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Record W3168805362

The Way We Do Things Back Home: Do Expatriate Judges Preferentially Cite the Jurisprudence of Their Home Countries?

2013· article· en· W3168805362 on OpenAlexaboutno aff
Stephen E. Smith

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicConflict of Laws and Jurisdiction
Canadian institutionsnot available
Fundersnot available
KeywordsExpatriateNationalityJurisdictionLawJurisprudenceCommonwealthPolitical scienceForeign nationalState (computer science)SociologyImmigration
DOInot available

Abstract

fetched live from OpenAlex

This study considers ‘expatriate model’ judicial systems, whereby some or all of the judges that sit on a country’s courts are nationals of a foreign state. The author explores whether these foreign judges ‘favour’ their home jurisdiction by inflating the number of citations to judgments of the courts of their home countries. The study focuses on the citations of Commonwealth judges from England, Australia, New Zealand, Canada, and the United States, in the courts of eight pacific states: Fiji, Kiribati, Nauru, Samoa, Solomon Islands, Tonga, Tuvalu, and Vanuatu. The study concludes that the nationality of an expatriate judge does have some effect on the nationality of the foreign case law that they tend to cite.

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)0.006
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.074
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0040.006
Scholarly communication0.0070.006
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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.

Study designObservational
DomainMethods
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
Published2013
Admission routes1
Has abstractyes

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