ENVIRONMENTAL INFRINGEMENTS DISPUTES SOLUTIONS IN BRAZIL AND CANADA
Bibliographic record
Abstract
The purpose of this paper is to verify some possibilities applicable in Brazil and Canada, with literature review from both countries, in which the peaceful settlement of disputes is used in the solution of environmental conflicts. The question that arises is whether the two countries apply this formula in order to make a proper justice and whether laws are in accordance with that purpose. In Brazil, Resolution n. 125 of the National Council of Justice and Joint Normative Instruction n. 2 (2020), allow the use of alternative solutions of controversies. Canada also allows the provinces the power to facilitate this practice in order to assist the Judiciary to establish justice more specialized. This research is based on Canadian experiences that are compatible with the Brazilian legal system, and that can offer examples of offense to the environment. In light of the research, the work provides a glimpse of the advantages of alternative means such as extrajudicial settlement of disputes, which were resolved as mere œtort in common law in Canada. In this study there are systemic reflections, with a focus on comparative law. The final considerations highlight how these mechanisms generated better solutions, increasing the efficiency of justice of countries involved.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".