The Two Faces of Petr Arkad'evich: Land and Dispossession in Russia's Southwest, ca. 2000
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract At the beginning and the end of the twentieth century, the Russian imperial and post-Soviet governments pursued large-scale projects to transform land tenure in the countryside. Based on the belief that people would work harder and more productively on land they themselves owned, both reform programs divided collectively-managed land into individual parcels. Post-Soviet land privatization, consciously modeled on the Stolypin-era reforms conducted in early twentieth-century Russia, resulted in the dispossession of much of the rural population. This article examines privatization in a district of Voronezh oblast ’ in Russia's southwest, considering contemporary processes through an historical lens. It shows how successful local efforts to adapt to markets and preserve large-scale agriculture nonetheless resulted in rural dispossession.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it