Bibliographic record
Abstract
Introduction The Conundrum of Military Education in Historical Perspective by John B. Hattendorf Educating Bellona: Carl von Clausewitz and Military Education by T.G. Ottee No Officer Rather than a Bad Officer: Officer Selection and Education in the Prussion/German Army, 1715-1945 by Dennis E. Showalter Sylvanus Thayer and the Ethical Instruction of Nineteenth-Century Military Officers in the United States by Lori Bogle History as Process and Record: The Royal Navy and Officer Education by Andrew Lambert Officer Education and Training in the British Regular Army, 1919-1939 by David French To Make the Men for the Next Crisis: The USAF Air War College and the Education of Senior Military Leaders, 1945-1993 by Mark R. Grandstaff The War Colleges and Joint Education in the United States by Thomas A. Keany The Labours of Athena and the Muses: Historical and Contemporary Aspects of Canadian Military Education by Ronald G. Haycock European Military Education Today by Peter Foot Bibliography Index
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.014 |
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".