Bibliographic record
Abstract
Legal systems are defined as "framework of rules, procedures, and institutions that a community uses to interpret and enforce their laws".Even though there are many types of legal systems, such as Romano-Germanic and Anglo-Saxon legal systems, customary law, religious law, and hybrid or mixed systems, two of them have had even more impact and influence in development of legal systems of today.Romano-Germanic and Anglo-Saxon legal systems, or in other words continental and common law, can be considered two main types of legal systems.These legal systems have been formed and developed throughout history and have been adopted by many countries as legal systems.Romano-Germanic law is adopted as the legal system of Germany, France, Italy, Japan, Azerbaijan, meanwhile Anglo-Saxon system is adopted in countries such as United Kingdom, United States of America, Canada, New Zealand and so on.Each of these legal systems have a lot of distinguishing characteristics, mostly observed in elements such as historical development, sources of the law, court proceedings, existence of precedent, legal education and so on.Even though both systems are quite distinct due to fundamental differences between their rules, procedures and institutions, they have also affected the development of each other, and can present some similarities as well.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".