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Record W2949668285 · doi:10.22329/wyaj.v35i0.5789

Judicial Dispute Resolution in Canada: Towards Accessible Dispute Resolution

2018· article· en· W2949668285 on OpenAlexaffvenueabout
Archie Zariski

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsAthabasca University
Fundersnot available
KeywordsDispute resolutionOnline dispute resolutionEconomic JusticeAlternative dispute resolutionLawPolitical scienceIntervention (counseling)Resolution (logic)Element (criminal law)Civil procedureDeterminativeComputer sciencePsychology

Abstract

fetched live from OpenAlex

This article argues that access to judges is an essential element of access to justice. Traditional civil litigation procedure aimed at preparation for trial that is complex, time-consuming and costly obstructs such access, especially for litigants without lawyers. To remedy this, the author proposes a summary judicial dispute resolution procedure comprising two stages: early judicial intervention followed by judicial dispute resolution that is determinative if necessary. At both points litigants would be given the opportunity to settle their dispute consensually, thus combining principles of self-determination with final disposition according to law. The proposal draws on and extends contemporary innovations in Canadian courts concerning summary proceedings and binding judicial dispute resolution. The new procedure should improve access to judges and thus access to justice.

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)0.009
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.100
Threshold uncertainty score0.722

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.022
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0160.009
Scholarly communication0.0100.004
Open science0.0030.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.078
GPT teacher head0.398
Teacher spread0.320 · 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
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

Citations1
Published2018
Admission routes3
Has abstractyes

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