SYSTEMS Presented to the Canadian Judicial Council Administration of Justice Committee Administrative Efficiency in Trial and Appeal Courts Sub-Committee By
Bibliographic record
Abstract
Administration. In exploring the trend towards governments granting greater administrative autonomy to the courts, the report offered seven different models present in a number of jurisdictions. In 2011 the Administration of Justice Committee of Council commissioned a research study which would present a comparison of key characteristics of court administrative systems against those models in common law countries including Australia, England and Wales, New Zealand, North Ireland, the Republic of Ireland and Scotland. Key to this comparative analysis was the collection of legislation, memoranda of understanding and other forms of written agreements between the Judiciary and the Executive. They outline which level of government is responsible for certain or all aspects of court administration. The report consists of two documents. Presented here is the first part, namely, a comparative analysis building on the seven models presented in the 2006 report and further analysing how each of the selected jurisdictions advances their work according to six specific characteristics of court administration. Further below is the second part, namely, a report presented in a chart or table format which gives an overview of the analysis ’ content and provides for an easy comparison of the systems in place within the
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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 | 0.012 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.017 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".