Interactions between parental and personal socioeconomic resources and self-rated health: Adjudicating between the resource substitution and resource multiplication theories

Further resource multiplication at more advanced ages? Interactions between education, parental socioeconomic status, and age in their impacts upon health

“…Veenstra and Vanzella-Yang (2022) highlighted how socioeconomic resources might especially benefit the health of those from less advantaged backgrounds since they compensate for a past dearth of health-protective resources. Accordingly, education might especially benefit those whose earlier circumstances disadvantaged their sense of personal control and mastery, and their opportunities for financial success (Veenstra & Vanzella-Yang, 2022). Scholarship in this vein began with Ross and Mirowsky (1989), who suggested that sentiments of control over one's circumstances and perceptions of support from others are mutually substitutive in reducing depression.…”

“…As a consequence, the effect of having a specific resource is greater for those who have fewer alternative resources” (Ross & Mirowsky, 2006, p. 1402). Veenstra and Vanzella‐Yang (2022) highlighted how socioeconomic resources might especially benefit the health of those from less advantaged backgrounds since they compensate for a past dearth of health‐protective resources. Accordingly, education might especially benefit those whose earlier circumstances disadvantaged their sense of personal control and mastery, and their opportunities for financial success (Veenstra & Vanzella‐Yang, 2022).…”

“…They might further live more healthily, a proclivity accentuated by education. Furthermore, early life disadvantages may have scarring effects on future health that cannot be counterbalanced by education (Veenstra & Vanzella‐Yang, 2022). Moreover, the middle‐class biases of Western educational establishments might result in students from more advantaged backgrounds acquiring greater benefits from their education (Andersson, 2016).…”

Inequality of opportunity in a land of equal opportunities: The impact of parents’ health and wealth on their offspring’s quality of life in Norway

“…Second, we investigate the extent to which two different types of circumstances that both lie outside of individuals' own control contribute to explaining inequalities in adult health. By considering childhood financial conditions, we contribute to a growing literature on the importance of childhood circumstances in determining adult health [14][15][16][17], particularly the financial environment in which children grow up [18][19][20]. Aside from the financial conditions during childhood, parents are likely to contribute to their offspring's adult health by passing on some of their health stock (e.g.…”

A manifesto for computational sociology: The Canadian perspective

“…Computational methods include a gamut of different techniques including machine learning (e.g., deep learning, statistical learning, reinforcement learning), social network analysis, text and data mining (e.g., sentiment analysis, topic modelling, named‐entity recognition), agent‐based modelling, more flexible regression/estimation models (e.g., regression shrinkage and selection, Bayesian statistics, spatial regression models), advances in survey methods (e.g., survey experiments, optimum design, respondent‐driven sampling), and so on. Some sociologists in Canada have contributed directly to the development of particular methods (Alexander & Alkema, 2021; Andersen, 2008; Bignami‐Van Assche et al., forthcoming; Fosse & Winship, 2019; Fox, 2015; Fox & Andersen, 2006; Fu et al., 2020, 2021; Hayduk, 1996; Li et al., forthcoming; Miles, 2016; Nelson, 2020; Stecklov et al., 2018; Wellman et al., 2003, 2020), but more often sociologists have embraced and adapted methods developed by computer scientists, statisticians, and econometricians (Abul‐Fottouh et al., 2020; Boase, 2016; Das, 2022; Gallupe et al., 2019; Gruzd & Mai, 2020; Gu et al., 2021; Hogan & Berry, 2011; Howe et al., forthcoming; Kudla & Parnaby, 2018; Letarte et al., 2021; Li & Luo, 2020; McLevey, 2022; McMahan & McFarland, 2021; Quan‐Haase et al., 2021; Richardson et al., 2021; Roth et al., forthcoming; Shor & Miltsov, 2020; Shor et al., 2013; Silver & Silva, 2021; Smith, 2020; Sytsma et al., 2021; Veenstra & Vanzella‐Yang, 2022; Yuan et al., 2022).…”