Cooperation in Rural Russia: Past, Present and Future
Bibliographic record
Abstract
Alexander Sobolev – Doctor of Science in Economics, Professor, Russian University of Cooperation. Address: 12/30, V.Voloshina St., Mytishchi, Moscow Region, 141014, Russian Federation. E-mail: sobolev-alekc@mail.ru Alexander Kurakin – Senior Researcher, Laboratory for Studies in Economic Sociology, National Research University Higher School of Economics; Senior Researcher, Center for Agrarian Studies, Russian Presidential Academy of National Economy and Public Administration (RANEPA). Address: 11, Myasnitskaya St., Moscow, 101000, Russian Federation. E-mail: akurakin@hse.ru Vladimir Pakhomov – Doctor of Science in Economics, Professor, Russian University of Cooperation. Address: 12/30, V.Voloshina St., Mytishchi, Moscow Region, 141014, Russian Federation. E-mail: vmpahomov@yandex.ru Irina Trotsuk – Doctor of Science in Sociology, Senior Researcher, Center for Agrarian Studies, Russian Presidential Academy of National Economy and Public Administration; Associate Professor, RUDN University. Address: 82, Vernadskogo Av., Moscow, 119571, Russian Federation. E-mail: irina.trotsuk@yandex.ru Citation: Sobolev A., Kurakin A., Pakhomov V., Trotsuk I. (2018) Cooperation in Rural Russia: Past, Present and Future. Mir Rossii, vol. 27, no 1, pp. 65–89. DOI: 10.17323/1811-038X-2018-27-1-65-89 The authors consider cooperation as a specific, alternative form of economic organization to the standard business firm within a market economy, and focus on agricultural cooperation in Russia. First, the article engages with the key milestones of the history of cooperation in Russia: (1) the first attempts to establish cooperative organizations before the Russian Revolution (agricultural societies, agricultural partnerships and credit cooperatives) which gave the poor rural population a chance to improve living standards and ensured promising prospects for the long-term development of cooperation in all forms; (2) the dependent forms of consumer and production cooperation under the Soviet regime that deprived all collective forms of their true cooperative nature. In the second part of the article, the authors describe the current state of the cooperative movement in the Russian countryside and identify its basic features, such as opposition to family farming and the state capitalist tendencies of the concentration and vertical integration in the form of agroholdings; state rural cooperation policies which aim to promote and financially support small farming including the development of rural cooperatives; the number and types of cooperatives in the countryside; the reasons for debates on cooperation legislation; the viability of the main types of agricultural cooperatives (production, consumer, credit cooperation). Finally, the authors emphasize that cooperation in contemporary Russia does not fit the classic Western scheme of cooperative development and still has to overcome a number of substantial challenges (the soviet legacy, lack of bottom-up initiatives, the ideological and economic dominance of large-scale farming, poor academic expertise in the field of cooperation studies).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".