Does automation replace experts or augment expertise? The answer is yes.
Yes, automation replaces experts or augment expertise.
Veranstaltungsreihe: Special Lecture Series
Herausragende internationale Forschende aus den Sozialwissenschaften stellen in der „IAB-Special Lecture Series“ ihre aktuelle Arbeit vor. Sie werden aufgrund ihrer herausragenden akademischen Leistungen ausgewählt, haben bedeutende Beiträge zu ihrem Fachgebiet geleistet und gestalten aktiv die internationale Forschungsagenda.
Patterns and Paradoxes of Migrant and Ethnic Inequalities in the UK
This lecture examines the patterns and paradoxes in observed educational and labour market attainment of migrants and minorities.
Measuring and Predicting New Work in the US: the role of local factors and global trends
`New work”, namely the introduction of types of jobs that did not exist earlier, is an essential part of innovation and employment growth for advanced economies.
Exploring Trust Dynamics in Citizens-State Interactions for Access to Public Services
This lecture delves into the multifaceted dynamics of the state-citizen relationship within the realm of service delivery in vulnerable contexts.
Climate Change, Migration, and Inequality
Can weather events predict migration choices of 140,000+ individuals?
Quantifying Non-Sampling Variation: College Quality and the Garden of Forking Paths
Moving the Needle: What Tight Labor Markets Do for the Poor
This lecture investigates the most durable positive consequences of tight labor markets and focus on the mechanisms that produce positive outcomes.
Short-run incentives and long-term commitments in maternity protection policy (englische Seite)
Evicted. Poverty and Profit in the American City (englische Seite)
Changing Gender Status Beliefs? Implications for Gender Inequality in the Labor Market
We draw on research on status processes and cultural change to develop predictions about gender status beliefs in the United States. We expect that
- while explicitly men and women may not distinguish competency and worth by gender, they do so implicitly,
- that younger respondents, especially women, hold less consensual gender status beliefs, and
- men are less likely to alter their gender status beliefs due to loss aversion.
We conduct two studies to assess these arguments. The first uses novel nationally-representative data to describe the distributions of status beliefs in the US population; the second demonstrates the importance of these beliefs for allocating rewards by gender. Combined, the studies demonstrate the distribution of gender status beliefs by age and gender, and the implications for gender inequality, thereby illustrating the role of cultural status beliefs for maintaining gender stratification and the potential role of cohort change for changing such beliefs. Finally, we discuss promising approaches to reduce the impact of gender status beliefs in labor market processes.