Bibliographic record
Abstract
We conducted research from October 2011 up to November 2016 on the evolution of the family concept and its influence on the legal succession order in Romania. Our scope was to provide an in depth analysis of the complex social, historical, philosophical and religious factors that worked together in modern and post‐modern Romanian civil law history, in order to evaluate the answer given by the recently enacted civil code of 2011. The paper hereby can give an idea on the conclusions we drawn at the end of our work. It argues mainly if the new provisions are covering all the aspects drawn into practice by the family – in its traditional and recent presentations. We focus on the successive versions of the civil code’s Book dedicated to the Law of successions, part of them being authored by ourselves. We take into account the recent evolutions in the Family law and in the Law of successions of several European and non‐ European countries, with a special accent on France and the Canadian province of Quebec – who deeply influenced the former and the present Romanian civil codification. The research ends with a set of conclusions leading to de lege ferenda propositions, meant to improve the actual state of the new Romanian civil code on the emphasized subject. They are meant to satisfy the specific needs of the present day Romanian society and to keep in touch with the tendencies we drawn out of the experience of comparative law of successions.
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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 | 0.006 |
| 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 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| 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".