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Record W4386793723

Reflection of Time of Troubles Events in Polish Poetry of the First Quarter of 17<sup>th</sup> Century (by Example of Adam Vladislavsky’s Works)

2017· article· en· W4386793723 on OpenAlexaboutno aff
N. V. Eylbart

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Cultural Studies of Poland
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PoetryReflection (computer programming)ArtLiteratureHistoryArt historyPhilosophyArchaeologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The article considers Polish poetry of the first two decades of the 17th century as historical source. Attention is focused on the works of Adam Vladislavsky, Krakow’s craftsman, a representative of the so-called “bourgeois poetry,” which to some extent reflects the events of the time of Troubles in Russia. The work “Lament of the Queen of Moscow” is subjected to a detailed analysis. Translation of the poem into Russian language was made by the author. It is noted that the poem is not so much elegiac but political in character: it is written on behalf of Marina Mnishek and urged compatriots to avenge the wrongs inflicted on her. The characteristic of this poetry as a means of influencing public opinion, the mouthpiece of the propaganda of certain political circles of the Polish-Lithuanian Commonwealth of that time is made. It is concluded that the author of analyzed works is not a supporter of any particular political platform, and his view expressed in poetry depended on the rapidly changing conjuncture, which in turn was in close relationship with the patronage of those persons by whose order at one or another time the poems were created.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.006
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.158
GPT teacher head0.431
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2017
Admission routes1
Has abstractyes

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