Translating the City: Interdisciplinarity in urban studies
Bibliographic record
Abstract
Cities are a highly fragmented, heterogeneous subject; those who study, ana- lyze and question it make a use of a variety of disciplines and methods and have different areas of expertise. How is a dialogue built between heterogeneous urban contexts and urban researchers, architects, developers, anthropologists, sociologists and political scientists? What capacity do concepts and meth- ods have to travel from one context to another? How can they be transferred? Can they be translated? The strength of Translating the City lies in its disci- plinary and geographical comparison and dialogue on a global scale. It openly targets an international audience, bringing together leading researchers from a variety of disciplines (urban planning, sociology, architecture and anthropology) and presenting case studies from highly contrasting urban settings, including Cape Town, Dubai, Rio de Janeiro, Montreal, Mumbai, as well as Geneva, Lisbon, or Berlin.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".