Precarious Urbanity: ‘The Jungle’ (Calais) and the Politics of Performing the Urban
Bibliographic record
Abstract
This article provides an innovative perspective on the themes of urbanity and performance in the context of the refugee camp, ‘the Jungle,’ in Calais, and its demolition in 2016. ‘Performing the urban’ is typically understood either in terms of ‘performance culture’ (urban dance, urban music, or street theatre) or as linking individual bodies to the production of urban space in the city. When suggesting that the ‘urban’ is performative in this article, I challenge both the implicit premise of voluntarism that underlies cultural practices such as street art, and the all-too-close link of urban performance to ‘city.’ Critically inquiring into the politics of performing the urban – and in a context that has been marked by denying refugees any formal status, including the right to dignified forms of even impermanent dwelling – I explore the power and privileges, and the mechanisms of social inclusion and exclusion, with which the markers ‘urbanity’ and ‘city’ are entangled. In other words, the events in Calais prompt us to consider the extent to which ‘urbanity’ and ‘city’ are part of epistemological mechanisms and performativities through which “the human is differentially produced” (Butler 2016, 41). With this premise, I inquire into the power and precarity of performances of urbanity, and into the claims to humanity, entitlement, dignity, and legitimacy to which they give rise.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.058 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".