Preschoolers’ mapping of in-group social groups versus out-group social groups to morphed faces
Notice bibliographique
Résumé
Past research has revealed children as young as six years old and adults show tendencies of dehumanization. For example, by age 5 children perceive ambiguous doll-human face morphs as being “less human” if they thought the faces belonged to an out-group (McLoughlin et al., 2018). However, there remains a gap in understanding whether and when this phenomenon starts earlier in development. The current study aimed to explore whether children as young as three years old display dehumanization tendencies towards out-group members, for which group membership is defined in different ways. Specifically, we will examine preschoolers' attribution of humanness to faces described as their in-group vs out-group. We explore this question in 3-to-5 ½-year-old children as past work suggests that the youngest age this phenomenon has been observed is in 6-year-olds (McLoughlin et al., 2018), suggesting that children may already attribute fewer human qualities to people perceived as their out-group in contrast to their in-group across different types of group membership (i.e. minimal group, language, preference, geographical location). Therefore, if the tendency to dehumanize is already present at that young age, we could observe a tendency to dehumanize developing earlier in development. To test this possibility, English monolingual 3- to 5-year-olds will hear descriptions that reflect four different types of group memberships (same/different minimal group, language identity, geographical location, food preference). For each of the four blocks (i.e. each block belongs to one of the four group memberships), on alternating trials, the description will be of an in-group member (e.g. “This person is also from Canada”) or an out-group member (e.g. “This person is from a far away place called Daxo”). Following each description, children will see a face-morph pairing that differ in their degree of humanness. In low contrast trials, one face will be only slightly more human (~5 to 10% difference in morph, as defined by FantaMorph software, Version 5; Abrosoft Co), whereas in high contrast trials, one face will be much more human (~15 to 20% difference in morph). Children will be asked to pick which of the two face-morphs best fit the description they just heard. As there has been no previous work, to our knowledge, that examines dehumanization in children in this age group; we do not have strong predictions for what might occur. However, we generally predict that children will pick the morph faces that are less human-like after hearing a description of an out-group member than after hearing a description of an in-group member.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».