Bibliographic record
Abstract
An eminent American scholar once remarked to me that ‘British historians kill concepts, they eat them right up and can’t help themselves’. I am reminded of his complaint each time I encounter the term ‘the Military Revolution’, for this is surely a good example of the process. A host of British historians alternately attacked and defended Michael Roberts's original formulation until the concept was hemmed in from all sides and threatened with suffocation. What Frank Tallett and D.J.B. Trim have done in this collection of specialised papers is rather more intelligent. They wish to establish exactly what changed, and what stayed the same in the organisation, administration and conduct of warfare over four long centuries of conflict in both Western and Eastern Europe. The editors take some trouble to synthesise the key lessons in the introduction. One might speak of a military revolution, they venture, but it was not as dependent on technology as some have claimed. Rather, military activity was managed from beginning to end by a single social class—the nobility—who, by following their inclinations for command, gradually became self-serving servants of the state. Princes waged war to enhance their power and their resources, but they were most effective when they had the willing participation of social and political élites. War for princes and aristocrats was ‘a natural mechanism for resolving disputes’, a ‘universal constant … integral to the conduct of relationships between all polities’ (p. 22).
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".