Family Education Strategies in Supporting Early Childhood Development
Bibliographic record
Abstract
High-quality research on family education has increased significantly over the past decade, with 1,040 documents recorded in Scopus. This study aims to analyze research trends, identify key terms, highlight the most active journals, examine author collaboration and citation networks, determine author affiliations and funding sources, map contributions by country, and explore related scientific fields. Data were collected from Scopus.com and analyzed using VOSViewer. The results show a positive trend with steady annual growth. Family education is closely linked to early childhood education, parenting, early intervention, and overall quality of life. Frontiers in Psychology is the most active journal in its field. Landier, W., is the most influential author. The top contributing institutions include Harvard Medical School and the University of Washington. Primary funding sources are the National Institutes of Health and the U.S. Department of Health and Human Services. The United States leads in publication output, followed by China and Canada. Most articles are from the fields of medicine and social sciences. These findings highlight family education as a growing multidisciplinary field with wide-ranging impacts. The results guide policymakers in creating targeted parental training on digital literacy and emotional regulation, while education practitioners can apply family-centered interventions to enhance parental involvement in early learning.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".