Global trends in cross-cultural endorsement of social mobility: Evidence from 167 countries.

Abstract

The American Dream-the perception that upward social mobility depends on effort-is a central cultural ethos in the United States. The belief in upward social mobility is not unique to Americans, and cultural groups across the world endorse it to varying degrees. The current study aims to examine cross-cultural trends in perceived mobility and to test possible mechanisms that may explain changes in perceived mobility. Using a dataset of over 1.4 million participants across 167 countries from 2005 to 2019, we comprehensively document cultural variations in perceived mobility. Citizens in Bhutan, Qatar, and Uzbekistan reported the highest levels of perceived mobility, and the United States ranked 107. We further examined the trajectories of perceived mobility across a 15-year timespan and found rapid declines in perceived mobility in countries experiencing sociopolitical crises (e.g., in Syria and Hong Kong). Multilevel analyses revealed high-income individuals are 32% (95% confidence interval, CI [24%, 39%]) more likely to perceive mobility than low-income individuals, and the level of disparity did not decrease over time. Preregistered time-series analyses showed education privatization and economic condition Granger-cause perceived mobility, but these temporal associations showed heterogeneity across countries. Overall, we performed the world's largest global monitor of perceived mobility and discussed how the cultural value of perceived mobility unfolds in social, economic, and political contexts.

Climbing the Invisible Ladder: Attenuating Belief in Free Will Reduces Subjective Perceptions of Social Mobility

“…Exposure to social mobility information (Kraus & Tan, 2015), political ideology differences (Chambers et al, 2015), and optimism about equality (Kraus et al, 2017) contribute to different perceptions of social mobility. A recent global investigation about upward social mobility found that income inequality, education privatization, and historical events contribute to changes in perceived mobility to various degrees (Chan et al, 2021). Thus, perceptions of social mobility fluctuate depending on social context.…”

“…We propose that free will beliefs shape our thoughts about moving up the socioeconomic ladder. Unlike other social categories such as race and gender, social class is relatively malleable (Kraus & Stephens, 2012), and perceptions about socioeconomic opportunity are influenced by context (Chan et al, 2021). Given that belief in free will invokes agency and perceptions that one can exert some control over their environment (Baumeister & Brewer, 2012), it stands to reason that altering free will beliefs can influence how much people believe they can change their social standing.…”

The psychology of cultural change: Introduction to the special issue.

“…Some of the articles in this special issue focus on the "What" of cultural change-documenting shifts in specific phenomena such as prejudice (Charlesworth & Banaji, 2021), mental health (Infurna et al, 2021), individualism (Hamamura et al, 2021), social mobility (Chan et al, 2021), and religious beliefs and practices (Jackson et al, 2021). Other articles focus on the "Why"-testing theories regarding the causes of specific cultural changes, such as shifts over time in levels of individualism (Kusano & Kemmelmeier, 2021), or openness (Götz et al, 2021), or fertility (Rotella et al, 2021).…”

“…These pieces capture a range of theoretical perspectives that have been brought to bear on how and why cultures change over time, including insights from evolutionary psychology (Jackson et al, 2021; Kusano & Kemmelmeier, 2021; Pan et al, 2021), behavioral ecology (Rotella et al, 2021), cultural evolution (Schaller & Muthukrishna, 2021), and socioecological psychology (Buttrick & Oishi, 2021). The special issue also highlights the diversity of methodological approaches in this emerging field ranging from computational modeling (Jung et al, 2021; Schaller & Muthukrishna, 2021; Pan et al, 2021), to machine learning (Sheetal & Savani, 2021; Stavrova et al, 2021), to time series analyses (Charlesworth & Banaji, 2021; Chan et al, 2021; Götz et al, 2021; Kusano & Kemmelmeier, 2021; Rotella et al, 2021).…”