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Record W4415616412 · doi:10.1080/00085006.2025.2546236

Disaster as a formative experience: the Leningrad flood of 1924

2025· article· en· W4415616412 on OpenAlexvenueno aff

Bibliographic record

VenueCanadian Slavonic Papers · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
Fundersnot available
KeywordsFlood mythFormative assessmentNatural disasterFlood controlDisaster preparedness

Abstract

fetched live from OpenAlex

Critical Disaster Studies – an emerging subfield of environmental history and memory – probes disasters as socially constructed political events that take place over time. Scholars of the Soviet Union are far from new to the study of disasters, as many policies and projects have been considered in light of calamities that either hindered socialist construction or demonstrated deep-seated failures of Soviet policy, science, and technology. Yet few scholars approach disasters in the Soviet Union as critical moments of state-building, in which narratives of confrontation, recovery, and reconstruction became integral means of justifying party rule. This article examines the Leningrad flood of 1924 not only as one of the Soviet Union’s first “natural” disasters, but as one that strengthened the Communist Party’s stature and propaganda machine. It expands, furthermore, on the conceptual relationship between disaster and state formation, revealing how local concerns like flood risk became tethered to the party leadership’s legitimacy through commitment to mobilizing scientific, technical, and civil efforts to mitigate and eradicate floods.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.217
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0320.024
Scholarly communication0.0080.005
Open science0.0010.008
Research integrity0.0030.006
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 head0.008
GPT teacher head0.286
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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueCanadian Slavonic PapersSame topicSoviet and Russian HistoryFrench-language works237,207