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
Abstract The European Union (EU)’s small, balanced budget is commonly considered to be one of the most important constraints on the Union’s powers. However, the EU has always borrowed, and it is now borrowing on the scale of a large state to aid member states’ economic recovery from the COVID-19 pandemic and to support Ukraine’s wartime economy. This book tells the story of how the EU became a sovereign-style borrower from Jean Monnet’s ‘American Loan’ in 1954 to the operation of the Recovery and Resilience Facility seven decades later. Drawing on archival analysis and elite interviews, it charts the origins and evolution of the European Commission, the European Investment Bank, the European Bank for Reconstruction and Development, and the European Stability Mechanism as European-level borrowers and asks how these bodies’ accountability to parliaments, auditors, citizens, and civil society groups can be improved. Borrowing is not simply a technocratic issue, but one that raises fundamental questions about what sort of polity the EU is and how it could develop in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.008 |
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