Public Budgeting in the EU Commission:A Test of the Punctuated Equilibrium Thesis
Bibliographic record
Abstract
We test a punctuated equilibrium model of budgeting in the context of the European Union. Compared either to the US or to the national systems of its member states, we know little about the impact of the institutional design of the EU on its internal budgeting processes. For one, we do not know whether the heterogeneous preferences of each member-state are likely to create friction or venue-shopping towards the EU Commission. This paper first describes European budgeting processes since the inception of the EU, taking into consideration the enlargement process. In a second section, we present European budgeting data to test models of friction, incrementalism, and punctuated equilibrium, drawing from a developing literature with US and European applications. The findings make clear that EU budgeting processes correspond to a punctuated equilibrium model of budgetary choice, as previous studies have recently shown for the US and many European member states.
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How this classification was reachedexpand
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".