Curative Mythmaking: Children's Bodies, Medical Knowledge, and the Frontier of Health in Early Soviet Odesa
Bibliographic record
Abstract
This essay explores how Soviet authorities appropriated medical knowledge derived from the treatment of a “passive” juvenile population to create a new assurance of municipal well-being in the 1920s. The attempt to control and remediate the spread of disease reflected a Bolshevik certainty in the state’s ability to confront the frontier of health by applying the dictates of modern science. Revolution and civil war brought challenge—the fractured city changed hands repeatedly until a final, tentative victory by the Red Army in 1920. Odesa’s children figuratively confronted a political, moral, and social liminality, standing between the diseased, corrupt yesteryear and a salubrious, principled future. Soviet central authorities sought to revive the newly liberated city by establishing a network of children’s institutions in which they would contain contagion, but also bring the full spectrum of applied expertise to bear on young bodies. In this traumatized city at the Soviet Union’s edge, state custodians would raise a new, loyal generation. Its health would signify revolution achieved. Illness would continue to plague the city’s residents, but the myth of a community united in health created an ecology of promise and activism.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.045 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".