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Record W4398247167 · doi:10.1111/russ.12652

A Woman’s Empire: Russian Women and Imperial Expansion in Asia by Katya Hokanson. Toronto: University of Toronto Press, 2023. x + 344 pp. $80.00. ISBN 978‐1‐4875‐4560‐4

2024· article· en· W4398247167 on OpenAlexaboutno aff
Sibelan Forrester

Bibliographic record

VenueThe Russian Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmpireHistoryEconomic historyAncient history

Abstract

fetched live from OpenAlex

The title A Woman's Empire might bring to mind Catherine II, "the Great," who oversaw considerable Russian imperial expansion.The actual focus of Katya Hokanson's book emerges in her subtitle: Russian Women and Imperial Expansion in Asia.It treats the writing of women who traveled in Asia, especially Central Asia, in the later nineteenth century in the context of their travels or expeditions.This overlaps with analogous writings from other parts of the empire, such as Olga Semyonova Tian-Shanskaia's ethnographic study Village Life in Late Tsarist Russia (translation published 1993); indeed, her father got the extra surname to honor his explorations in the Tian-Shan mountains, near the Pamirs, which feature in this book.The topic also resonates with the final expedition of Fyodor Godunov-Cherdyntsev's entomologist father in Nabokov's novel The Gift, as Hokanson briefly notes (p.20): this moment in late imperial scientific ambition has been important in Russian history and culture.The peasants back home recur in implicit or explicit comparison to the residents of Central Asia encountered by these authors.The topic lets the reader look at practices and assumptions of imperial expansion and Russia's "civilizing" mission (both of these in competition with Britain) while considering women's roles in science and the imperial bureaucracy.The writers treated at significant length are Vera Dukhovskaia, Elena Apreleva, Elena Blavatskaia, Iuliia Golovnina, Aleksandra Potanina, Ol'ga Fedchenko, Praskov'ia Uvarova, and Anna Rossikova.Among them only Blavatskaia is widely known (as Blavatsky in the West), though Apreleva has received attention from scholars of women's writing.Most of the women have been discussed by other scholars, cited here, but this is the first time they have been treated together, making for some interesting comparisons.The texts treat travel to Turkestan, including the Pamirs, and to a lesser extent the Far East; they present a variety of memoir, stories, and scientific or ethnographic records.Hokanson makes the important point that surveying previously unknown territory scientifically means assimilating and claiming its natural riches-and this was recognized by the local population, though they were "pacified" by the time of the expeditions she addresses.Hokanson spends considerable time citing men who wrote about the same areas or expeditions-Golovnina's husband; Colonel Olcott, the co-founder of Theosophy and Blavatskaia's fellow traveler in India.This provides context, though it is not always clear whether the reader is meant to understand better the ambitions of the expedition or to evaluate the woman's writing alongside the men's, particularly with regard to Blavatskaia and her veracity.Hokanson returns again and again to the Great Game and Russia's imperial competition with Britain, reflected in the competition of individual writers (especially Blavatskaia) with other or earlier writers.Some texts were quickly or even originally published in English, foregrounding the sense of a common interest in Central Asia.Some of the various editions offer different information and interpretation, and Hokanson usefully teases out how

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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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