Book Reviews: Die Reichsbahn und die Juden, 1933–1939. Antisemitismus bei der Eisenbahn in der Vorkriegszeit [The German Railways and the Jews, 1933–1939. Antisemitism on the Railways in the Pre-War Period], Russia in Motion: Cultures of Human Mobility since 1850, the Socialist Car: Automobility in the Eastern Bloc, Quest for Speed: A History of Early Bicycle Racing 1868–1903, Mobility, Space and Culture, India's Railway History: A Research Handbook (Handbook of Oriental Studies; Section 2, South Asia), Land Based Air Power or Aircraft Carriers? A Case Study of the British Debate about Maritime Air Power in the 1960s, Carscapes: The Motor Car, Architecture, and Landscape in England, Hotel Dreams: Luxury, Technology, and Urban Ambition in America, 1829–1929, the World's Key Industry: History and Economics of International Shipping, Cultures and Caricatures of British Imperial Aviation: Passengers, Pilots, Publicity, Materializing Europe: Transnational Infrastructures and the Project of Europe, Swissair Souvenirs, British Aviation Posters: Art, Design, and Flight, Re-Inventing the Ship: Science, Technology and the Maritime World, 1800–1918, Last Trains: Dr Beeching and the Death of Rural England, Travels in the Valleys, Railway, the Cultural Life of the Automobile, Die Geschichte der Verkehrsplanung Berlins [The History of Transport Planning in Berlin]
Bibliographic record
Abstract
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.075 | 0.035 |
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".