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Record W7018350933

The Cost of Experiencing Everyday Legal Problems Related to Social Assistance

2017· article· en· W7018350933 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 JusticeSocial issuesSocial justiceEveryday lifeCivil societySocial policyPoison control
DOInot available

Abstract

fetched live from OpenAlex

Experiencing a civil or family justice problem in Canada can come at a significant price. Outside of the monetary legal costs that Canadians incur when trying to resolve serious civil and family justice problems, many Canadians also pay for legal problems with high stress, emotional health problems and physical health problems. In addition, serious civil and family justice problems have also been shown to cause or exacerbate other family, personal and social problems and result in significant temporal costs that often come in the form of lost opportunity, reduced productivity, and reduced time and energy for building and maintaining family and social relationships. For Canadians with limited resources or whose location and or circumstances create additional obstacles to access information or assistance to resolve their legal problems, the cascade effect of these interconnected family, personal and social problems are especially onerous and can lead to social exclusion.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0140.003
Scholarly communication0.0040.002
Open science0.0020.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0330.001

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 head0.039
GPT teacher head0.365
Teacher spread0.326 · 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 designObservational
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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