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Record W2416350214

Vexatious litigant law reform.

2009· editorial· en· W2416350214 on OpenAlexaboutno aff
Ian Freckelton

Bibliographic record

VenuePubMed · 2009
Typeeditorial
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsnot available
Fundersnot available
KeywordsLaw reformParliamentLawGuard (computer science)HarmSubject (documents)Political scienceCommon lawKingdomLibrary sciencePolitics
DOInot available

Abstract

fetched live from OpenAlex

A number of jurisdictions, including in the United Kingdom, Canada, Australia, India and Hong Kong, have recently canvassed reform of vexatious litigant laws which in prescribed circumstances restrict access to the litigation system. The most recent contribution to law reform on the subject is the 2008 report of the Law Reform Committee of the Victorian Parliament. Having reviewed psychiatric and psychological literature on relevant mental health considerations, and taken into account empirical data on the subject, as well as having engaged in extensive consultations, the Committee recommended a series of graduated litigation restriction orders, comparable to but distinct from the system in place in the United Kingdom. This editorial reviews the recommendations of the Committee, the reasons for them and their advantages. It argues that there is much to be said for law reform in relation to vexatious litigation that has, at its centre, management of difficult litigants in a humane and responsive way and that has resort to preclusionary orders only to the minimum extent necessary to guard against foreseeable harm from the repeated bringing of unmeritorious applications or litigation.

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)0.005
metaresearch head score (Gemma)0.024
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.013
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0050.004
Open science0.0020.001
Research integrity0.0130.015
Insufficient payload (model declined to judge)0.0060.003

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 head0.019
GPT teacher head0.282
Teacher spread0.262 · 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
GenreEditorial

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

Citations2
Published2009
Admission routes1
Has abstractyes

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