Testing Our Faith: Why It Is Important to Study the Complexity of Client Experiences in Family Dispute Resolution
Bibliographic record
Abstract
Increasingly across Canada, court-based processes are being recast as forums of ‘last resort’ for family conflict. Studies inviting lawyers to reflect on the success of their collaborative negotiations, mediations, and settlement conferences show optimism—faith that the quality of their clients’ experiences has been more positive, or, at least, less damaging. As researchers, however, we know less about how the parties in the midst of separation and divorce actually experience those processes. The Saskatchewan study described in this article suggests that ‘the inside’ of dispute resolution (DR) processes in family conflict might be as qualitatively painful, negative, and difficult as the inside of court-based ones, and—yet—that people still prefer DR options. Future research needs to explore the emotional complexity of people’s experiences in the justice system. User-focused feedback may test legal professional’s assumptions, making room for authentic acknowledgements of the difficulties and strains which co-exist with the benefits of DR processes. User-focused feedback is also essential to help refine reform agendas in the family law justice arena.
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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 | 0.095 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.064 |
| Scholarly communication | 0.021 | 0.040 |
| Open science | 0.007 | 0.017 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".