The role of judges in delaying timely access to civil justice: Analysis and proposal for reform
Bibliographic record
Abstract
Delays in access to justice is a global crisis. It is a pathology of legal systems all over the world. Delivering timely justice, therefore, is one of the most formidable developmental challenges of the 21st century. To tackle the problem of excessive court delays, North American civil justice systems have undergone radical transformations in the last half century in as much as the justice systems in both Canada and the US have traveled far away from their traditional moorings. The litigant-dominated adversarial models of adjudication have been largely replaced by judge-controlled case-managed litigation processes that privilege judicial economy over substantive adjudication. However, despite drastic reforms, North American courts are grappling with an excruciating inability to deliver justice within a reasonable time. In fact, the quantum of court delays continues to spiral upwards. My thesis investigates the less understood and underexamined problem of judicial exacerbation of court delays. It argues that the direction taken by judicial reforms in the last fifty years has, unwittingly, altered the very nature of the problem of court delays. Even as the reduction of delays is an important goal of managerial judging, the thesis argues that case management frameworks established by the legislative and appellate policymaking end up normalizing judicial complacency which, in turn, engenders and perpetuates a judge-led culture of delays. The thesis advances a new approach for future reforms to mitigate court delays. In doing so, it draws upon North America’s present and past experiences with case management and innovatively leverages the insights to develop a novel non-invasive model of judicial accountability for case managed systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".