Children's Experiences with Family Justice Professionals in Ontario and Ohio
Bibliographic record
Abstract
There is increasing recognition in law and social science research of the importance of having children participate in post-separation decision making, though there is not a clear consensus on how this should be done. This article reviews the social science literature about children’s participation in the family justice process and presents results of a study in Ohio and Ontario with 32 children between 7–17 years of age, who either met with a judge, had a children’s lawyer represent them, or spoke to a mental health professional in a custody evaluation. Themes focus on (i) what they remembered about their parents’ separation and how they felt about it; (ii) how they found out about the plans that were made for their care; (iii) their level of involvement in decisions about their parents’ post-separation arrangements; (iv) the plans for their care; (v) what they remembered about their participation in the family justice process; (vi) what they found helpful about the process, and what was not helpful; and (vii) what advice they would give to lawyers/social workers/judges who work with children and young adults to help others in similar circumstances. The authors conclude by challenging some of the myths that professionals have about the possible harms or problems with involving children in decision-making post-separation. Children should never be forced to participate or feel that they are making a choice between parents, but it is valuable for children to be given the opportunity to participate, including meeting with the judge, if that is what they want.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.035 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".