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Record W2030920387 · doi:10.5235/20414005.4.4.700

Complementing Comparison: Renewing Analytical Legal Theory to Meet the Explanatory Challenge of Globalisation

2013· article· en· W2030920387 on OpenAlexaff
Keith Culver, Michael Giudice

Bibliographic record

VenueTransnational Legal Theory · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsGlobalizationParochialismState (computer science)Relevance (law)Law and economicsSubject (documents)Political scienceSubject matterJurisprudenceSociologyLawEpistemologyPositive economicsEconomicsPhilosophyPoliticsMathematicsComputer science

Abstract

fetched live from OpenAlex

It is now beyond question that legal theory risks parochialism and diminished interest if it fails to understand the implications of globalisation for law. Historically state-focused analytical legal theory, once a dominant force in jurisprudential debate, is thought by some to be especially likely to fade into irrelevance. William Twining has been a particularly acute critic of analytical legal theory, offering arguments whose force is amplified by Twining's long history of work from within that tradition. Twining argues that analytical legal theory's state-centred approach and analytic method of conceptual analysis render it incapable of taking globalisation seriously. In response, we argue that analytical legal theorists might well take Twining's criticisms of them not as the end of their relevance, but instead as a challenge to explain how their methods and subject matter are capable of renewal and expansion. In this paper we take some initial steps towards showing how this might be done.

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)0.026
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0060.054
Scholarly communication0.0130.041
Open science0.0030.013
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.051
GPT teacher head0.331
Teacher spread0.280 · 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 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

Citations3
Published2013
Admission routes1
Has abstractyes

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