But who's flying the plane? Integrating UAVs into the Canadian and Danish armed forces
Bibliographic record
Abstract
North Atlantic Treaty Organization (NATO) members such as Canada and Denmark have transformed their military forces to better engage in expeditionary warfare. They are incorporating advanced technologies to find and strike targets precisely from great distances at little risk to themselves. The persistence of unmanned aerial vehicles (UAVs) represents the next step in modern airpower's long-range reconnaissance/precision strike complex and has transformed ground operations. Nonetheless, operational requirements in Afghanistan caught Canada and Denmark flat-footed. Ultimately, Canada effectively used UAVs while Denmark could not. Moreover, neither state has a UAV capability beyond small tactical systems (although each has plans to develop or join in the development of larger ones). The Canadian and Danish experiences suggest that ground forces are most likely to acquire and integrate small UAVs into their force structures and concepts of operation and that the air forces of small- and medium-sized Western countries will likely do so only in cooperation with others. It is here that the Canadian and Danish UAV paths may yet again cross.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".