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Record W3090757946 · doi:10.3390/ani10101786

Organic Dairy Cattle: Do European Union Regulations Promote Animal Welfare?

2020· review· en· W3090757946 on OpenAlexaff
Eugénie Duval, M.A.G. von Keyserlingk, Benjamin Lecorps

Bibliographic record

VenueAnimals · 2020
Typereview
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
FundersHans-Sigrist-Stiftung
KeywordsAnimal welfareEuropean unionBusinessWelfareAgricultureOrganic farmingDairy cattlePosition (finance)Public economicsAgricultural scienceEconomic policyPolitical scienceEconomicsLawGeographyFinanceEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Animal welfare is an emerging concept in EU law; with the advent of specific regulations intending to protect animals. The approach taken by European lawmakers is to provide "minimum standards" for conventional farming; argued by some as failing to adequately protect animals. In contrast, the EU organic farming regulations aim to "establish a sustainable management system for agriculture" and promote "high animal welfare standards". The first aim of this review was to identify key areas where there are clear improvements in quality of life for dairy cattle housed under the EU organic regulations when compared to the conventional EU regulations. Using the available scientific evidence, our second aim was to identify areas where the organic regulations fail to provide clear guidance in their pursuit to promote high standards of dairy cattle welfare. The greater emphasis placed on natural living conditions, the ban of some (but unfortunately not all) physical mutilations combined with clearer recommendations regarding housing conditions potentially position the organic dairy industry to achieve high standards of welfare. However, improvements in some sections are needed given that the regulations are often conveyed using vague language, provide exceptions or remain silent on some aspects. This review provides a critical reflection of some of these key areas related to on-farm aspects. To a lesser extent, post farm gate aspects are also discussed.

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 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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.004

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 head0.094
GPT teacher head0.364
Teacher spread0.271 · 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
GenreReview

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

Citations29
Published2020
Admission routes1
Has abstractyes

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