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Record W6902472151 · doi:10.6084/m9.figshare.c.7007824

Supplementary material from "Are regulations addressing farm animal welfare issues during live transportation fit for purpose? A multi-country jurisdictional check"

2024· other· en· W6902472151 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAnimal welfareLivestockWelfareSpace (punctuation)Legislation

Abstract

fetched live from OpenAlex

Growing animal welfare concerns have pushed some jurisdictions to strengthen regulations addressing live farm animal transportation, but whether they provide satisfactory levels of protection for animals remains to be shown. Using the recent peer-reviewed literature, we identified four major risk factors associated with live animal transportation (fitness for transport, journey duration, climatic conditions and space allowances) and explored how regulations were structured to prevent animal welfare issues in five English-speaking Western jurisdictions (Australia, Canada, New Zealand, the EU and the USA). All legally binding federal regulations were systematically reviewed and compared. Whether these rules were fit for purpose was assessed using the relevant peer-reviewed scientific literature. Our findings indicate that most regulations in most jurisdictions are often insufficient or too vague to be deemed fit for purpose. All five jurisdictions fall short in guaranteeing adequate protection to livestock during transport. Using recent changes as well as future policy proposals currently in discussion, we drew key future directions for regulatory changes that may largely improve the welfare of farm animals during transportation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.750
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.7540.004

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 head0.057
GPT teacher head0.322
Teacher spread0.265 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2024
Admission routes1
Has abstractyes

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