Bibliographic record
Abstract
The struggle against banditry cannot be waged separately from class struggle. – Vladimir Shcherbakov, head of the VKP(b) CC Bureau for Lithuania In order to suppress resistance in the western borderlands, the Soviet state armed thousands of local peasants who fought the insurgents side by side with the regular forces. This chapter explains why the government organized militia from populations it mistrusted and investigates the social composition of the Soviet paramilitaries, their motivations to enlist, the difference between the militias operating in the old territories and in the borderlands, and the problems that the government experienced with those in the western regions. The militia suffered from grave flaws and often remained merely an antiguerrilla tool rather than a law enforcement agency, but it was, nevertheless, a vital component of the Soviet pacification. Every government fights guerrillas primarily with its army and police. The army is an appropriate means against rebels operating in large formations, but it is ineffective against fragmented resistance focusing on terror against local administrators. In rebellious rural regions, the army most often is alien, its personnel recruited from all over the country and lacking expertise in local affairs and culture. Unable to identify the insurgents, soldiers vent their frustrations on peasants, thus driving them to support the guerrillas. Police are better suited to counterinsurgency, being submerged in the local milieu, but they usually lack the manpower needed to cover an entire rebellious area, whereas dispersal in garrisons reduces their offensive capabilities and leaves the initiative to the guerrillas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".