MILITARY FINANCE AND THE EARL OF ESSEX'S INFANTRY IN 1642 – A REINTERPRETATION
Bibliographic record
Abstract
ABSTRACT Scholarly works dealing with the Long Parliament's military finances have often necessarily relied on sampled data and exemplary evidence. This communication demonstrates that full, systematic analyses of the relevant materials in the Commonwealth Exchequer Papers have the potential to alter our understanding of these finances when certain questions are asked. Lacking a detailed calendar, this vast collection of documents is extraordinarily complex and opaque, and because of this it is very hard to deal with holistically. Nevertheless, this communication demonstrates that achieving a broad yet precise view of this vital quantitative material is sometimes possible. It will be suggested here that the army of the earl of Essex enjoyed full payment from the moment of its creation in August 1642 until the end of that October. This will be demonstrated by comparing the total payments received by the foot soldiers to a newly calculated model of their monetary needs during the period in question. Ultimately, there are many possible reasons for the army's failure to secure a decisive victory at Edgehill, but a financial crisis at the political centre was not one of them.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".