Bibliographic record
Abstract
1. Introduction Christopher Kopper and Massimo Moraglio 2. Clashes of Cultures: Road vs. Rail in the North-Atlantic World during the Inter-War Coordination Crisis Gijs Mom 3. Half-Holiday Excursions and Rambling Clubs - How did Leisure Shape the Mobilities of the Early Twentieth Century? Jill Ebrey 4. Towards a Better Understanding of Bicycles as Transport Peter Cox 5. Mobile Worths: Disputes Over Streets Jim Conley 6. Urbanization and Transport Restructuring Before World War II: A Comparison Between London and Osaka Takeshi Yuzawa 7. Why the Los Angelization of German Cities Did Not Happen: The German Perception of U.S. Traffic Planning and the Preservation of the German City Christopher Kopper 8. Automobility, Utopia, and the Contradictions of Modern Urbanism, Concerning Karel Teige Steven Logan 9. The Conquest of Urban Mobility: The Spanish Case, 1843-2012 Alberte Martinez and Jesus Miras 10. Shifting Transport Regimes: The Strange Case of Light Rail Revival Massimo Moraglio 11. The Creation and Perpetuation of an Automobile-Oriented Urban Form: Dispersed Suburbanism in North America Pierre Filion 12. Transportation Planning as Infrastructural Fix: Regulating Traffic Congestion in the Greater Toronto and Hamilton Area John Saunders 13. Move and Maintain: Mapping Multi-Local Lifestyles in Hyderabad, India Angela Jain and Gowkanapalli Lakshmi Narasimha Reddy 14. Dwelling In Between? Multi-Location between History and New Socio-Technical Systems Hans-Liudger Dienel and Massimo Moraglio
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.075 | 0.036 |
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".