What can we learn by marshaling new data and approaches to study the past? That was the question in a successful webinar series launched by LCDS in the past year, the Nuffield Historical Social Mobility Seminar, organised by researcher Per Engzell.
“We had originally planned an in-person event but were forced online by the pandemic,” Engzell explains. Speakers ranged from California in the West to Hong Kong in the East; Chile in the South to Sweden in the North. “It was a challenge to run an event spanning 15 time zones, but this way we were able reach a much wider crowd.”
Participants were brought together by their interest in social mobility – how social class, education and income tend to run in families, and how individuals can escape their origins to climb the social ladder.
Social mobility is among the most studied topics in social science, but common data sources only go as far as a few decades back. We know much less about how economic fortunes changed in earlier times: during the rise of industry, democracy, modern infrastructure, or the welfare state.
Today, our understanding is evolving rapidly thanks to new data and methods. Engzell explains: “Information that used to be locked away in dusty archives is now available digitally to mine for insights.” With the Big Data revolution, we can study the past with the same lens we apply to the present.
What are some of the new insights gained? “One thing we have learned is that there was much more social mobility in the past than researchers have reckoned with,” says Engzell. “We think of rags-to-riches stories as something unique to our time, but to some extent they have always occurred.”
These new approaches challenge both traditional disciplines and a common divide between “historical” and “contemporary” scholarship, says Engzell. The webinar aimed to overcome such knowledge silos by drawing participants from demography, history, sociology, economics, and other backgrounds.
At the LCDS, historical Big Data research is conducted in the Digital & Computational Science Programme.