Regimes of representation in Canadian police museums: Othering, police subjectivities, and gunscapes
Bibliographic record
Abstract
There are dozens of public police museums located across Canada that memorialize the country’s history of law enforcement and criminalization. Drawing from fieldwork at these sites, we explore the representational devices used to curate police museum displays. Invoking Stuart Hall’s work on representation and Othering, we examine how gun displays at Canadian police museums are organized to minimize the harm that police interventions with guns cause. Arguing these displays are made intelligible through a regime of representation that naturalizes the distinction between police officers and the “criminal” Other, we examine how these museums position weaponry including the gun as an esthetic object and a force of social good when in the hands of police. Analyzing curatorial strategies such as the arrangement of weapons, mannequin placement, dress, and level of humanization, as well as the rhetoric and narratives espoused on accompanying placards, we show how the curatorial approach in these spaces ratify an ideological framework that normalizes police violence and criminalization. We then assess what our analysis contributes to literatures on police museums and policing myths.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.034 | 0.030 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".