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Record W7106227280 · doi:10.26188/30664649

Research Project Overview: First Nations Women’s Engagement with the Family Law System

2025· other· W7106227280 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Melbourne data repository · 2025
Typeother
Language
Field
Topic
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsExcellenceFamily lawDomestic violenceEconomic JusticeLegal research

Abstract

fetched live from OpenAlex

This document provides an overview of a collaborative research project conducted by Women's Legal Services Australia (WLSA) and the Australian Research Council Centre of Excellence for the Elimination of Violence Against Women (CEVAW). The research examines First Nations women's experiences navigating the family court and family law system, drawing on insights from Women's Legal Services practitioners working directly with this community.The overview outlines the report's key aims and objectives, briefly summarises the research methodology, and presents findings across four critical areas identified through the study. It concludes with all 13 recommendations from the final report, which aim to improve access to justice and systemic responses for First Nations women engaging with family law processes.This resource is intended for policymakers, legal practitioners, researchers, and advocates working to address violence against women and improve family law outcomes for First Nations communities.

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)0.036
metaresearch head score (Gemma)0.029
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 score0.042
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0070.002
Scholarly communication0.0050.004
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0420.011

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 head0.081
GPT teacher head0.303
Teacher spread0.221 · 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
Published2025
Admission routes1
Has abstractyes

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