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Record W3169653265 · doi:10.54119/jflp.xrbg7090

Private Farms, Public Power: Governing the Lives of Dairy Cattle

2020· article· en· W3169653265 on OpenAlexaffabout
Jessica Eisen

Bibliographic record

VenueJournal of Food Law & Policy · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPower (physics)Dairy cattleBusinessAnimal scienceBiology

Abstract

fetched live from OpenAlex

It is widely assumed that laws governing dairy productioninclude substantial protection of animals’ interests—that in some way the state is regulating the treatment of farmed animals and protecting them against the worst excesses of their owners’ selfinterest. In fact, across jurisdictions in Canada and the United States, the standards governing farmed animal protection are not established by elected lawmakers or appointed regulators, but are instead primarily defined by private, interested parties, including producers themselves. As scholars of animal law have noted, this has contributed to weak and ineffectual legal protection of the interests of farmed animals. The present study will focus on a distinct, though related, difficulty arising from the de facto or de jure delegation of standard-setting authority to animal industries. Not only does this delegation result in less stringent standards, but it also works to erode crucial public law values, such as transparency, accountability and impartiality.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.028
GPT teacher head0.227
Teacher spread0.199 · 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 designNot applicable
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
Published2020
Admission routes2
Has abstractyes

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