Associations between School Readiness and Student Wellbeing: A Six-Year Follow Up Study
Bibliographic record
Abstract
Abstract It is well established that children’s school readiness is associated with their later academic achievement, but less is known about whether school readiness is also associated with other measures of school success, such as students’ social and emotional wellbeing. While some previous research has shown a link between early social and emotional development and student wellbeing, results are mixed and the strength of these relationships vary depending on whether data is based on child, teachers or parents ratings and which specific student wellbeing outcomes are measured. The present study explored the association between teacher-rated school readiness (Mage = 5.6 years) across five developmental domains (physical, social, emotional, language and cognitive, and communication and general knowledge) and four aspects of student wellbeing (life satisfaction, optimism, sadness and worries) in Grade 6 (Mage = 11.9 years) in a sample of 3906 Australian children. After adjustment for background child and family-level factors, children’s early physical, social and emotional development were associated with all four wellbeing outcomes in Grade 6, but early language and cognitive skills and communication and general knowledge skills were only associated with internalising behaviours (sadness and worries). Mechanisms through which these different aspects of development might influence later wellbeing are discussed, as well as ways that schools and governments can support students’ social and emotional wellbeing.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".