Improving public safety through technology: The past, present, and future of electronic monitoring in Canada
Bibliographic record
Abstract
Sexual predators who target strangers cause great harm to individuals, families, and the community, and generate considerable fear. There is a robust legal regime in place to manage Dangerous Offenders and Long Term Offenders, including supervision by parole officers and access to electronic monitoring. However, the legal tools and capacity to manage offenders who reach their “Warrant Expiry Date” (“WED”) after failing to qualify for parole or statutory release are limited to recognizances under section 810.1 and 810.2 of the Criminal Code and ad hoc monitoring by police. Modern Global Position Satellite (GPS) based electronic monitoring (EM) provides a cost-effective opportunity to improve the supervision of predatory offenders released at the end of their prison sentences and can increase public safety.\n\nThis Major Paper explores the legal regime to manage dangerous, long term, and WED prisoners, and profiles WED offenders, examines the history and features of EM technology, as well as its use internationally, and summarizes the research on the efficacy of EM. Further, this Major Paper considers current and future uses of GPS-based EM for crime solving, as an alternative to detention in appropriate cases pending trial, to prevent terrorism, and in forensic psychiatry. This Major Paper also explores the use of EM outside the criminal justice system, such as for those suffering from cognitive disorders who “wander.” Finally, this Major Paper makes several recommendations to increase the use of EM for sexual predators in well-designed, evidence-based studies, and concludes that this can be done in a cost-effective manner that balances privacy rights with legitimate public safety goals.
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 | 0.000 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".