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Record W7069002617

Access to Justice

2017· article· en· W7069002617 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeOrder (exchange)Rule of lawProcedural justice
DOInot available

Abstract

fetched live from OpenAlex

There is mounting evidence that access to justice in Canada is approaching a crisis point. An estimated 3.8 million Canadians per year experience at least one legal problem - but many of these people are unable to resolve their problems fairly, effectively or affordably. According to the World Justice Project's Rule of Law Index, Canada ranks among the top ten countries globally on aggregate legal system indicators such as fundamental rights, open government, and order and security. But Canada ranks a distant forty-eighth based on the public's ability to access and afford civil justice. The most recent data from national legal needs surveys in Canada confirm the extent of the crisis, and reveal Canadians' widespread dissatisfaction with the options available to address their justice problems.

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)0.020
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: Empirical · Consensus signal: none
Teacher disagreement score0.678
Threshold uncertainty score0.647

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0080.003
Scholarly communication0.0070.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0980.007

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 head0.153
GPT teacher head0.417
Teacher spread0.264 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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