Bibliographic record
Abstract
This paper provides an overview of protection indicators developed for Colombia’s Intersectoral Commission for Comprehensive Early Childhood Care for the Early Childhood Comprehensive Care Strategy, “De Cero a Siempre”. De Cero a Siempre Strategy promotes the national public policy to strengthen the realization of rights for children aged 0–6 and is laudable in its holistic approach to supporting children’s rights in the early years. The paper provides a context on progress made in strengthening international norms and standards in child protection during early childhood and presents a summary of current frameworks for early years risk and protection indicator development, in particular the un Committee on the Rights of the Child General Comments No. 7 (Early Childhood) and No. 13 (Prevention of Violence). The paper presents a framework of risk and protection indicators, drawing on gcs Nos. 7 and 13, across the first five moments of the lifecycle, and four social environments of home, educational environment (ecd, kindergarten, and school), health environment and public space. The paper also suggests opportunities for community involvement in piloting these indicators. Finally the paper recommends a strategy for Colombian municipalities to incorporate indicators for protection in early childhood, and suggests five specific ways the data gathered from the indicators can be used to strengthen outcomes for children in the early years impacted by De Cero a Siempre policy and its programmes.
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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 | 0.023 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".