Bibliographic record
Abstract
T he European Union (EU) has witnessed a growth in innovative gover- nance in recent years, much of which is not well understood.This book offers a comprehensive account of what characterizes the modes of governance in various areas of EU policymaking.From the outset the project aimed at being more ambitious than most, asking what the specific characteristics of European modes of governance across policy areas are and how EU governance and policymaking differ from those at the national level.To embark on such an ambitious study obviously required major preparation.As editors and authors, we are indebted to institutions and people for the support we received along the way.The book is the product of half a decade of collaboration.We first met in 2003 at the Max Planck Institute for the Study of Societies in Cologne, Germany, where we were both visiting fellows on sabbatical leave.It was then that we started to think about working together on a major project.In 2004 we designed a research study in which we could identify the nature of EU governance and policymaking.We applied for and received research support from the Canada Council for the Arts and the Social Sciences and Humanities Research Council of Canada (SSHRC) that enabled Ingeborg Tömmel to spend the academic year 2005-2006 at the University of Victoria as holder of the Diefenbaker Award.During this time we developed the analytical and theoretical framework of the research and also held a conference in Victoria in March 2006 with scholars from both sides of the Atlantic.The conference was aided by a general SSHRC grant (646-2005-1135).We gratefully acknowledge additional financial support by the University of Victoria and the British and German consulates.We owe a debt of gratitude to Lynne Rienner, who was from the outset as excited as we were about the idea of publishing this book and who, along the way, provided numerous suggestions for improvement.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.365 | 0.223 |
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".