Marco Jurídico e Institucional para el Desarrollo de Políticas Públicas sobre la Primera Infancia en el Perú (Legal and Institutional Framework for the Implementation of Early Childhood Policies in Peru)
Bibliographic record
Abstract
Spanish Abstract: El objeto del presente trabajo es desarrollar el marco juridico e institucional del Peru con respecto a las politicas de primera infancia. Para este fin, en la primera parte se hara una contextualizacion sobre el contexto economico del pais en los ultimos anos, el cual ha contribuido para el desarrollo de politicas y programas sociales dirigidos a la primera infancia. En la segunda parte se estudiara el marco juridico interno y su relacion con los tratados internacionales de derechos humanos para la proteccion de la infancia y adolescencia. En la tercera parte del ensayo se hara un analisis de la institucionalidad y finalmente se hara una breve descripcion de los principales programas sociales en torno a la primera infancia.English Abstract: The present essay analyzes the legal and institutional framework of early childhood policies in Peru. The first part explains how recent economic development has fostered social policies, prioritizing early childhood. The second part analyzes how international human rights standards have contributed to the design of social policies targeting children and adolescents. The third part studies the impact and challenges of current early childhood social programs in Peru.
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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 | 0.005 | 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 | 0.006 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".