A Survey of Beliefs and Priorities About Access to Justice of Family Law: The Search for A Multidisciplinary Perspective*
Bibliographic record
Abstract
Within the last decade, the term “access to justice” has grown in popularity among legal commentators, scholars, family justice reformers, government policy makers, and the media. But with all of this new attention, there remains no common understanding or definition of access to justice and its potential implications for children and families in domestic relation courts. The purpose of this cross‐sectional online survey was to explore the meaning of access to justice according to legal, mental health, and dispute resolution professionals in various countries. The sample included 442 respondents (e.g., judges, lawyers, custody evaluators, mediators, family court services, court administrators, parent educators, etc.) from seven countries. Of the total respondents, 398 participants completed the survey (response rate of ninety percent). The majority of participants defined access to justice as the ability of disputants to seek and obtain a remedy through formal (e.g., the courts) or informal (e.g., mediation) institutions and services for resolving disputes. Noteworthy differences were reported, however, between the views of legal and mental health professionals, where the latter most likely viewed access to justice as a legal issue, while the former focused on alternative approaches outside of the legal system to resolve family disputes. Implications for family court reforms are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".