MétaCan
Menu
Back to cohort
Record W3123653304

The International Regulation of Animal Welfare and Conservation Issues through Standards Dealing with the Trapping of Wild Mammals

2000· article· en· W3123653304 on OpenAlexaboutno aff
Stuart R. Harrop

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationPolitical scienceWelfareInternational communityAnimal welfareInternational tradeWork (physics)International lawEuropean communityLaw and economicsLawBusinessEconomicsPoliticsEcologyBiologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

The development of laws at both national and international level dealing with the welfare of wild animals has been slow. In 1994 the European Community agreed a Regulation banning the use of leg-hold traps but import bans were postponed following the threat of legal challenge by the US and Canada under Gatt and WTO. The subsequent legal and policy history reveal important insights into the developments of international environmental standards where difficult ethical issues arise. The International Standards Organisation's attempts to devise agreed standards for humane trapping were frustrated by a consensus based approach and fundamental disagreement between interested parties. Their work was eventually confined to standards concerning trap testing methodology, thus avoiding difficult moral judgements and uncertainties. Eventually, negotiations between the European Community, Canada, the US, and the Russian Federation led in 1998 to two international agreements. These are the first such agreements to deal predominantly with the welfare of wild animals, but can still be criticised as being over concerned with the facilitation of trade.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.187

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 studies0.0000.000
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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicIdentification and Quantification in FoodFrench-language works237,207