Bridging the gap between facts and norms: mutual trust, the European Arrest Warrant and the rule of law in an interdisciplinary context
Bibliographic record
Abstract
Abstract The rule‐of‐law‐backsliding in some Member States has subverted not only one of the EU fundamental values but also trust among national authorities when implementing European Arrest Warrants (EAW). However, when evaluating the execution of EAWs issued by countries experiencing rule‐of‐law crises, the Court of Justice of the EU (CJEU) sought to preserve judicial cooperation and imposed a rather “top‐down” view on mutual trust among Member States. This approach seemingly disregards the (dis)trust which has emerged in the EU due to rule‐of‐law‐backsliding and fails to acknowledge the psycho‐sociological nature of trust. Drawing on the trust literature, the paper offers novel conceptual elements to rethink mutual trust in the EAW framework. Notably, it critically assesses some of the gaps in the CJEU's interpretation of mutual trust and advances suggestions to embed empirical considerations in the conceptualisation of this principle to bridge the gap between trust in practice and in principle.
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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 | 0.033 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.082 |
| Scholarly communication | 0.022 | 0.022 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.010 | 0.007 |
| 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".