EXPLORANDO A PARCERIA PÚBLICO-PRIVADA EM DEFESA CIVIL: UMA INICIAÇÃO À PESQUISA ATRAVÉS DO PROGRAMA DE EDUCAÇÃO TUTORIAL
Bibliographic record
Abstract
Resumo: Este artigo destaca a importância de entender as Parcerias Público-Privadas para uma boa gestão da defesa civil no país, por meio da experiência no desenvolvimento de uma Iniciação à Pesquisa do Programa de Educação Tutorial da Engenharia Civil da Universidade Federal de Juiz de Fora.Com isso, foi desenvolvido um material didático da disciplina de Parcerias Público-Privadas (PPPs) para o Curso de Especialização Lato Sensu "Gestão Pública em Proteção e Defesa Civil" da UFJF, criado em 2018 em cooperação com o CBMMG.Esta disciplina busca correlacionar as PPPs com situações de desastres e mostrar como elas podem ser eficazes nas fases de Proteção e Defesa Civil.Para embasar o material, foram utilizados materiais internacionais que continham definições e experiências práticas de países que utilizam esta temática em Proteção e Defesa Civil.
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 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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".