Divest or Disband?: A Social Problems Game Analysis of Canadian Media Coverage of 2020's Defund the Police Movement
Bibliographic record
Abstract
Policing in Canada and America has come under the microscope due to several high-profile incidents of police violence against racialized citizens. The murder of George Floyd by officer Derek Chauvin thrust the concept of ‘defund the police’ to the mainstream public dialogue. To date, there are few studies that explore what defund the police means. The present media analysis addresses this research gap by analyzing how Canadian mass media covered the defund police movement. A social constructionist theoretical framework was utilized to analyze 109 newspaper articles on defund the police from The Toronto Star and The Globe and Mail. The study illustrates how ‘defund the police’ was constructed as a solution to the putative problem of biased policing. However, the way in which the term was typified significantly differed among claims-makers, resulting in a competition within the social problems game. For one group, defund the police was typified as organizational reform and sought to change existing policies and procedures to raise the legitimacy of police, while for the other group it was typified as abolishment with the goal of dismantling policing. The following thesis empirically investigates how this claims-making competition played out within Canadian media sources.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".