The introduction of the agricultural technologies by the occupation authorities in the Kherson region in 1941–1944
Bibliographic record
Abstract
Introduction. The article explores the little-known facts about the implementation of technologies aimed at preserving the harvest and increasing its volumes by the occupation authorities.Purpose. It is suggested to study the organizational measures and technologies of preservation and increase of productivity in public and state farms and the work of the population on their implementation, which were proposed by the occupiers.Results. The organization by the occupation authorities various measures to ensure conservation of crops and increase results of agricultural products in the Kherson region in 1941-1944 was shown detailed in the article. The work to preserve and increase the forest shelter belts, which were destroyed by the local population through a shortage of fuel, has been reconstructed on the materials of the district and rural activities structures. The organization of fire protection of fields by creation of observation system, fire brigades and introduction of rigid instructions on use of fire dangerous technology is shown; the forms of punishment for negligent behavior with fire are characterized. The organizing work on pest control in the fields, in orchards and places of agricultural products storage, punitive and encouraging methods of its organization are reflected in the article. The process of introduction of agrarian innovations, technologies for efficient production of organic fertilizers and creation of a system for the preservation of water resources are described.Originality. The scientific novelty of the research results is a detailed reconstruction of the implementation of agrarian and technical innovations in the farms of Kherson region.Conclusion. The authorities introduced a rigid system of fines for tree felling, a special forestry service, and imposed protection obligations on special farm workers for forest conservation, which played a key role in a region where wind erosion was a major threat. The district governments have introduced a number of measures to prevent fires: fines, outreach, the creation of fire brigades and wagons, the introduction of a system of circular responsibility. Effective methods of chemical use were used to control pests and the peasantry was stimulated. The occupying authorities have launched a program to effectively utilize agrarian crop innovations, organic fertilizers and water supplies taking care of productivity improvements. The author plans the further study of the topic about the reconstruction of the realities while the German occupation, and the relationship between the peasantry and the occupation authorities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".