About Prospects of Participation of Russia in the Convention on the International order of Alimony Recovering of 2007
Bibliographic record
Abstract
The article analyzes the prospects for the possible participation of the Russian Federation in the Convention on the International order of alimony recovering and Other Forms of Family Maintenance in 2007. Identified factors contributing to the ratification of the Convention, as well as circumstances that create certain difficulties. Among the first are: universality of the Convention; compliance of many provisions of the Convention with the norms of family, civil procedural legislation and legislation on enforcement proceedings of the Russian Federation; the existence of a real mechanism that facilitates the effective alimony recovering abroad, and thereby satisfies the vital needs of needy family members. Among the factors of a “restraining nature”, some differences were noted in the provisions of the Convention and Russian legislation regarding entities entitled to alimony. In addition, Russia's accession to the Convention may require a review of national legislation on the provision of free legal aid. However, the system of reservations and declarations of amendment or cancellation of the rules provided for in the Convention allows to mitigate the constraints. As a result, it was concluded that for the Russian Federation, ratification of this Convention will have a greater effect and will solve the problem of receiving alimony from abroad.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".