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Record W4405698603 · doi:10.24144/2788-6018.2024.06.52

On digital transformation of justice and prospects for the economic sector

2024· article· en· W4405698603 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnalytical and Comparative Jurisprudence · 2024
Typearticle
Languageen
FieldMedicine
TopicLegal, Health, Environmental and COVID-19 Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsDigitizationEconomic JusticeRestructuringDigital transformationPolitical scienceBusinessLawComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

The article focuses on analyzing the impact of digital transformation and technology on the judicial system. It highlights a terminological foundation that includes concepts such as digitization, digitalization, and digital transformation, which cover the transition of information into digital formats, the use of new tools for optimizing judicial processes, and comprehensive changes within the justice system. It establishes that digitalization involves the integration of technology at the level of automating judicial services, such as electronic document submission and electronic court hearings, whereas digital transformation encompasses the restructuring of justice itself. The importance of digital transformation is emphasized as a comprehensive reorganization of the entire judicial system through the adoption of advanced technology, laying the groundwork for electronic justice and enhancing access to justice. The conclusion drawn is that the development of the judiciary in Ukraine can proceed not only through the digitalization of judicial processes but also through the creation of new models for judicial processes, including the use of online courts. The online court model aims at an innovative transformation of the judicial environment, where digital technologies serve not merely as tools for automation but as drivers of a paradigm shift in delivering judicial services and resolving disputes. The article analyzes international experience in this area, specifically the operation of online courts in countries such as the United Kingdom and Canada for handling simple cases, reducing the burden on the judicial system, and simplifying procedures for citizens. The appropriateness of using online courts for resolving minor disputes and straightforward economic cases is substantiated. The role of artificial intelligence is considered separately, providing new opportunities to support judges in routine tasks, while also raising ethical and security risks, such as algorithmic bias and privacy threats. The argument is made that for the successful implementation of digital innovations in the justice system, it is necessary to develop infrastructure, establish standards for the ethical use of artificial intelligence, and ensure high levels of cybersecurity to protect the confidentiality of judicial information.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.342
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it