CLOTHING AND FINANCIAL SUPPORT FOR THE PERSONNEL OF ARTILLERY AND ENGINEERING UNITS IN THE FIRST QUARTER OF THE 18TH CENTURY
Bibliographic record
Abstract
Since the early 18th century, signifi cant changes had been made in the military organisation of Russia, after which it received, in almost all respects, a new device, borrowed, in many cases, from European states. To maintain high combat readiness and combativity of the regular army being established, it was necessary to provide it with all necessary types of allowances, including fi nances, uniforms and other belongings. The article considers some problems of organisation of providing the personnel of the Russian army, including the artillery and engineering corps, with such types of allowances as clothing and fi nances, on the basis of previously unknown archival documents stored in the Archive of the Militaryhistorical Museum of artillery, engineering troops and signal troops and other sources. Special attention is paid to the issues of providing with monetary allowances, necessary uniforms and other belongings of employees, privates, non-commissioned offi cers and offi cers of artillery and engineering units. It is concluded that the existing order of proportional formation of the annual budget of the Department of artillery at the expense of one or another part of the income of various provinces and from other places led to chronic underfunding of Artillery Department, which, in turn, made it diffi cult to allocate funds in full for keeping and maintenance of daily life of the artillery and engineering corps. Some archival and other sources are for the fi rst time introduced in the study into scientifi c circulation.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".