Bibliographic record
Abstract
This book is about the role of national parliaments in the EU, in particular the power asymmetries that exist between the different parliaments and how these asymmetries affect representative democracy in the EU.Almost five years ago, when I submitted the research proposal for this project, the topic was a completely different one -and to this day and for that reason many close friends and colleagues are still surprised when they learn the present title of this book.From the beginning of the book in 2013 until its final draft in spring 2018, it was not only my thesis project that has gone through considerable changes but also I have learned a lot in the process, both on a professional and on a personal level.My gratitude goes first and foremost to my promotors, Aalt Willem Heringa and Wytze van der Woude.Without their guidance and their firm belief in the book's value even when I had my doubts the writing process would have been indefinitely more difficult.I also wish to thank Bruno de Witte, Mark Dawson, Luc Verhey and Sascha Hardt for agreeing to read this thesis and for providing valuable comments on the
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".