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Record W4244848783 · doi:10.22215/etd/2014-10372

The Impact of the Russian Military System on Nineteenth Century Russian Expansionism in the Caucasus and Central Asia

2014· dissertation· en· W4244848783 on OpenAlexaff
S. V. Eaton

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsCarleton University
Fundersnot available
KeywordsExpansionismCentral asiaPolitical scienceCONQUESTAncient historyGeographyHistoryLawPolitics

Abstract

fetched live from OpenAlex

This work explores the Russian military system after the Napoleonic Wars, and the impact the military ideologies developed therein had on Russian expansionist efforts in two separate conflicts. The Russian conquests of the Caucasus and Central Asian regions are the expansionist efforts under focus, and specifically battles at Dargo in the Caucasus and Khiva in Central Asia are analyzed. It is argued that, due to a Russian military system that refused to move away from Napoleonic era tactics and ideas, the conquest of the Caucasus was a far more difficult endeavor than the Russian seizure of Central Asia, where largely similar tactics were employed. The established Russian military system created a military that was ill-suited for combat in the Caucasus, and disabled its ability to learn from that conflict. This same system was equally responsible for allowing the Russians to easily defeat their enemies in a Central Asian setting.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.862
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.276
Teacher spread0.268 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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