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Record W2774722504 · doi:10.53386/nilq.v68i3.49

When is a Haida sphinx: thinking about law with things

2017· article· en· W2774722504 on OpenAlexaff
Genevieve Painter

Bibliographic record

VenueNorthern Ireland Legal Quarterly · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsMcGill University
Fundersnot available
KeywordsSphinxLawMateriality (auditing)ScholarshipPhilosophy of lawLegal historySociologyObject (grammar)ConstitutionCommercial lawComparative lawPolitical scienceAestheticsHistoryPhilosophyArchaeology

Abstract

fetched live from OpenAlex

The ‘law and . . .’ field of legal scholarship verges on consensus about the co-constitution between law and nearly everything else. Co-constitution raises questions about how to differentiate law from other things. The contemporary turn from words towards the material brings fresh perspective on these questions by suggesting that law’s differentiation is fabricated through materiality. This article considers whether and how material techniques that differentiate law might fabricate the difference of a thing not commonly understood by Western law as law. Its focus is an object created in Haida Gwaii in the late nineteenth century and now displayed in the British Museum. It shows that while techniques common to Western law differentiate this thing, competing materialities are also at work. Furthermore, jurisdictional choices are embedded in the fabrication of this thing’s difference. Understanding law as differentiated materially does not escape the social and jurisdictional forces that underpin how the matter of law comes to matter.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.031
Scholarly communication0.0070.015
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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