Bibliographic record
Abstract
This paper aims to describe the crisis affecting civil execution in Brazil, identify its main obstacles, assess what measures have already been adopted to address these issues, and, most importantly, analyze what can be done to ensure future effectiveness and efficiency in the execution phase, implementing the mandates in the Brazilian Constitution (Article 37, caput, CF) and the 2015 Code of Civil Procedure (Articles 4 and 8, CPC/15).Since the first edition of "Justice in Numbers" by the National Council of Justice (CNJ) in 2004, it has been noted that the major bottleneck in the judiciary is in the execution phase.This delay in implementing rights is a primary factor contributing to the judiciary's loss of prestige.It also affects the country's reliability in other areas, such as economic and political spheres.The research, therefore, from a legal-sociological perspective, sought to understand the execution crisis phenomenon within the broader social environment, identifying the main economic, cultural, and legal obstacles that prevent the execution phase from fulfilling its primary duty, which is to satisfy the creditor's right (Article 797, CPC/15) without unduly burdening the debtor (Article 805, CPC/15).Subsequently, it was found that among the solutions proposed for the civil execution crisis, three major approaches are consistently identified: pre-procedural measures; procedural measures, including legislative and jurisprudential improvements; and managerial measures.Thus, this work traced the historical trajectory of the 20th century and the early 21st century, outlining the main pre-procedural, procedural, and managerial measures adopted to improve satisfaction in civil execution.Finally, the study delved into the 6th wave of access to justice, characterized by the use of new technologies, and suggested that their intensive use across the three fronts -pre-procedural, procedural, and managerial measures -could be a genuine solution to permanently attenuate the civil execution crisis in Brazil.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.015 |
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; both teacher heads agree on what is shown here.
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".