Legal Harmonization Through Interfederal Cooperation: A Comparison of the Interfederal Harmonization of Law Through Uniform Law Conferences and Executive Intergovernmental Conferences
Bibliographic record
Abstract
Abstract Modern federations are faced with the challenge of cross-state as well as cross-nation economic activities and with the ever-increasing mobility of society. This has not only promoted international law, but has also created the need for harmonized laws throughout federations within the competence areas of the states. Diverse laws within federal systems may increase transaction costs, cause delays, and lead to jurisdictional conflicts for nationwide or cross-state transactions. In order to preserve federalism, and therefore prevent an ever-advancing process of centralization, interfederal legal harmonization promoted by the states themselves is crucial. There are two distinct methods of legal harmonization of state laws: (1) harmonization by “Uniform Law Conferences,” which are in principle run by lawyers and thus independent, to a certain extent, from the influence of policy makers; and (2) harmonization by executive intergovernmental conferences. These two distinct models of interfederal legal harmonization will be analyzed and evaluated with regard to efficiency, compatibility with democratic principles, transparency, and accountability in a comparative legal study of the harmonization processes. This Article will scrutinize the federal systems of the United States and Canada, on the one hand, as well as those of Germany and Austria, on the other hand. The study will reveal that the efficiency of interfederal legal harmonization increases with the level of intergovernmental integration through the participation of government officials and their staff.
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 | 0.025 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".