Distribution of event complexity in the British Columbia court system an analysis based on the CourBC analytical system
Bibliographic record
Abstract
This paper reports an exploratory research on the distribution of event complexity in the British Columbia court system. Analysis of event distribution shows that the frequency of events sharply decreases with the increase in the number of persons and counts. The most frequently observed type of event is the event that has one person involved with one count. The number of events observed sharply declines when we query for events with a larger number of people involved or more counts charged. It is found that the number of events observed exponentially decreases when more complex events comprising more counts are analyzed. The same exponential decrease is observed for events with two or more people. This means that, in general, the least complex events are the most frequently observed ones. The events with more than one person involved have a mode of two counts. A first approximation model for the distribution of the load on the system based on different levels of complexity is proposed. The proposed model can be used for and be evaluated by predicting the load distribution in the BC criminal court system.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".