Notice bibliographique
Résumé
During the first two thirds of the 20th century, electricity, running water, and a host of new consumer durables diffused into most American homes. These new household technologies revolutionized domestic life by freeing up time from basic housework. In this dissertation, I study the consequences of household technological change on families, focusing on fertility, child health, marriage, and female labour force participation. \n \nChapter 1 provides a short history of household modernization. I then present an econometric framework for evaluating the effects of household technological change, and discuss the main estimation challenges. To address these issues, I introduce an estimation strategy based on a newly-assembled dataset that captures the rollout of the U.S. power grid during the mid-20th century. \n \nIn chapter 2, I study the impact of household technological change on fertility and child health, exploiting substantial cross-county and cross-state variation in the timing of when households acquired new consumer durables. Modern household technologies led families to make a child quantity-quality tradeoff favouring quality: household modernization is associated with decreases in infant mortality and decreases in fertility. The declines in infant mortality were particularly large in states where households had relied heavily on coal for heating and cooking, where the potential to improve indoor air quality was greatest. Health improvements were also larger in states that had previously invested heavily in maternal education, suggesting that household modernization led parents to provide better infant care. Overall, household technological change can account for between 25% and 30% of the total decline in infant mortality between 1930 and 1960. \n \nIn chapter 3, I examine the relationship between household modernization, investment in children, and female employment. I present a conceptual framework in which household technological change has little immediate impact on female employment, but generates increased investment in daughters' human capital, ultimately causing a rise in employment for subsequent cohorts of women. I find empirical support for these predictions. Further, the results suggest that the diffusion of modern technology into the home during the first half of the 20th century can account for a significant fraction of the rise in female employment after 1950.
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 | 0,001 | 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 | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».