When it comes to hot topics in social science research, the potential link between intelligence and success ranks near the top of the list. New findings from a USC Marshall School of Business researcher turn the debate on its head and offer a novel approach to shaping public policy as a means of addressing social inequality.
Intersectional Inequality: Race, Class, Test Scores & Poverty, a recently published book by Charles Ragin, a Chancellor’s Professor of Sociology at UC Irvine, and Peer Fiss, USC Marshall Professor of Management and Organization, reveals what they deem critical flaws in The Bell Curve, which was published in 1994 by Richard Herrnstein and Charles Murray and immediately sparked global controversy. That book argued for a correlation between test scores and life chances – suggesting that an individual’s intelligence is the most important factor in determining descent into (or emergence out of) poverty.
Soon after, a team of prominent UC Berkeley sociologists used the same data to publish a refutation of Herrnstein and Murray’s explosive thesis. Over the past 20-plus years, the dispute has raged; in Intersectional Inequality, Ragin and Fiss finally explain why they think camps on both side are wrong: Their work is based on a faulty premise.
“All of these researchers take data from the National Longitudinal Survey of Youth and attempt to isolate the effects of one variable from the others,” says Fiss. “In other words, they use the same methodology and differ only in their ideas about which variable – whether it’s test scores, parental income or something else – is the most important, with the other variables held constant.”
The problem, he continues, is that this misses a crucial point: Poverty is not primarily determined by one factor but by a broad range of factors that jointly create conditions that foster or suppress it. “Those with the most money tend to have more highly educated parents, live in nicer neighborhoods and send their children to better schools—advantages coincide. The same is true at the other end of the economic scale, where disadvantages co-occur.” Fiss notes. “The notion that we can zoom in on the unique impact of one of these factors while keeping all the others steady is very problematic. Ultimately, these varying influences combine rather than compete with one another to shape life outcomes.”
Reframing the Conversation
Ragin and Fiss arrive at their conclusion using sets and Boolean algebra to identify patterns in data. Their research leverages a methodological toolkit, developed by Ragin starting in the 1980s, called Qualitative Comparative Analysis (QCA), which they maintain yields more accurate results than earlier works’ reliance on standard correlational analysis.
“Our goal was to examine the different ‘recipes’ that are associated with life chances,” Fiss says. “We wanted to know what combination of circumstances could protect someone from experiencing poverty – or push them more deeply into it.” As Ragin and Fiss show, blacks are "doubly disadvantaged": not only must they cope with having fewer advantages, but they also must accumulate more advantages than whites in order to avoid poverty.
Ragin and Fiss point out that the debate over intelligence and its intersection with poverty has always been fueled by competing political perspectives. The result, they say, is that the agenda manipulates the data instead of being driven by it.
Intersectional Inequality reframes the conversation, paving the way for an informed policy discussion that puts partisanship aside in favor of comprehensive, collaborative solutions.
“We believe this book has great potential for enhancing our ability to tackle entrenched challenges facing our society,” Fiss says.