The policing of major events in Canada: Lessons from Toronto's G20 and Vancouver's Olympica
Bibliographic record
Abstract
Major events ranging from sporting events to major international conferences too often result in disorder, deployment of riot squads, and mass arrests. Events surrounding a meeting of the G20 in Toronto and those at Vancouver’s Winter Olympics provide insight into the ways in which things can go wrong and the ways in which they can go well at major events. This article employs a “thick history” of events in order to explore gaps in Canadian law, including gaps between “law in the books” and “law in action.” \nThe legal frameworks governing large-scale events affect the likelihood of success measured in public safety, minimization of disorder, and protection of basic liberties. Surprisingly, large events often proceed without the benefit of a developed legal framework, leading to confusion among federal police, local police, and civil authority. We assess past reliance on the common law, a Vancouver City bylaw, Ontario’s Public Works Protection Act [PWPA], and the policing and security provisions of the federal Foreign Missions and International Organizations Act (Foreign Missions Act) in order to determine which sorts of legal arrangements are most conducive to successful event management. Since major events in Canada are most often developed in law’s penumbra, without the benefit of clear legal authority or statutory direction governing the measures that are required, both effective management and ordinary liberties are compromised. A “worst of both worlds” outcome destabilizes police–citizen relationships and leaves individuals uncertain as to the durability of their rights of property, speech, assembly, movement, and personal integrity. Equally, police forces are left insecure as to the lawful means by which they should perform their duties. A comparison of the two events provides the pathology and a prescription, illustrating the need for legislation to govern the management of major events.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.032 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".