Preschoolers’ emotion knowledge: The role of cognitive flexibility and family interactions in financially vulnerable contexts.
Bibliographic record
Abstract
A growing number of studies recognize the importance of emotion knowledge for later child social and academic adaptation, but most studies have not considered the various components of emotion knowledge (i.e., receptive, expressive, stereotypical, and nonstereotypical emotion konwledge). This study was to better understand the role of both family interactions and cognitive flexibility on the different components of emotion knowledge in preschoolers in the context of financial insecurity. Family interactions of 85 families with children aged 3-5 were filmed during a home visit. During the same visit, emotion knowledge was measured using a puppet task, and cognitive flexibility was assessed using a standardized task. Results showed that the quality of family interactions significantly contributed to all components of emotion knowledge. Child cognitive flexibility only significantly contributed to the expressive and nonstereotyped components of emotion knowledge. No significant associations were found between household income and the different components of emotion knowledge. These results highlight the importance of considering the family environment and the interactions between all family members, as well as cognitive flexibility on preschoolers' emotion knowledge skills in the context of financial insecurity. These results offer new avenues for interventions aimed at supporting the development of these skills among low-income families. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".