Applicability of the parenting workshop in the Mineiro Judicial Power: A descriptive and spatial analysis
Bibliographic record
Abstract
In this article, we sought to analyze the applicability of the parenting workshop in the Judiciary of the State of Minas Gerais, through a quali-quantitative approach, considering its characteristics and spatialization. To complement the analysis, by means of a case study, together with the CEJUSC workshops, in the District of Viçosa-MG, a scan was carried out in the Center's database and the questionnaires applied to the participants, at the end of the workshops, by the exhibitors were analyzed. The sample consisted of 74 respondents, who participated in workshops held between 2018 and 2019. The data were processed and analyzed using the GNU PSPP software, resulting in tabular and graphical analyses. The data obtained in field research with the Districts of Minas Gerais were projected on a georeferencing map, through the free software QGis 3.2.1, aiming at a spatial analysis of the object of study. As a result, it was found that, although the parenting workshop was implemented in Brazil in 2014, its application in the Court of Justice of Minas Gerais is still limited. In addition, although, in the perception of the public involved, the workshops held in the District of Viçosa-MG proved to be effective in resolving family conflicts, strategies are needed to expand the scope of the instrument and more empirical studies on this topic are needed.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".