Estimating the Delay of Criminal Trials: Evidence From Canada
Bibliographic record
Abstract
Court congestion is among society’s oldest legal problems; protections from it are enshrined in constitutions around the world. This paper uses publicly available data on the duration of millions of criminal court cases over the course of two decades across Canadian provinces to analyze the performance of the criminal justice system using queueing theory. Our new approach to estimating the delay of criminal trials appropriately includes the time from the point the charges are laid to first appearance, which is not available in raw data. We find that the queue sizes and wait times are growing in many provinces, suggesting that the criminal justice system is approaching, or perhaps beyond, capacity. Using several different time series specifications, we find that the utilization rate and model-implied queue size co-move positively with the population in pretrial custody. The results suggest that court congestion, as measured by statistics from queueing theory, has explanatory power for the rising population in pretrial custody.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".