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Record W609596522

Designing national pesticide legislation

2007· article· en· W609596522 on OpenAlexaboutno aff
Jessica Vapnek, Isabella Pagotto, Margaret B. Kwoka

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural safety and regulations
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationConventionLegislaturePolitical sciencePublic administrationEnvironmental planningBusinessEnvironmental protectionLawGeography
DOInot available

Abstract

fetched live from OpenAlex

International and national legal frameworks governing the trade and use of pesticides have undergone significant changes over the last twenty years. The International Code of Conduct on the Distribution and Use of Pesticides, the Rotterdam Convention, the Stockholm Convention, the Basel Convention and the Montreal Protocol are only some of the binding and non-binding international instruments applicable to part or all of the life cycle of a pesticide. Specific guidelines for implementation are often available from the secretariat of the applicable international instrument, but comprehensive guidance is generally lacking. Governments need a clear picture of their international obligations as well as guidance on the accepted international consensus on the proper management of pesticides. Upgraded national legislation is needed to align national frameworks with international norms. This text aims to provide governments wishing to design, reform or update their national legislation with up-to-date advice on all aspects of pesticide management. Although the recommendations for national legislative change are designed to be useful to all countries, the text highlights the particular problems faced by developing countries and countries in transition, offering practical solutions to common problems. Also published in Spanish.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0060.004
Scholarly communication0.0080.009
Open science0.0030.006
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0150.007

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations10
Published2007
Admission routes1
Has abstractyes

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