Court Form Accessibility: Adopting, Designing and Evaluating Online Guided Pathways
Bibliographic record
Abstract
Abstract Self-represented litigants (SRLs) have repeatedly identified overly complex court forms as a major source of confusion and frustration. Digital guided pathways have been identified as one possible means to reduce barriers that the public experiences with court forms — but how effective are guided pathways as access to justice measures? Do they make court forms easier to fill out? If so, how can they be optimally designed and evaluated? This article reports on research seeking to answer these questions through a case study of family law guided pathways developed by Community Legal Education Ontario (CLEO). This study yielded two major conclusions. First, guided pathways can significantly reduce complexity for SRLs and, thus, other jurisdictions should consider adopting them as access-enhancing measures. Second, when designing and evaluating the design of court form guided pathways, a functional literacy framework, combined with user data and human testing, can be helpful in identifying barriers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".