Digitization of Law: Some Problematic Aspects
Bibliographic record
Abstract
This article reveals the important practical importance of academic cooperation between legal doctrine and achievements of technical laboratories in terms of defining “points of growth” in questions of digitalization of law and development of legal tools aimed at regulating the technogenic factor on the one hand and legal support of “game-changing” results in a in the conditions of digital economy on the other hand. The important role of the transformation of social regulators, designed to regulate the “infrastructural” and “institutional” incorporation of “digital” technologies into the existing legal system, is noted. The current place of the Russian Federation on readiness for the digital economy is subject to, among other things, insufficient theoretical study as a result of the regulatory framework, which often does not act as a platform for growth, but rather contains many gaps - which have to be overcome at the expense of law enforcement practice. The article notes that the trend of “digitalization” of Russian law is closely linked to the need to maintain the ecosystem of the digital economy and to identify “growth points” and enforce their urgent character based on the state’s resource base, defines a positive agenda for “digitalization” of Russian law and raises a number of questions for the Russian science. It is concluded that one of the topical issues in the framework of the “digitalization” of Russian law is legal robotics, which is perceived as the automation of workflows, the existence of interrelated algorithms of actions aimed at generating a predictable result based on some initial simulated and prescribed situation and maximum robotization of legal processes. Using the example of the Kazan Federal University, which proclaimed the promotion of innovative development of the focus areas of the Russian Federation as one of its missions, the achievements obtained as a result of the interaction of legal doctrine and technical laboratories are revealed.
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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.009 | 0.045 |
| Scholarly communication | 0.015 | 0.026 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".