Responding to Calgary's “Gang War”: A Political Sociology of Criminological Ideas
Bibliographic record
Abstract
Drawing on the political sociology of ideas, this article considers a crucial crime control policy: increasing levels of policing. This policy is particularly interesting, given the scarcity of research indicating that increased levels of policing lead to reductions in crime. An examination of the ideas used to guide understandings of criminal events and crises shows how political actors understand crime as the consequence of a lack of control. In light of this understanding of crime, increasing the level of control through a heightened police presence becomes a logical solution. To illustrate this process, the article presents a case study of a “gang war” occurring in Calgary since 2007. Through an analysis of newspaper articles, the article shows how this event was framed by political actors in a way that legitimized policies that increase the number of police.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.025 | 0.125 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.010 |
| 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".