Políticas públicas para a primeira infância: questões conceituais experiências e o papel dos Tribunais de Contas
Bibliographic record
Abstract
Early childhood represents a crucial phase of human development, characterized by intense brain plasticity and the formation of fundamental socio-emotional skills. Investments in this stage have demonstrated significant returns in several areas, including education, health, and economics, as evidenced by studies from the Organisation for Economic Co-operation and Development (OECD), Harvard University’s Center on the Developing Child, and international organizations such as the World Bank and the United Nations Children’s Fund (UNICEF). This paper analyzes the strategic importance of public policies aimed at early childhood, highlighting successful international experiences, such as Chile's Chile Crece Contigo program and Canadian initiatives, as well as national policies including Brazil’s Marco Legal da Primeira Infância (Early Childhood Legal Framework) and the Programa Criança Feliz (Happy Child Program). Also noteworthy are the recent initiatives of the Brazilian Audit Courts, which have launched early childhood pacts across multiple states to strengthen governance and enhance the effectiveness of public policies for children up to six years of age. This work proposes a critical examination of the need for intersectoral and sustainable actions, prioritizing equity and social participation, to achieve integrated child development in Brazil.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".