Court Governance: The Challenge of Change
Bibliographic record
Abstract
This article argues that overworked and overburdened individual judges are not in an effective position to initiate meaningful and systematic improvements in the quality of the administration of justice without a supporting judicial institution that would assist the courts in achieving a greater degree of organisational quality, efficiency, responsiveness and integration. The article provides a comparative overview of the Australian, Irish, Canadian, English and Dutch models of court governance. It is argued that the proposed Judicial Council of Victoria should be modelled on the Dutch Judicial Council, because it is the only institution that has a broad and unambiguous mandate to improve the quality of the administration of justice, while at the same time expanding the independence, self-responsibility and accountability of the courts in the areas of judicial administration, management, human resources and finances. The author argues strongly against any models of governance that would maintain internal administrative separation between judges and court administrators in the courts. Ultimately, it is argued that fully integrated and autonomous court management - supported by a judicial council - would lead to greater institutional responsiveness of the courts and improvements in judicial management, innovation, case management and quality of justice.
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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 | 0.038 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.062 |
| Scholarly communication | 0.021 | 0.018 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".