Development of Felted Footwear Craft in Tambov Province During Transition from Late Imperial to Soviet System
Bibliographic record
Abstract
This article examines the development of the handmade felted footwear craft within an agrarian region. The novelty of this study lies in its interdisciplinary approach and its analysis of an extensive timeframe encompassing the late Imperial era, the period of War Communism, and the years of the New Economic Policy (NEP). The research draws upon a diverse source base, including regional archival documents, the authors’ own field archive of oral histories, published statistical data, administrative records, and contemporary periodicals. The study demonstrates that during the late Imperial period, the work of felters was predominantly subsistence-based, with cottage industries only beginning to emerge in areas with a high concentration of artisans. It is reported that the mechanization of production progressed at a slow pace. Furthermore, the authors conclude that the rapid development of trade cooperatives among felters during War Communism was driven by the demands of the military front. The article also pays particular attention to explaining the reasons for the decline in the number of these trade cooperatives during the NEP. Finally, it is emphasized that the concurrent use of dialectal and literary lexicon related to the professional domain within the same locality not only reflects a deep-seated cognitive framework for labor but also underscores the significance of specific types of work and the value of artisanal skill.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".