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Record W4237463551 · doi:10.32920/ryerson.14662518

Self-representation in the family court: is justice for all in Canada?

2021· preprint· en· W4237463551 on OpenAlexaffabout
Maria Evelyn Jovel-Rollins

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsToronto Metropolitan UniversityCentre for Social Innovation
Fundersnot available
KeywordsPerspective (graphical)Theme (computing)NarrativeRepresentation (politics)Work (physics)Economic JusticeSocial justiceQualitative researchFamily courtSociologyPublic relationsPolitical scienceCriminologyLawSocial scienceEngineering

Abstract

fetched live from OpenAlex

This research study examines the experience of self-represented litigants (SRLs) in family court and their challenges accessing justice. It focuses on barriers that women litigants experience in accessing justice and explores how the process of self-representation affects their health and finances. Despite the growing corpus of literature in recent years on the theme, few studies have been done from the social work perspective. Grounded in structural social work and anti-oppressive approaches, his qualitative research focuses on analyzing the stories of three women who are or have been SRLs in the family court. Data collected from one-on-one narrative interviews are utilized to analyze the issue from a social work perspective. Most current literature is concerned with the lack of legal aid in addressing the issue. Findings of this study are expected to facilitate deeper debates and influence policy change.

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)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.513

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0390.010
Scholarly communication0.0090.003
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.072
GPT teacher head0.374
Teacher spread0.302 · 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
Published2021
Admission routes2
Has abstractyes

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