Yelling ‘Fire’ in a Crowded Occupation: Cynical Fire Hazard Claims and the Technocratic Containment of Dissent
Bibliographic record
Abstract
While the privatisation of public space has been the subject of considerable research, literature exploring the shifting boundaries between public and private law, and the role of those shifts in the expansion of neo-liberal social relations, has been slower to develop. This article explores the use of fire safety regulations to evict political occupations in the context of these shifts. Two examples from the UK student occupation movement and two from the US Occupy movement demonstrate how discourses and logics of both private and public law are mobilised through fire hazard claims to create the potent image of a neutral containment of dissent on technical grounds in the public interest – an image that proves difficult to contest. However, the recourse to the public interest and to expert opinion that underpins fire hazard claims is inconsistent with principles governing the limited neo-liberal political sphere, which underscores the pragmatic and continually negotiated implementation of neo-liberal ideas. The article sheds light on the complexity of the extending reach of private law, on the resilience of the public sphere and on the significance of occupations as a battleground on which struggles over neo-liberal social relations and subjectivities play out.
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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 | 0.027 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.128 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| 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".