‘Sadly, my group was “hanged” at the end of the evening’: the politics of deservingness and representation at carceral-themed escape rooms
Bibliographic record
Abstract
Escape rooms are a popular new form of leisure and amusement globally, including in North American cities. Based on a thematic and discourse analysis of online content, we examine ten carceral-themed escape room operations in the United States and Canada. Drawing on theories of cultural power and neoliberalism, we analyze the messages conveyed by site operators about the deservingness of life, freedom and justice for imprisoned people. Contributing to literature on dark tourism and dark leisure, we also explore how the ideas of a ‘crime complex’ and ‘safe contact’ are reflected in representations of penality attached to escape room games. We argue that such depictions misrepresent the realities of carceral experience, producing understandings of carcerality and deservingness that foster punitive views among participants.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".