White subjects: domestic science in the colonies and other places
Notice bibliographique
Résumé
Classism is the most obvious ‘ism’ to plague the domestic science story. The domestic science movement was undeniably, to some extent and in certain quarters, about putting working- class women in their place. Imposing middle- class values on ‘an unruly, unkempt and ultimately unfit working class’ was a poorly thought out route to solving many problems of industrialisation and urbanisation: crime, drinking, poor nutrition, high infant mortality. But classism and sexism are linked to other ‘isms’. This chapter focuses on racism, imperialism and colonialism as creeds that have done their part in afflicting the domestic science movement. The chapter is also about the wide reach of the Euro- American ideology and practice of home science: how it was exported to other places, including Japan, Canada, New Zealand and other territories of what used to be the British Empire. The story in this chapter features a multi- faceted cast of characters: two Japanese women advocates of household science, Sumi Miyakawa and Hideko Inoue; the British household scientist Alice Ravenhill (again); a wealthy Canadian called Lillian Massey Treble; two clever Canadian food chemists, Annie Laird and Clara Benson; three British women who developed household science in New Zealand, Winifred Boys- Smith, Helen Rawson and Margaret Dyer; and two very different male characters, John Studholme, a philanthropic landowner, who thought women needed to be educated for their work at home; and an enthusiastically reformist Indian royal, the Maharaja of Gaekwad, who wanted a scientific woman to modernise his palaces. Household science was nothing if not versatile in adjusting to different cultural contexts. However what was versatile could also be inflexible. The same Euro- American- derived values and practices didn't necessary agree with the habits of the cultures into which attempts were made to insert them. Why whiteness? In 2001 a Canadian home economics teacher, Mary Leah de Zwart, was asked a testing question by one of her students: ‘White flour, white sugar, white sauce, white table manners, why is it that everything we do is white ?’ The student might have added to her (it was almost certainly a her) list of white subjects the overwhelming emphasis on whiteness and how to achieve it that has habitually haunted the laundry sections of domestic science manuals and classes, and that more than linger in our consumer industry today. Why should everything be white? What's wrong with off- white, grey, brown or even black?
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 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».