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Record W7015309061

Social Membership: Animal Law beyond the\nProperty/Personhood Impasse

2017· article· en· W7015309061 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAnimal Law and Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsProperty (philosophy)Animal rightsDomesticationOppressionSubject (documents)Social animalLegal realismEconomic JusticePrivate property
DOInot available

Abstract

fetched live from OpenAlex

While animal law has been subject to frequent reform in Canada and abroad, the basic legal foundations of animal oppression are largely unchanged. There are many reasons for this impasse, but part of the explanation is that legal reforms are caught in what we might call the property/personhood dilemma. In most legal systems, domesticated animals are defined as property and so long as this remains true, reforms are likely to be marginal and ineffective. However the main alternative-to shift animals from the category of property to personhoodis politically unfeasible, particularly for the domesticated animals who are most intensively exploited in our society In this paper I explore a third option for legal reform, which is to include domesticated animals into other legal categories such as "workers" or "members of the family" which carry with them social standing and social rights, even if not full legal personhood. Indeed, there is already some movement in this direction: the law is recognizing (some) animals as (rightsbearing) workers or family members, for at least some purposes, without having declared them to be persons. I call this the social recognition strategy, and argue that it has unexplored promise for advancing justice for animals, although it is not without its own dilemmas and limits.

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 categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score1.000

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 studies0.0130.002
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.309
Teacher spread0.275 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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