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Record W7111939965

Review of: On Common Laws

2007· article· en· W7111939965 on OpenAlexaboutno aff

Bibliographic record

VenueBristol Research (University of Bristol) · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Legal Studies and Society
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Dialogical selfCommon lawLegal historyCommon sense
DOInot available

Abstract

fetched live from OpenAlex

In this highly stimulating short book, Professor Glenn of McGill University revisits the old notion of a common law, including in his study not only the English common law, cradle of the namesake tradition, and the pan-European ius commune, but also the various national or transnational common laws which, until the age of codification, existed (first in Europe and then in the world) in a dialogical relationship with the various local laws that they encountered. Professor Glenn’s book attempts to re-interpret their historical relationship in accordance with the principle of subsidiarity, whereby at every level the general law would defer to the particular. By so doing, the author puts forward an explanatory model of ten centuries of legal developments in terms of layered, ‘relational’ common laws which cohabited harmoniously. This, it is argued by the reviewer, should be regarded as an ideal-type with which much, but clearly not all, of the historical data fits; and whose eirenic nature is probably inseparable from the Québecois context in which the book was written.

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)0.015
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.036
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.009
Science and technology studies0.0020.004
Scholarly communication0.0050.007
Open science0.0020.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0360.017

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 head0.106
GPT teacher head0.414
Teacher spread0.308 · 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
GenreReview

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
Published2007
Admission routes1
Has abstractyes

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