Officers' Perceptions of the Ontario Provincial Police Framework for Police Preparedness for Indigenous Critical Incidents
Bibliographic record
Abstract
AbstractResponding to First Nation occupations and protests is one of the most challenging duties that police officers in Canada undertake. Over the last 30 years, these types of incidents have resulted in deaths and injuries to police and protesters, and millions of dollars’ worth of damage and financial loss. After the 1995 shooting death of an unarmed Indigenous protester by police at the Ipperwash occupation, the Ontario Provincial Police (OPP) introduced an unconventional operational approach for protests known as the OPP Framework policy. That approach was built on the concepts of peacekeeping, patient negotiation, mutual respect, and the minimal use of force, and only as a last resort. To address a gap in academic literature pertaining to officers’ perceptions of the Framework, data for this qualitative phenomenological research study were collected using interviews of 23 participants and analysis of archival records. Despite public criticism of the Framework approach, participants overwhelmingly supported it, highlighting the OPP Provincial Liaison Team members’ work in building strong relationships and trust with First Nations as its greatest strength. Those relationships enabled police to resolve more than 700 Indigenous critical incidents without having to resort to the use of force. In order to enhance the policy’s public perception and operational effectiveness, participants suggested improvements in training and education, internal and external communication, clarifying the role of government, and addressing public concerns about two-tiered policing. The study findings have potential implications for positive social change by averting or mitigating future protests and by altering negative the public perception of the Framework’s conciliatory and rights-based approach to resolving conflict.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".