Disaster as a formative experience: the Leningrad flood of 1924
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.024 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".