Study people, not numbers, for truth post Trump’s election

Some social scientists, including us, will tell you that they thought Donald Trump could win the US presidential election. But few expected he really would. And within sociology – the academic circle we most often navigate – scholars certainly did not prepare for a Trump victory.

We have come to believe that this wasn’t arrogance so much as oversight. Social science has become increasingly beholden to analysis derived from big data: large numerical sets analysed computationally. This has brought us much insight into the social world, but it has often come at the direct expense of the rich qualitative work most likely to capture people’s everyday patterns of meaning-making and decision-making.

The more interpretative methodological tools of interviewing and observation, once the hallmark of the social sciences, are giving way to an increased reliance on numbers in nearly all realms of social and political life. But in order for us to understand the election results and to properly document the effects of a Trump administration, social scientists need to conduct more research into people’s everyday lives. And in order to understand people’s real lives, we need more thoughtful qualitative work.

The 19th-century mathematician and physicist Lord Kelvin famously said: “When you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.” This sentiment has become appealing to many social scientists as new information technologies facilitate the accumulation of greater amounts of quantitative data. The embrace of big data is part of a larger trend to try to capture and predict social life using only numbers. As the legal anthropologist Sally Merry explains in her recent book The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking, quantitative data analysis is seductive. Yet when we try to translate the confusion of social life only into discrete variables, we strip away context and meaning. Qualitative work helps to bring back in some of this nuance as a complementary component of the larger social science endeavour.

Ignoring context and meaning in the run-up to the 2016 election came at a cost. There is a difference between a wholehearted Trump supporter and someone who “begrudgingly” supported him, as noted by an evangelical Christian one of us interviewed. Just as social scientists have worked hard for decades to show the heterogeneity of minority communities, we need to respect the fact that there is no single “red” or rural voter. So the University of California, Berkeley sociologist Arlie Hochschild’s 2016 book Strangers in Their Own Land: Anger and Mourning on the American Right cannot be the only one written about Trump supporters. Nor can she be the sole ethnographic voice charting the future of research into the political Right.

This means that social scientists will have to be willing to spend a lot of time among people with whom they likely disagree. This may include people who reject the very ideological “values” most academics profess as the hallmarks of progress. The same could be said in Europe, where largely middle-class and secular academics may find it difficult to understand both the anti-immigrant sentiments of working-class voters and the deep religious commitments of newcomers to the continent. More interpretive work based on capturing everyday personal narratives may help to bridge the divide between those two populations – which may prove more consequential come the spring, when France, Germany and the Netherlands all hold general elections.

We as social scientists can also do a better job of translating our research for non-academic audiences: people who do not necessarily use our jargon but also crave understanding. One of us grew up in a rural community, where the immigration that the academy supports so strongly feels like a risk to ever-dwindling jobs. The other grew up in a traditionally red Texas suburb. So we both know lots of people who mean well but have no idea what “heteronormativity” means, or how it can help to explain why white women with college degrees voted for Trump.

Bringing jargon-free interpretative analysis into wider public discourse is one of the many steps scholars can take to address the yawning gaps in our understanding of voter intentions – as well as the yawning ideological gap between the political Left and Right.

Pamela Prickett is a postdoctoral fellow in the department of sociology and Elaine Howard Ecklund is Herbert S. Autrey chair in social sciences and director of the religion and public life programme at Rice University in Houston, Texas.