THE BOLOGNA SYSTEM OF HIGHER EDUCATION AS THE BASIS OF THE EDUCATIONAL QUALIFICATION FOR ADMISSION TO THE LEGAL PROFESSION
Bibliographic record
Abstract
The relevance of the study is caused, on the one hand, by the unification of approaches to the content of higher legal education in the world (related to the Bologna process), and, on the other, by different approaches of states when using the results of training in the bachelor/master/doctoral student paradigm when admitted to the legal profession. The authors investigated the situation in the main “civilized” states on this issue, revealing a wide range of approaches to the requirements for having an appropriate level of higher legal education for candidates for the status of a lawyer: only master (Ukraine, France), law bachelor (UK, Australia, Canada, USA, Slovenia), not a bachelor of law with the condition of additional training (UK, Australia), not a bachelor of law with subsequent legal practice (state California). As a result, the following conclusions were made: 1. In countries with the Bologna system of higher education, there are no unified approaches to the level of education that a candidate for obtaining the status of a lawyer should receive. 2. No regularities were found to determine why in some states the choice was made in favor of the “master's degree”, and in others - the “bachelor's degree” requirements for candidates for the status of a lawyer.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".