No supply without demand: explaining the absence of the EU Battlegroups in Libya, Mali and the Central African Republic
Bibliographic record
Abstract
Although the sad track record of the EU Battlegroups has attracted considerable scholarly attention, analyses have largely focused on obstacles related to the provision of the Battlegroup troops and to the consensus within the EU Council, hence taking a supply-side perspective. This article calls for complementing this perspective with an analysis of the demand for their deployment. That implies analysing whether and why the EU Battlegroups were (not) considered as an option by those actors taking the initiative to intervene in a particular crisis. Applying a rational-institutionalist approach, this article explains the absence of the Battlegroups from three recent crises: Libya (2011), Mali (2013) and the Central African Republic (2013–2014). Using data from document analysis and elite interviews, it shows that once a rapid military reaction became urgent, the EU Battlegroups were not even considered as an option by those initiating an international reaction.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".