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Russian Expansion in the Baltic in the 18th Century

2022· article· en· W4323649297 on OpenAlexaboutno aff
Arkadiusz Janicki

Bibliographic record

VenueStudia Historica Gedanensia · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCentral European and Russian historical studies
Canadian institutionsnot available
FundersNarodowe Centrum NaukiUniversity of Cambridge
KeywordsBaltic seaLithuanianCommonwealthEmpireQuarter (Canadian coin)State (computer science)Power (physics)GeographyEconomic historyHistoryEconomyPolitical scienceAncient historyArchaeologyOceanographyEconomicsGeology

Abstract

fetched live from OpenAlex

Russia’s expansion in the Baltic region in the 18th century was neither an obvious nor historically justified direction. It was Peter I who abandoned the expansion to the south and east in favor of the west. The rise of Russia’s power on the Baltic was linked to the decline in importance of the 17th‑century powers blocking its path to Europe: Sweden, the Polish‑Lithuanian Commonwealth, and the Ottoman Empire. When Peter I the Great took power Russia had no access to either the Baltic Sea, the Black Sea or the Sea of Azov. However, thanks to Peter I’s consistent policy and the actions of subsequent Russian rulers, during the 18th century Russia not only gained access to the Baltic Sea, but also conquered several strategically important ports and became the largest naval power in that area. A symbolic confirmation of the change in the direction of Russian policy in the 18th century can be the transfer of the capital of the state from Moscow to St. Petersburg in 1712. St. Petersburg was a “window on Europe”for Russia and the wide access to the Baltic Sea enabled Russia to influence the fate of the whole of Europe. This article tries to identify the most crucial moments and events that determined the success of Russian policy on the Baltic in the 18th century.

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)0.000
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.262
Teacher spread0.239 · 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
Published2022
Admission routes1
Has abstractyes

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