Interrupting planetary urbanization: A view from Middle Eastern cities
Bibliographic record
Abstract
This paper argues that the ‘city’ as a political entity is significant in struggles over the ‘urban’, by identifying two moments of ‘differential urbanization’ in the Middle East. Our study in Iran and Palestine/Israel shows that the vision of the ‘city’ as a legitimizing space for political citizenship is at the heart of conflicting imaginaries: in Iran, ‘cities of revolution’ built through housing the poor around Tehran, and redistributive politics that stand on filling the ‘rural/urban gap’, and in Palestine, the new city of Rawabi as a city of Palestinian independence, where privatized urban development contrasts colonial spatialities with anti-colonial potentials. Thus, the right to the ‘urban’ involves claims for the ‘city’ that go beyond the capitalist logic of urbanization. This theorization points to a troubling gap in the planetary urbanization thesis, which moves from collapsing the ‘urban/non-urban’ divide into ‘concentrated’, extended’ and ‘differential’ urbanization to diminishing the role of distinct sociospatial configurations in claims over the ‘urban’. Our case studies show that examining the reconfiguration of inherited spatialities in the context of particular political regimes is imperative for epistemology of the ‘urban’ in its planetary stage. Urbanization otherwise remains an uninterrupted process towards a non-spatial ‘urban condition’.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.037 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".