Bibliographic record
Abstract
This Journal has a somewhat special origin. The first issue of the actual Federalisme Regionalisme appeared in 1999-2000. That was however not the real beginning. There is a history that goes further back. A journal aiming at discussing issues related to federalism in Belgium was launched already in 1988. It was then called Coudenberg - Journal for Federalism and Democracy. The publisher was the Coudenberg Group, a collection of 47 prominent members of different sectors of Belgian society and 28 ‘young members’ who came mainly but not exclusively from the academic world. The Group was led and financed by Jean-Pierre De Bandt, chair of the law firm De Bandt, van Hecke & Lagae. That Coudenberg Group wanted to analyze and discuss the Belgian political system and its ongoing reforms in the light of theories of federalism. The Rapport Coudenberg1 that was published in 1987 put forward ‘twelve commandments’ of a classic federalism and concluded that many of these were not met by the way in which the Belgian state was being reformed. This classic federalism was however for the Coudenberg Group the way to go. We will not discuss the details of this rather negative evaluation of the Belgian system of the late 1980s, but must note that it was being evaluated against an ideal type of what a federal state should be, an ideal type modelled mainly on cases like the US and Canada, and to a lesser extent on Australia, Germany or Switzerland. The leading scholars on federalism were at that t
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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 | 0.002 | 0.003 |
| 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 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".