Cities Beyond Borders: Comparative and Transnational Approaches to Urban History
Bibliographic record
Abstract
Preface Introduction: 'Every time I describe a city': urban history as comparative and transnational practice, Nicolas Kenny and Rebecca Madgin. Part I: The seven Cs: reflections on writing a global history of urban segregation, Carl H. Nightingale Port cities in crisis: considering urban governance, modernity and migration in mid-19th-century Montreal and Liverpool in a transnational context, Dan Horner Choreographies of urban life: mapping the social history of cities, Jordan Stanger-Ross Rebuilding the cities destroyed in the Second World War: growing possibilities for comparative analysis, Jeffry Diefendorf. Part II: Urban governance and prostitution in 18th-century port cities in France and England, Marion Pluskota Comparing urban reform in London and Brussels, Janet Polasky Town planning and municipal growth in late colonial Bombay: towards a transnational perspective, Nikhil Rao Whose 'urban internationale'? Intermunicipalism in Europe, c.1924-36: the value of a decentred, interpretive approach to transnational urban history, Stefan Couperus and Shane Ewen The (trans)national question: Nazi spatial and urban planning, Janet Ward. Reflections: Cities of fear: the globalization of insecurity in the age of the gated community, Harold L. Platt Reflections: putting the 'trans' into transnational urban history, Richard Rodger. Bibliography Index.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.002 |
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".