Reporting guidelines for implementation research on nurturing care interventions designed to promote early childhood development
Bibliographic record
Abstract
Meta-analyses of interventions such as parenting, stimulation, and early childhood education have reported consistent medium-to-high effect sizes on early childhood development (ECD) and early learning outcomes. However, few effective interventions promoting ECD have achieved scale. In order to increase the access to effective or high-quality services, greater focus on implementation research of interventions promoting ECD is necessary. In this paper, we describe the development of reporting guidelines for implementation research of nurturing care interventions designed to promote ECD following an expert consensus-building process. The goal of these guidelines is to support a transparent and standard reporting of implementation evidence on nurturing care interventions designed to promote early childhood development.
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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 | 0.662 | 0.811 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.011 | 0.029 |
| Bibliometrics | 0.028 | 0.028 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.017 | 0.013 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".