The Blue Line on Thin Ice: Police Use of Force in the Era of Cameraphones, 'Citizen Journalism', and YouTube
Bibliographic record
Abstract
In today's urban environments the ubiquity of cameraphones and the entrenchment of both 'citizen journalism' and Web 2.0 media into social life and socio-political discourses have exponentially increased the public's exposure to police violence.This thesis investigates the impact on contemporary policing of the 'new visibility' of police conduct.Findings emerged from the surveying of 231 front-line officers in Toronto and Ottawa, follow-up interviews with 20 of these officers, and interviews with 8 policing officials in those cities.It was determined that widespread video oversight of policing and the ability of citizens to disseminate imagery through social media is profoundly embedded in the consciousness of operational officers and has resulted in various behavioural changes through the deterrence of certain 'performances', including significant moderations in police use of force practices.Technological innovations have enabled transformative changes in the public-police relationship and power dynamic through a democratizing social leveling.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".