Ethical conflicts around the procedure preimplantation genetic diagnosisand their overcoming by legal remedies based on foreign experience
Bibliographic record
Abstract
Objectives. The purpose of this study is to study the essence of ethical conflicts arising over the use of preimplantation genetic diagnosis (PGD) and to identify ways to overcome them by legal means, taking into account existing foreign experience. Materials. The legal acts and doctrinal sources of Australia, Great Britain, Canada, China, New Zealand, USA are investigated. The methods used are: general philosophical, general scientific, private scientific, special (structural-legal, comparative-legal, formal-legal). Results. Ways to resolve ethical conflicts around the PGD procedure that are relevant for use in Russian conditions are proposed. Conclusions. It was established that the resolution of ethical conflicts around the procedure should be based on state legal regulation of requirements related to informing patients about the content of the services provided and the consequences of the procedure, methods and procedures for the independent interpretation of the results. In addition to the official fixing of the list of genetic diseases, for the presence of markers which are allowed to conduct research, the legislation on the protection of the health of citizens must establish a procedure for authorizing PGD in exceptional cases, as well as factors and circumstances that must be taken into account and evaluated when an appropriate decision is made (including the features of a family history, an assessment of the degree of impaired function of the organism, the state of individual organs and their systems during development of the corresponding disease, etc.). Regulatory requirements can be supplemented and developed in the content of professional manuals
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 | 0.049 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| 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".