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Record W7017840277

Canadian Access to Justice Initiatives: Justice Development Goals Status Report

2017· article· en· W7017840277 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeConversationAction (physics)State (computer science)Civil society
DOInot available

Abstract

fetched live from OpenAlex

One of the keys to understanding what needs to be done in the area of access to justice in civil and family matters is to first understand what is already being done. That is the goal of this first ever national survey (“Survey’) on the Action Committee on Access to Justice in Civil and Family Matters’ (“Action Committee”) nine Justice Development Goals. This Survey, in support of this first (and hopefully regular) Status Report (“Report”), is based on the Action Committee’s A Roadmap for Change report that offers six guiding principles for change and a ninepoint Access to Justice Roadmap.”1 The purpose of this Survey and Report is to help inform a national conversation on the state of access to justice in Canada with a view to recognizing current initiatives and identifying areas for future work. The Survey was conducted by the Canadian Forum on Civil Justice (CFCJ). This follow up Report was produced by the Canadian Forum on Civil Justice, under the leadership of Lisa Moore, Nicole Aylwin and Trevor Farrow.

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)0.012
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: Other · Consensus signal: Other
Teacher disagreement score0.133
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.010
Science and technology studies0.0120.001
Scholarly communication0.0060.002
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.003

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 head0.079
GPT teacher head0.414
Teacher spread0.336 · 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
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
Published2017
Admission routes1
Has abstractyes

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