Reappraising the Elizabethan and Early Stuart Soldier: Recent Historiography on Early Modern English Military Culture
Bibliographic record
Abstract
Abstract For much of the 20th century, historians could muster little praise for the late Tudor and early Stuart soldiery, often portraying them as amateurs who were part of a decaying and moribund military tradition isolated from the transformations shaping warfare on the European continent. In the 1980s and 1990s, these theories were tested and found wanting by those who argued that the English were fully engaged in the so‐called early modern military revolution. Instead of decline and decay, England is now considered to have been engaged in the military revolution from early in the 16th century, with scholars arguing that the English art of war was in step with continental practice. This article weighs the contributions of a new generation of historians to the ongoing reappraisal of late Tudor and early Stuart soldiering over the last decade. Along with examining England and the military revolution, new work has focused much attention on the motivations and mentalities of English officers serving in France, the Low Countries and Ireland, with confessional zeal, honour and economic hardship seen as the primary factors motivating English volunteers to serve abroad. At the same time, scholars are also taking a fresh look at how military administration and improvements to training affected the lives of common soldiers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".