Empirical legitimation analysis in International Relations: how to learn from the insights – and avoid the mistakes – of research in EU studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The political legitimation (or de-legitimation) of the European Union (EU) has been the object of much empirical research. This paper argues that this research holds lessons that can inform debates about the legitimation of global governance more generally. After some conceptual clarifications, the paper presents a critical review of the literature on the EU’s legitimation, focusing on six crucial aspects – (1) the emergence and change of legitimation debates; (2) the arenas where legitimation occurs; (3) the role of the state as a reference point in legitimacy assessments; (4) the difference between various objects of legitimation; (5) the actors that trigger legitimation change; as well as (6) the relationship between legitimation and polity development. In each of these respects, the paper identifies important insights that can be gained from EU Studies, but also conceptual and methodological weaknesses in the EU-related literature that researchers working on other aspects of global governance should avoid. The paper closes by formulating a set of general desiderata for empirical legitimation research in International Relations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it