Right to Life: Improvements in the Legislation of the Russian Federation Concerning Palliative Care
Bibliographic record
Abstract
This article raises the issues of organizing palliative care as one of the forms of implementing the right to life. The authors identify and describe the principles of palliative care. International law regulating palliative care is reviewed, along with a brief overview of the development of Russian law concerning palliative care and a list of patients who may be subject to palliative care. Special attention is given to the issue of decision-making by the patient's family. In connection with that, examples are cited for foreign models of communication between palliative care and decision science researchers, theorists, and clinicians, patients and their families for the purpose of exchanging information and studying the patients' health issues, discussing treatment options and making coordinated decisions during the life-limiting illness of patients. The results of this research are based on using the following methods: universal dialectical method of scientific cognition, as well as general scientific methods based on it (description, analysis, synthesis, induction, deduction, comparison, analogy, generalization) and specific scientific methods (comparative law method, systematic structural method and formal law method).
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".