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Russia as the “Western Other” in Southeast Asia: Encounters of Russian Travelers in the Second Half of the Nineteenth Century

2012· article· en· W2011144638 on OpenAlexaff
Karen A. Snow

Bibliographic record

VenueThe Russian Review · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicColonial History and Postcolonial Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsThroneEmpirePower (physics)ChinaGovernment (linguistics)Ancient historyMythologyEconomic historyPolitical scienceEast AsiaHistoryLawPoliticsClassics

Abstract

fetched live from OpenAlex

This article explores an intriguing and unexplored angle of the evolution of Russia's Asian Mission in the second half of the nineteenth century. In 1869 the opening of the Suez Canal increased Russian shipping to the Far East and brought more Russian travelers to Southeast Asia where in an interesting coincidence of local interests and imperial views they interacted with the local rulers, officials in the region. As scholars, naval officers or government officials/advisors they wrote literary accounts or reports of their journeys and sometimes gave public presentations on their experiences which informed the Russian public and government about British and French expansion in the region and the local perception of Russia as a European power. One of these travelers included the heir to the throne and future tsar of Russia, Nicholas II and his mentor E. E. Ukhtomskii, later a prominent exponent of Russia's Asian mission. By examining the contact of Russian travelers with the rulers and officials of Burma and Siam this article reveals how the interpenetration of Russia's imperial myth of an Asian Mission with an Occidental view of Russia in Burma and Siam helped confirm the empire's notion of a “civilizing mission” and its claim of moral and cultural superiority to other Western powers.

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)0.001
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: none
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.302
Teacher spread0.278 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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