MULTILEVEL ACCESS TO JUSTICE IN A WORLD OF VANISHING TRIALS: A CONFLICT RESOLUTION PERSPECTIVE
Bibliographic record
Abstract
Access to justice emphasizes the notion of making law available to all, from the most advantaged to the disempowered, and has generally focused on the legal process as a whole. Using the access to justice framework, Dispute System Design, and principles from the Alternative Dispute Resolution (“ADR”) movement, this Article proposes a multi-level model of access to justice, which underscores the various stages of a legal conflict, from its inception as a dispute, up to its resolution in an adjudication on the merits or an out of court settlement. Drawing on legal theory and using methodology from law and society scholarship, we propose solutions to each stage that ensure access to justice for disempowered litigants. Furthermore, as many judicial systems experience the Vanishing Trial phenomenon, wherein most legal conflicts do not result in a trial but end in various pre-trial procedures, we focus primarily on the pre-trial phase where judges employ ADR techniques to facilitate and promote consensual dispositions. Based on data collected through interviews with judges and court observations, we argue that a new public sphere has formed in the pre-trial phase, where judges develop and apply their own understanding of access to justice. In our attempt to enhance the access to justice paradigm, we conclude by proposing an “ideal type” model of access to justice exemplified by the Canadian justice system in Quebec, which is based on a conflict resolution perspective instead of adjudication and litigation as preferred forms of justice. We further draw inspiration from a public health perspective on law, which focuses on prevention as part of the solution to social problems, be they diseases or social conflict.
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.059 |
| Scholarly communication | 0.024 | 0.013 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".