The possibility of using cybersex evidence in divorce proceedings in the context of proving fault for marriage breakdown from a comparative legal perspective
Bibliographic record
Abstract
Objectives The purpose of the study is to comprehensively examine the interpretation of cybersex in the context of marital guilt, while assessing the implications and challenges of bringing such evidence to court. The article aims to navigate the interpretation and legal recognition of cybersex as grounds for divorce. Material and methods The study used methods used in legal science: 1) the dogmatic method, referring to the establishment of current legal regulations governing the rules of electronic evidence, including cybersex evidence, as well as the way they are used in divorce processes and their impact on the permanent and complete breakdown of marital relations; it has a dominant character in the study due to the fact that the authors focus on the analysis of current legal regulations, as well as their practical use and application in other countries (e.g., the USA and Canada). 2) The analytical method was applied with reference to the current state of knowledge in the subject area in the body of legal science. 3) The comparative legal method is of complementary importance and relates to the analysis of legal and organizational solutions to the use of so-called illegal evidence, as well as the difficulties of conducting evidence and regulations in other countries. 4) The historical method is related to the evolution of the development of the rules of evidence in civil litigation in view of the development and spread of the use of modern technological solutions in justice. Results The potential use of cybersex evidence in divorce proceedings in Civil Procedure, while complex, provides an opportunity for legal growth. Conclusions Incorporating cybersex evidence in divorce proceedings brings a set of challenges, especially related to the violation of privacy rights, data protection, and the potential for cybercrime.
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 | 0.024 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".