The Transformation of European Airpower: Implications for the Royal Danish Air Force
Bibliographic record
Abstract
Denmark will buy new fighter aircraft in 2015. This is stated in the 20014-17 Defense Agreement. The Danish Parliament will accordingly need to allocate funds in the range of 20 to 30 billion Danish kroner to replace the Royal Danish Air Force’s fleet of aging F-16 fighter jets. This will be the largest defence procurement program in a generation and it will have long-term effects on Danish military capabilities as well as the procurement plans and opportunities of the Danish Armed Forces. Substantial effort is currently being put into deliberating and preparing a comprehensive platform for making the final decision. A dedicated “New Combat Aircraft Program Office” within the Ministry of Defence is conducting analyses of the strategic, military, economic, and industrial issues inherent in the choice between the three competitor aircraft. These will inform members of Parliament as they choose the number and type of replacement aircraft. This decision, in turn, will determine the general capabilities and shape of the Royal Danish Air Force (RDAF) for the next 40 years. Denmark is not alone in making such significant decisions at this time. The United States, Canada, the United Kingdom, France, the Netherlands, Norway, and Sweden have faced similar requirements and have recently made, or will soon make, similar decisions. These countries have modernized, reorganized, downsized, restructured, adapted, and transformed their airpower capabilities in ways that can inform Danish decisions and stimulate debate about the future of Danish airpower. The intent of this symposium is to provide analyses of these experiences by scholars and officers from these countries to Danish civilian and military policy makers and to the wider public. Our objective is not to consider or judge which aircraft is best or make recommendations as to appropriate investments. It is, rather, to provide a platform for discussing the long-term opportunities and constraints that such an investment entails. If Denmark’s experience with the F-16s is instructive, new aircraft will enable new capabilities and new opportunities for their use. These could require changes in the organization of the RDAF, the number and type of its personnel, their training, education, and career development, ethos, the support and maintenance structure, and basing. Furthermore, a valuable lesson from the F-16 program is that international collaboration in missions, modernization, maintenance, and training is essential in today’s use of airpower. Understanding what Denmark’s allies and partners have done and will do to overcome similar challenges and realize similar opportunities should prove useful as politicians, civil servants, and officers are required to make further decisions as new aircraft are being integrated into Danish and allied air force structures in the period ahead.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".