Nuevas formas de distribución competencial: la legislación divergente en el federalismo alemán
Bibliographic record
Abstract
El funcionamiento practico de las tecnicas de comparticion competencial, en sus diversas variantes, acostumbra a dar lugar en los Estados compuestos a una progresiva ampliacion de la competencia federal sobre las materias previamente compartidas, con la consiguiente disminucion (y en ocasiones eliminacion) de la competencia correspondiente a las entidades federadas. Alemania no ha sido una excepcion a esta regla, y por ello los Lander habian venido reclamando desde hace decadas una reforma de las competencias concurrentes y marco. Tras algunas reformas constitucionales que no lograron cambiar la situacion de partida, y que obligaron finalmente al TCF a poner por si mismo limites a la expansividad del Bund, la reforma de 2006 introdujo una nueva tecnica competencial que permite a los Lander apartarse de la normativa previa del Bund en una serie de ambitos, y dictar en consecuencia una normativa propia que diverja de la de aquel. La puesta en practica de esta nueva tecnica en los ultimos anos permite verificar si ha funcionado de modo efectivo, si los temores que se suscitaron al principio se han cumplido o no y si, por tanto, resulta una tecnica util tanto para el caso aleman como para otros Estados donde se de una problematica similar en el ambito de la comparticion de competencias.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".