ANALYSIS OF THE EXISTING EXPERIENCE IN THE IMPLEMENTATION OF MODELS OF ORGANIZATION AND SUSTAINABLE FUNCTIONING OF AGRICULTURE BASED ON TRADITIONAL ECONOMIC ACTIVITY IN THE RUSSIAN FEDERATION AND IN THE COUNTRIES OF THE CIRCUMPOLAR ARCTIC TERRITORY
Bibliographic record
Abstract
The article considers the existing experience in the implementation of models of organization and sustainable functioning of agriculture based on traditional economic activities. The analysis is based on the practices of organizing agriculture among the indigenous peoples of the North, both in Russia and in other subarctic countries. In the course of the analysis of domestic experience, the practices of the Soviet period are considered. At this time, for such a form of traditional agriculture as reindeer herding, a form of reindeer herding collective farms and state farms was created. The form of organization of hunting for the purpose of producing furs (fur resources) and meat products (game and meat resources) — hunting enterprises and fur farms (cage fur farming), as well as procurement offices (raw material collection points), which also acted as forms for other species traditional economic activities — fishing, collecting and harvesting wild plants. The article also considers the experience of organizing and functioning of agriculture based on indigenous crafts in the USA, Canada, Denmark, Norway, Sweden, Finland and Iceland.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".