The Civil Justice System and the Public: Highlights of the Alberta Pilot
Bibliographic record
Abstract
In 1999, the Canadian Forum on Civil Justice initialed the "Civil Justice System and the Public," a research program designed to study the state of communication between the civil justice system and the public and to develop practices to improve communication so that the public can become more involved in civil justice reform. The goal of the project is to make specific and clear recommendations for effective change that will ultimately improve access to the civil justice system by increasing the ability of the system to hear, involve and respond to the public. Researchers from the Canadian Forum on Civil Justice and the University of Alberta are joined by partners from across Canada in academia, the judiciary; the legal profession, court administration, public legal education agencies, community organizations, private consultants and the public in a collaborative and multidisciplinary research alliance. The extensive partnership and our collaborative approach to the research are key to our "action research " design, which involves our partners in the drafting of research questions, data collection, analysis and dissemination. Through the active and engaged participation of our partners, our findings are broadly known, understood and acted upon, ensuring that change is promoted through the process of conducting the research itself. This article outlines the major features of the study and the findings, recommendations and conclusions arising out of the pilot study conducted in Alberta.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.028 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".