Domestic Foodwork in Value and Practice: A Study of Food, Inequality and Health in Family Life
Notice bibliographique
Résumé
This dissertation explores home-cooked family meals – the ideals and expectations around them, as well as how they are navigated by parents in diverse social positions. This exploration assesses how discourses and practices surrounding family foodwork reflect and shape inequalities in a variety of realms including gendered labour, economic disparities, health outcomes and consumer politics. It utilizes diverse methods including a discourse and content analysis of North American news media, as well as qualitative interviews, cooking observations and food recall conversations with parents in the Greater Toronto Area who are primary cooks in their families. These varied methods facilitate investigation into how home cooking is publicly presented, automatically understood, and emotionally experienced by parents from diverse backgrounds. The dissertation explores these ends in three analytically distinct chapters, offering three key insights. First, the media analysis reveals that public discourse promotes a complex allocation of responsibility for family meals that recognizes multiple structural conditions constraining meals (such as unhealthy food environments and inflated normative standards), yet assigns responsibility for resolving them to individuals (i.e. parents should work harder to combat these constraints and cook more at home). These findings apply to family meals but can also be extended to consider responsibility for social problems within neoliberalism more broadly. Second, interview analysis identifies the ubiquity of a cultural schema of “cooking by our mother’s side”: an automatic, semi-conscious understanding of learning to cook that privileges culinary knowledge acquired during childhood through the social reproductive work of mothers. Analysis of this schema reveals its role in reproducing gendered inequalities and obscuring diversity in food learning, especially by overemphasizing the importance of childhood and masking learning later in life. Third, I qualitatively analyze how socio-economic disadvantage (alongside its intersections with gender and race/ethnicity) negatively impacts the emotional experience of foodwork but does not necessarily predict cooking pleasure. In identifying and exploring five conditions of cooking pleasure, I examine how certain conditions can operate relatively independently from class and facilitate cooking enjoyment for low-income groups. Collectively, the dissertation advances scholarly understanding of the ideals, meanings and emotions encompassing family foodwork, their embeddedness with social inequalities, as well as opportunities for resistance and social change.
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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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».