Reframing Civil–Military Relations in the EU: Insights From the Drone Strategy 2.0
Bibliographic record
Abstract
Abstract In November 2022, the European Commission presented its Drone Strategy 2.0 with two main objectives: to build the European Union's (EU's) drone service market and to strengthen the Union's civil, security and defence industry capabilities and synergies. From the Commission's perspective, accelerating the integration of drones in Europe's airspace has the potential to enable progress on numerous policy objectives, such as the green transition, urban mobility, industrial renewal and cutting‐edge R&D in the civil–military domain. In this commentary, though, we argue that the Strategy is indicative of wider contemporary trends in EU policy‐making regarding cross‐cutting policy agendas, industry‐centred R&D ambitions and the identification and promotion of infrastructural goals enabling further civil–military co‐operation. These tendencies capture the growing importance of dual‐use technologies, both in society at large and in the security and military domains. This is particularly relevant in the current European context of growing military expenditure with the war in Ukraine.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".