Representations of Surveillance and Perceptual Technologies at Military Museums
Bibliographic record
Abstract
Drawing from fieldwork at military museums across Manitoba, Canada, we explore the objects and narratives used to curate museum displays featuring what Bousquet (2018) calls “military perception.” Using Bousquet’s categories of military perception to organize our analysis, we examine how these museums position scopes, sonars, camouflage, and other devices meant to create visibility or invisibility as aesthetic objects rather than as instruments enabling state violence. With a focus on curatorial strategies and the arrangement of objects at these museums, we explore how surveillance and camouflage displays are organized to minimize the harm that military interventions cause and align the affect of the viewer with the form of Canadian nationalism animating the museum and against “enemy” others and spaces, a process we refer to as encasement. In conclusion, we reflect on what our analysis adds to literature on military museums and representations of surveillance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".