Finding common ground : new directions in First World War studies
Bibliographic record
Abstract
Preface Jeffrey Grey ... ix Introduction: Who Owns the Battlefield? Jennifer D. Keene and Michael S. Neiberg ...xi List of Contributors ... xvii Part One: Setting the Stage 1. Why Are We Still Interested in This Old War? Roger Chickering. 3 Part Two: Soldiers and Sailors 2. Black-hearted Traitors, Crucified Martyrs, and the Leaning Virgin: Role of Rumor and the Great War Canadian Soldier Tim Cook. 21 3. Their Lordships Regret That...: Admiralty Perceptions of and Responses to Allegations of Lower Deck Disquiet Laura Rowe. 43 4. Imperialism, Nationalism and the First World War in India Santanu Das... 67 5. Letters from Captivity: First World War Correspondence of the German Prisoners of War in the United Kingdom Brian K. Feltman... 87 Part Three: Civilians under Occupation 6. Schools, State-Building, and National Conflict in German-Occupied Poland, 1915-1918 Jesse Kauffman... 113 7. Humanitarian Relief in Europe and the Analogue of War, 1914-1918 Branden Little... 139 Part Four: Re-Thinking the Battles 8. Railroads and the Operational Level of War in the German 1918 Offensives David T. Zabecki... 161 9. Liaisons not so Dangerous: First World War Liaison Officers and Marshal Ferdinand Foch Elizabeth Greenhalgh. 187 10. Junior Partner: Anglo-American Military Cooperation in World War I Mark E. Grotelueschen. 209 Part Five: Demobilization 11. The Crusade of Youth.: Pacifism and the Militarization of Youth Culture in Marc Sangnier's Peace Congresses, 1923-32 Gearoid Barry... 239 12. Militarizing the Disabled: Medicine, Industry, and Total Mobilization in World War I Germany Heather R. Perry... 267 13. Suspicious Pacifists: Dilemma of Polish Veterans Fighting War during the 1920s and 1930s Julia Eichenberg... 293 Bibliography. 313 Index... 331
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.014 | 0.036 |
| Scholarly communication | 0.019 | 0.047 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.057 | 0.006 |
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".