Les dépenses militaires soviétiques ou le fardeau de la défense soviétique
Bibliographic record
Abstract
Our understanding of the Soviet defence burden remains woefully inadaquate. The official Soviet defence expenditure figure is not helpful. It is not inclusive. There is no concensus on what or how much is covered by other budget accounts. Soviet statistics do not allow independent calculation. Official Western estimates, on the other hand, are equally dubious. They reflect more on Western political dynamics than on Soviet reality. The Soviet defence industry is not immune from the vicissitudes of the economy at large. The Soviet military do not enjoy carte blanche. They contribute extensively to civilian needs, both in terms of goods and services. But, in turn, they extract benefits from a wide range of civilian endeavors. The military-political culture, rooted in an older Moscovy, and reinforced by Lenin's Clausewitzian leanings, is quite different from that which prevails in the west. There is no military-industrial complex threatening the Soviet State. In the USSR the military is OF the State, integral to a wider establishment. The military burden cannot be specified, for much is inextricably fused with the burden of State, and culture. It is systemic. It will be sustained. Because it is OF the System. Western debate is ethnocentric. We need new research, new under standing.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".