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Record W1481052930 · doi:10.21226/t2z595

The Impact of Holodomor Studies on the Understanding of the USSR

2015· article· en· W1481052930 on OpenAlexvenueno aff
Andrea Graziosi

Bibliographic record

VenueEast/West Journal of Ukrainian Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
Fundersnot available
KeywordsPeasantModernityContext (archaeology)Political scienceState (computer science)Soviet unionPolitical economyPower (physics)Development economicsSociologyPoliticsLawHistoryEconomics

Abstract

fetched live from OpenAlex

This paper investigates what the Holodomor tells us about the development and dynamics of Soviet history. It starts by examining the evolving relations between Stalin and the peasantry during the Soviet Union’s first decades as well as the social, economic, moral, and psychological consequences in the USSR after 1933 following the destruction of traditional rural society. The relationship between the Holodomor and the viability of the Soviet system will then be discussed along with the opportunities that history presented to the Soviet leadership after 1945 to reverse the country’s critical 1928-29 decisions. This leadership’s awareness of the tragedies of the 1930s in the countryside, as well as of their consequences, will then be raised, before shifting the focus to the linkage between the peasant and the national questions in Soviet history. In this context the Holodomor will be discussed as a tool to solve both the peasant and the national “irritants” caused by Ukraine to both the Soviet system and Stalin’s personal power. The legacy of such a “solution” will then be addressed, including a consideration to the background of the collapse of the Soviet system from the perspective of the sustainability of a state whose past is marred by unacknowledged genocidal practices. Finally, the consequences of the growing awareness of the Holodomor’s importance and nature on the USSR’s image will be discussed. In particular, the question of the “modernity” of the Soviet system and of the “modernizing” effects of Stalin’s 1928-29 policies will be raised.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.013
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0060.040
Scholarly communication0.0090.013
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.377
GPT teacher head0.432
Teacher spread0.054 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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