The Child and Parent Emotion Study
Bibliographic record
Abstract
Introduction: Parents shape child emotional competence and mental health via their beliefs about children’s emotions, by modelling emotion regulation skills, emotion-related parenting, and the emotional climate of the family. Much of the research to date has been based on small samples with mothers of primary school-aged children. The Child and Parent Emotion Study (CAPES) aims to examine longitudinal associations between parent emotion socialisation, child emotion regulation and socioemotional adjustment at four time points. CAPES will investigate the moderating role of parent gender, child temperament and gender, and family background. Methods: CAPES is an age-stratified longitudinal cohort study. CAPES recruited 1,992 parents of children aged 0–9 years and 264 prospective parents (i.e, pregnant parents of their first child) in 2018–2019. Parents are residents of six English-speaking countries (i.e., Australia, New Zealand, US, Canada, UK, Ireland). Participants completed online self-report surveys that included several measures of parent outcomes, including parent emotion socialisation (e.g., parents’ beliefs about children’s emotions, parents’ stress), and age-sensitive measures of child outcomes (e.g., child emotion regulation, child internalising problems). Between 2018 and 2021, three timepoints of data have been collected, in intervals of approximately 12 months. Data collection for time 4 will be completed by late 2022. This dataset includes three timepoints of data, for participants who consented to share their data (N=2,069).
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".