The Role of the USSR Academy of Sciences in the Formulation of the USSR Science and Technology Policy in the 1920s – 1940s
Bibliographic record
Abstract
In the first quarter of the 20th century no common scientific policy existed neither in the Russian Empire nor in the Soviet Union although there was a need for such a policy in view of the want of addressing the tasks of industrialization and overcoming the country’s technology gap. The article shows how the young Soviet state formulated its science and technology policy priorities and how it succeeded in creating one the most effective science organization systems in the world. We analyze the measures aimed at introducing planned scientific research, creating scientific institutes, establishing a network of scientific centers in the country’s remote regions, and organizing postgraduate education to train the cadre of scientists. Taken together, these measures resulted in the emergence of a unique scientific complex whose formation proceeded differently than that in the advanced countries of the West. The intensified development of Soviet science occurred at the same time as global changes in the role of fundamental science in the progression of modern civilization. By the late 1940s, global science became a driver in the development of modern society and Soviet science in many aspects found itself at the forefront of this process.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".