Dima Adamsky/ Stanford University Press, The Culture of Military Innovation: The Impact of Cultural Factors on the Revolution in Military Affairs in Russia, the US and Israel.
Bibliographic record
Abstract
Dima Adamsky'sThe Culture of Military Innovation is an account of how one intellectual paradigm, called the Revolution in Military Affairs (RMA), rose and fell in the militaries of the USSR, USA and Israel.Adamsky characterizes it as an empirical and theoretical contribution to the third, constructivist wave of strategic culture scholarship.This subdiscipline has made various attempts to identify culture, instead of rationality, as "the pivotal intervening variable" in military development.The study distinguishes itself within its subdiscipline for its excellent sources (archival material from all three countries and interviews in Israel), skillful argumentation, and very intelligent case selection.Adamsky's cases connect logically and make for compelling reading.Theorists working in the USSR coined RMA to refer to a series of insights derived from analyzing new NATO (mainly American) threats.The Soviets realized that American long-range weapons and sensors seriously undermined conventional Soviet field placement.This prompted a wild futurology among a powerful cadre within the general staff.They thought they had discovered an entirely new force paradigm, the key principles of which were low density, high velocity troop deployment and an absolute need to maintain technological parity or advantage.Happily for the Soviets, the Americans were slow to catch on.They had developed the technology in order to strike deep into the Soviet rear echelons, but did not perceive other uses for it until they translated the Soviets' professional journals in the late 1980s.Not until Desert Storm (1990-1) did they implement their version of RMA.Its perceived success in that conflict initiated Donald Rumsfeld's controversial "Transformation," a series of major operational, organizational and budgetary changes to the Department of Defense and the services.Having studied the Soviet military journals and kept abreast of American technological developments, the Israelis were the first to wage an RMA-style war.They successfully fused Soviet principles and American technology in the First Lebanon War in 1982.This prompted the Israeli Air Force to embrace RMA.RMA theorizing gradually spread through-
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.013 |
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".