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Record W6889740449 · doi:10.26188/28536698

First Nations Women’s Engagement with the Family Law System in the Context of Family Violence. The Evidence Base.

2025· other· en· W6889740449 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Melbourne data repository · 2025
Typeother
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsFamily lawContext (archaeology)Child protectionInternational lawInterpersonal communicationColonialismDomestic violence

Abstract

fetched live from OpenAlex

This review focusses on First Nations women’s engagement with the family law system, especially in the context of family violence (FV). It consolidates key considerations gathered from existing research about, and by, First Nations people and their engagement with colonial structures and institutions, focussing on the family law system.In Australia, there has been growing recognition and understanding of the impacts of colonisation and historic and contemporary oppressive and discriminatory policies and practices on First Nations people and communities, both at an interpersonal level and in how systems and services are designed and delivered. This has underpinned efforts to reform systems and services with the aim to improve the accessibility, equity, inclusiveness and outcomes for First Nations women.First Nations women face a significantly higher risk of FV than non-First Nations women and are also at greater risk of having their children removed from their care by state-based child protection agencies – potentially as a result of FV, institutional racism and other factors. The family law system may offer some protection against child removal. As such, identifying barriers and exploring how these barriers to the family law system can be dismantled for First Nations women is a vital component of Australia’s strategy to reduce FV risks and harm. Targeted consideration of the legal and non-legal drivers and barriers First Nations women experience when engaging, or considering engaging, with the family law system is crucial.This review finds that there has been limited research specifically on First Nations women’s engagement with family law in the context of FV. Further research to identify and understand the needs of First Nations women in the family law system, especially in the context of FV, is necessary. Further analysis of available data from family courts, family law cases, support services and research with service providers and victim-survivors is needed to better understand the dynamics and drivers of First Nations women’s engagement with the family law system. This is required to continue to enhance accessibility, equity, inclusiveness and outcomes for First Nations people and to prioritise the identification of systemic reform and to highlight required service changes and other reforms as part of this endeavour. Additionally, further research is needed to provide a clear evidentiary basis to understand what is working well and to inform recommendations to reform the ways in which the family law system can best work to meet the needs of First Nations women who have experienced FV.This review developed out of a partner project between Women’s Legal Services Australia (WLSA) and the Centre of Excellence for the Elimination of Violence Against Women. WLSA is a peak body for two First Nations Women's Legal Services, Wirringa Baiya Aboriginal Women's Legal Centre and First Nations Women's Legal Service Queensland, and other Women's Legal Services that provide legal assistance and support services to First Nations women. The focus of our review is grounded in what our partner, WLSA, has identified as a key priority area in terms of practically-oriented research that is needed on the ground.

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)0.007
metaresearch head score (Gemma)0.034
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: none
Teacher disagreement score0.965
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.028
GPT teacher head0.259
Teacher spread0.231 · 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
Published2025
Admission routes1
Has abstractyes

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