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Record W7031642194

Ag-Gag Illustrated

2021· article· en· W7031642194 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Education Research in Brazil
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationComicsLimitingFreedom of informationConstitutional lawConstitutional rightEconomic JusticeJurisprudence
DOInot available

Abstract

fetched live from OpenAlex

In February 2021, Professor Jodi Lazare was contacted by Petroglyph Comics, a social justice comic studio, that wanted to turn her research on Canadian ag-gag legislation into a comic, accessible to all. The resulting comic is based on two articles by Prof. Lazare, the first published in the Alberta Law Journal and the second currently under review at a second Canadian law journal. Both articles combine her interests in animal law and constitutional law to suggest that recently adopted legislation limiting access to and information about industrially farmed animals in Canada constitutes an unjustified limit to the constitutional right to freedom of expression and the public right to information about the violence of industrial animal farming. Images were inspired by the work of We Animals Media.

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.1060.012

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 head0.046
GPT teacher head0.283
Teacher spread0.236 · 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
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
Published2021
Admission routes1
Has abstractyes

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