fetched live from OpenAlex

Abstract Genetically engineered ( GE ) crops are subject to regulatory oversight to ensure their safety for humans and the environment. Their approval in the European Union ( EU ) starts with an application in a given Member State followed by a scientific risk assessment, and ends with a political decision‐making step (risk management). In the United States ( US ) approval begins with a scientific (field trial) step and ends with a ‘bureaucratic’ decision‐making step. We investigate trends for the time taken for these steps and the overall time taken for approving GE crops in the US and the EU . Our results show that from 1996–2015 the overall time trend for approval in the EU decreased and then flattened off, with an overall mean completion‐time of 1,763 days. In the US in 1998 there was a break in the trend of the overall approval time. Initially, from 1988 until 1997 the trend decreased with a mean approval time of 1,321 days; from 1998–2015, the trend almost stagnated with a mean approval time of 2,467 days.

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)0.002
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 score0.986
Threshold uncertainty score0.099

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.018
GPT teacher head0.210
Teacher spread0.192 · 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