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Record W4210565764 · doi:10.1017/cbo9781107282148.003

How legal documents are interpreted

2018· book-chapter· en· W4210565764 on OpenAlexaboutno aff
Peter Butt

Bibliographic record

VenueCambridge University Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicComparative and International Law Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStatutePlain languageField (mathematics)LawPlain EnglishLegal writingEngineeringStyle (visual arts)Political scienceEngineering ethicsLegal researchHistoryArchaeology

Abstract

fetched live from OpenAlex

Modern Legal Drafting provides a comprehensive, authoritative guide to drafting legal documents in effective, plain English. Peter Butt, a leading expert in the field, has fully revised and updated the text for this new edition. It combines a practical focus with the legal principles that underpin the use of plain language in law. This dual practical and academic approach distinguishes it from other books in the field. It includes expanded material on the techniques for achieving a style that is both clear and legally sound. It also includes new material on the challenges and merits of drafting in plain language, and provides many before-and-after examples to help both practising lawyers and students develop their skills. It takes an international approach, drawing upon case law and statutes from England, Australia, New Zealand, the United States, Canada, Ireland, India, Malaysia, Singapore and Hong Kong.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.780
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.263
Teacher spread0.227 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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