The impact of well‐groomed appearance on children's epistemic trust decision
Bibliographic record
Abstract
This study investigates whether children's trust in information sources is influenced by the groomed or ungroomed appearance of an individual and whether age affects this decision-making process. A total of 662 children aged 4-10 from kindergarten, second grade and fourth grade participated. Children viewed photos of identical twins labelled as groomed or ungroomed, then watched videos where these individuals named unfamiliar shapes. Results showed that children across all age groups significantly preferred the groomed individual. Analysis of their explanations revealed that kindergarteners relied more on appearance-based justifications compared with older children. From second grade onward, children increasingly shifted towards accuracy- and skill-based explanations, even without direct evidence of competence. This developmental trend suggests that as children's language and reasoning abilities improve, they begin to provide more epistemic justifications rather than relying on superficial cues. Overall, the findings indicate that appearance strongly affects children's epistemic trust decisions throughout early and middle childhood. The study highlights the importance of educational practices that help children critically evaluate information sources based on reliability and competence rather than external appearance.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".