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Record W2269989974

Multiculturalism in Law is Legal Pluralism-Lessons from Indonesia, Singapore and Canada

2007· article· en· W2269989974 on OpenAlexaboutno aff
Gary F. Bell

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Studies and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismLegal pluralismPluralism (philosophy)Political scienceLawIndonesianLegal cultureCultural pluralismState (computer science)State lawSociologyLegal researchLegal realismEpistemology
DOInot available

Abstract

fetched live from OpenAlex

The Indonesian, Singaporean and Canadian States define or describe themselves as multicultural. Since law is part of one's culture, a state's multiculturalism should lead that state to recognise a multiplicity of laws, to recognise one form or another of legal pluralism. Singapore and Indonesia practice legal pluralism by granting state recognition to laws other than state law. Canada however does not really do so. The author questions Canada's commitment to multiculturalism in law.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.513

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0210.020
Scholarly communication0.0120.006
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.283
Teacher spread0.272 · 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 designQualitative
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

Citations28
Published2007
Admission routes1
Has abstractyes

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