An Examination of Children's Selective Social Learning Based on Expertise Cues
Notice bibliographique
Résumé
At a young age, children develop the ability to make selective social learning decisions, wherein they decide from whom they trust to learn new information. Substantial literature has examined children's selective social learning decisions based on epistemic cues (e.g., knowledgeability) and non-epistemic cues (e.g., perceived benevolence). When these cues are pitted against each other, a shift emerges wherein children aged 6-8 tend to rely on epistemic cues whereas children aged 4-6 prioritize non-epistemic cues. As children encounter experts such as doctors from an early age, it is important to determine how they understand and recognize expertise, an epistemic cue, and the extent to which expertise guides their selective social learning decisions. This research aimed to address these questions. Study 1 (Experiments 1-3) showed that children aged 4-5 were able to recognize expertise when it was indicated by an explicit label and professional attire, and that they could determine relative expertise when a clear contrast was presented (e.g., one informant works in a given field whereas the other has no exposure to that field). These cues subsequently informed their selective social learning decisions. In contrast, they struggled to discern expertise when it was indicated using technical language, and when the degrees of expertise were increasingly nuanced (i.e., contrasting informants that have exposure to a field as a hobby and for work). Children aged 7-8 were able to infer expertise in medicine from technical language and make selective learning decisions accordingly. Study 2 (Experiments 4-5) examined the robustness of children’s preferences to learn from experts, and pitted expertise cues against group membership as indicated by nationality and the minimal group paradigm. Results revealed that 7- to 8-year-olds, but not 4- to 5-year-olds, prioritized expertise cues over shared group membership (i.e., ingroup information) in their selective learning decisions. These results provide novel insights into the developmental changes in children’s conceptions of expertise and how they prioritize different expertise cues to guide their social learning. The implications of this can be seen in children’s susceptibility to misinformation from others if their selective trust decisions are based on cues that are not reliable or valid.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».