Bibliographic record
Abstract
This chapter provides a summary of the deep-rooted connections between Canadian Doukhobors ( Doukhobortsy or Spirit Wrestlers) and Tolstoy, starting with important anti-militaristic events organized by the Doukhobor leader Peter Verigin at the end of the nineteenth century: refusals to serve in the army and the Burning of the Weapons in Doukhobor villages in the Caucasus, Russian Empire. These events as well as the following severe persecutions of Doukhobors in Russia caught the attention of Tolstoy because this peasant anti-militaristic movement resembled his own peaceful non-resistance teachings. Tolstoy became one of the most passionate protectors and a dear friend of the Doukhobors, commending their pacifism in his works. The chapter describes the first encounter of a group of Doukhobors with Tolstoy, and Tolstoy’s friendship and correspondence with Peter Verigin, as well as the pivotal role played by Tolstoy in organizing and funding the Doukhobors’ immigration to Canada. In conclusion, the author points out a few other correspondences between Tolstoy’s teachings and Doukhobor beliefs, such as agrarianism, communal cultivation of land, the unity of people, and rejection of Church institutions and priests. The chapter highlights the significance of pacifism (as it is understood by Tolstoy and the Doukhobors) in contemporary context.
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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 | 0.021 | 0.019 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".