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Record W4286518010 · doi:10.17951/rh.2022.53.61-77

Expeditions of Łan Soldiers in the Writings of Andrzej Maksymilian Fredro

2022· article· pl· W4286518010 on OpenAlexaboutno aff
Dariusz Kupisz

Bibliographic record

VenueRes Historica · 2022
Typearticle
Languagepl
FieldArts and Humanities
TopicHistorical and Cultural Studies of Poland
Canadian institutionsnot available
Fundersnot available
KeywordsInfantryQuarter (Canadian coin)Context (archaeology)PoliticsLimitingMilitary tacticsHistoryCommonwealthOfficerLawAncient historyPeriod (music)Economic historyClassicsPolitical scienceArchaeologyEngineeringArt

Abstract

fetched live from OpenAlex

Andrzej Maksymilian Fredro is one of the leading Polish writers of the Old Polish era who dealt with military reform issues. The article presents his ideas on replacing the mass levy with a new type of military unit made up of the peasants appointed in a number proportionate to the size of arable land, presented in his four writings from the period between 1668 and 1675. Those soldiers were designated by the landowners of noble, royal, and Church estates. Initially, Fredro regarded them as mere support for the traditional mass levy and permanent mercenary troops (called in Polish wojsko zaciężne). Ultimately, however, he opted for limiting the latter to 5,000 soldiers of the so-called ‘quarter army’ (in Polish: wojsko kwarciane – as a quarter [kwarta] of income from the royal lands was to be used for their upkeep). In place of the mercenary army and mass levy, he proposed an expedition of soldiers drafted per the income or the land area (the number of lans, called in Polish łan or, in Latin, laneus). He expected as many as several tens of thousands of armed men, which, as practice showed, was unrealistic. In this context, Fredro’s proposals did not differ from similar ideas presented in numerous treatises and political writings throughout the seventeenth century. With few exceptions, mass levies and expeditions did not make an outstanding contribution to the history of the Commonwealth wars. However, the writer’s reasonable demands concerning the armament of cavalry and infantry, equipping them with large ammunition stocks, limiting the number of wagons, training soldiers, and providing adequate provisions for the army should be pointed out.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.027
GPT teacher head0.211
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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