National Council of Justice and the one test: democratizing the Brazilian Judiciary
Bibliographic record
Abstract
This article evaluates the potential impacts of the reforms introduced by the National Council of Justice on the composition of the judiciary. By examining the proposal for a unified judicial exam, it explores how this reform could alter the composition of Brazil's judicial elites by addressing two major obstacles to judicial democratization: the decentralization of justice administration and the methods of judge recruitment. To assess the centralization sought by the CNJ in contrast to the decentralization advocated by the courts of justice, the article primarily draws on Luciano Athayde’s research on the judiciary as an archipelago. The second part of the article examines the two models used in Brazil for recruiting judges: public examinations and appointments. In discussing the public examination process, the article references the work of Daniela Passos. The debate over the exam is divided into two parts. The first part examines the content of the exam and the skills it prioritizes for the judiciary. It also proposes suggestions for the content of a unified exam. The second part analyzes the socioeconomic profile of judges recruited through public examinations. This is followed by an investigation into the appointmentsystem, also examining the socioeconomic profile of appointed judges, in order to assess the effectiveness of appointments as a tool for democratizing the judiciary.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".