USAF Relevance in the 21st Century. A First Quarter Team in a Four Quarter Game
Bibliographic record
Abstract
The rise of terrorism by non-state actors as a primary threat to U.S. national security challenges the relevance of air and space power. This study first looks at the current and foreseeable security environment and identifies weak/failing states as the largest strategic threat to the United States since the Cold War. Next, the paper describes the culture of the U.S. military as a whole and assesses the relevance of the current American way of war to meeting the challenges of the weak/failing state security threat. If the military studied military operations other than war "MOOTW" lessons as much as the combat lessons, they would see that the U.S. has always struggled with winning the peace in operations short of major combat. Third, the author examines how the United States Air Force's preferred way of war coupled with a service bias toward combat flying has manifested itself in a body of doctrine that limits the ability of the service to provide a stronger contribution to the nation. Just as the Air Force balanced the nuclear and conventional force structure in favor of conventional forces, the USAF must now think about tailoring its conventional forces for major combat operations to ones more suitable for MOOTW. Finally, the author provides recommendations for the Department of Defense in general and the USAF in particular, to transform educational and doctrinal thinking to embrace capabilities ready to respond throughout the spectrum of conflict.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".