Bibliographic record
Abstract
Introduction: the physical and technological transformations of the modern world are accelerating due to the theory of technological singularity. This phenomenon indicates that the time between fundamental technological discoveries is shortening. In the context of such a dynamic development of technology, the existing law does not always have time to adapt to new challenges, which pushes for the need to revise legal norms and introduce new concepts. The purpose of the work is to explore fundamental issues related to the impact of technological singularity on human rights as well as to propose a new concept – human cyber rights. Methods: the methods of theoretical analysis and comparative jurisprudence were used in the course of the study. The analysis of literary sources on the research topic was carried out, including the works of scientists and jurists dealing with philosophy of law, technology, and human rights. The methods of logical analysis and synthesis were also used to identify the connections between fundamental concepts and develop a new concept. As a result of the study, the main problems associated with the lag of law from technological progress have been identified. The concept of human cyber rights has been proposed, which includes the rights of an individual in the digital space. The need to adapt legal norms to new challenges, such as the rights of scanned persons and ensuring data security in the digital space, has been discussed. The study has confirmed the need to revise the legal norms in the light of technological singularity and proposed a new concept of human cyber rights as a way to adapt law to the challenges of digital transformation. Further research in this area can contribute to the development of more flexible and effective legal mechanisms to ensure the protection of human rights and freedoms in the era of the digital revolution.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".