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Enregistrement W626122697

Who's afraid of the fire alarm or going to preschool? A comparative study of early childhood fears and caregivers' responses to fear in Australia and Canada

2004· article· en· W626122697 sur OpenAlexaboutno aff
Reesa Sorin

Notice bibliographique

RevueResearchOnline at James Cook University (James Cook University) · 2004
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEarly Childhood Education and Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychologySurpriseFeelingHappinessAction (physics)CognitionSocial psychologyDevelopmental psychologyCognitive psychology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

As an emotion, fear can have both positive and negative effects. It can alert people to potential danger and motivate them to choose a path of action or reaction. It can also bond people together in collaboratively seeking protection from the feared object. However, fear can also impede its victims' cognitive processes, behaviour and social interactions. Memory, problem-solving ability, perception and choices for action can be obstructed due to fear, and self-esteem, emotion regulation and sociability hindered by fear. Fear and other emotions have both a biological and a cultural component. As many as ten emotions are considered to be innate; many sharing universal understanding and display rules. For example, happiness is displayed with a smile; surprise with eyes open and eyebrows raised. Other emotions tend to have culturally specific ways of understanding and display. Each culture passes these ways on to children from birth, through everyday interactions with the young child. Yet as they grow, some children are considered to be "emotionally literate" - to be aware of and understand emotions and emotion expression in themselves and in others - and other seem to lag behind, to have problems understanding and expressing their feelings and empathising with others' feelings. Emotional literacy, then, seems to be a learned skill and one that cannot be left to chance acquisition. Educators need to understand emotions and emotion displays and how best to guide children to becoming emotionally literate. In this multicultural world, multiplicity of emotion understanding and display needs to be considered not only to aid in this understanding but also to offer educators a variety of strategies to implement effective emotion education programs with their students. The study described here focused on preschool children and the emotion of fear; kinds of fears, how children display these fears and how caregivers respond to fear. Utilising preschool venues in Australia and Canada, caregivers (adults working in early childhood settings) were asked what their preschool-aged children were afraid of, how they display their fear, and how, as caregivers, they responded to the fear. While many responses were similar in both countries in these areas, incidences of reporting varied widely in some fears, fear displays and responses to fear. For example, 55% of Canadian caregivers reported young children to have a fear of loud noises, whereas only 11% of Australian caregivers reported this fear. Fifty-nine percent of Australian caregivers reported that their students had a fear of preschool, while no Canadian caregiver specifically mentioned this fear. Twice as many Australian caregivers reported that fearful children withdraw and hide. In responding to fear, more Canadian caregivers said that they planned activities to address fears before they occurred. Caregivers' responses to fear have been compiled as a table to offer Early Childhood Educators a variety of ways to respond to fear and develop emotional literacy in their students.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,343
Score d'incertitude au seuil0,820

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,033
Tête enseignante GPT0,297
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2004
Routes d'admission1
Résumé présentoui

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