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Record W4414327137 · doi:10.1111/jfcj.70015

Reimagining family courts: Integrating trauma‐informed care for healthier legal outcomes

2025· article· en· W4414327137 on OpenAlexaff
Laura Pearl Spivack, Michael Saini

Bibliographic record

VenueJuvenile and Family Court Journal · 2025
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAdversarial systemFamily courtFamily lawFamily therapyBest practice

Abstract

fetched live from OpenAlex

Abstract This paper explores the integration of Trauma‐Informed Care (TIC) within the family court system, emphasizing the need for a paradigm shift that incorporates understanding and addressing trauma as a fundamental aspect of legal proceedings. The authors argue that the existing family law framework, often marked by adversarial processes, fails to recognize the pervasive impact of trauma on individuals involved in family court cases. The paper reviews the principles of TIC and their application in family courts, advocating for an approach that prioritizes safety, empowerment, collaboration, and trustworthiness. By aligning these principles with the concept of Therapeutic Jurisprudence, the paper suggests a more compassionate and effective legal system that not only addresses legal outcomes but also fosters the psychological well‐being of those involved. The discussion includes practical recommendations for implementing TIC in family courts, highlighting the potential to reduce retraumatization and enhance the overall effectiveness of the court system in addressing complex family dynamics. The authors call for widespread training and education for legal professionals to ensure the successful adoption of trauma‐informed practices, ultimately aiming to create a more empathetic and supportive environment within family courts.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.661
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.341
Teacher spread0.316 · 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 teacher head, 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

Citations1
Published2025
Admission routes1
Has abstractyes

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