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Record W7017790209

A Call for Evidence-Based Research in ADR

2023· article· en· W7017790209 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeWork (physics)Action (physics)PopulationSustainable developmentCivil society
DOInot available

Abstract

fetched live from OpenAlex

In any three-year period, almost half the adult population in Canada will experience at least one justiciable civil or family problem. Few, however, will have the resources to resolve their legal problems, thus highlighting longstanding barriers that make access to justice such a pressing issue in Canada. Among many global justice initiatives, a prominent call to action is Goal 16 of the 2030 United Nations Sustainable Development Goals, which commits nations to work towards ensuring equal access to justice for all by 2030. Although there is no single strategy to achieve this, evidence-based practices in all areas of civil and family justice can help close the access-to-justice gap by shining a light on where gaps exist and suggesting how they may be closed.

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)0.571
metaresearch head score (Gemma)0.749
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.571
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5710.749
Meta-epidemiology (narrow)0.0030.005
Meta-epidemiology (broad)0.0130.018
Bibliometrics0.0190.015
Science and technology studies0.0070.028
Scholarly communication0.0370.062
Open science0.0200.020
Research integrity0.0590.060
Insufficient payload (model declined to judge)0.0320.009

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 head0.297
GPT teacher head0.480
Teacher spread0.183 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2023
Admission routes1
Has abstractyes

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