The most important thing about November 8 is of course the result itself, but as a professional social scientist, I want to put out a few thoughts on what the 2016 elections might mean for social science.
For the last year, I have repeatedly told colleagues and friends I thought there was no chance Donald Trump would be elected president. Yesterday, I told a colleague I thought Hillary Clinton would win the popular vote by maybe 3 percent and it could be an early evening if she won Florida or North Carolina.
I was wrong.
My view was based on three things, all tied in with my core belief that while imperfect, social science is better than guessing—
- Long-term trends: extensive political science research suggesting that economic and political fundamentals, and underlying demographic shifts, are more important than the campaign itself. Much of this research suggested any Democrat running in 2016 would start the race ahead of any Republican.
- Month-by-month measures of performance: immense amounts of public opinion polling and detailed analysis of it both by academic political scientists and by data journalists, which almost consistently showed Hillary Clinton ahead nationally and in key states.
- The campaign itself: the sense—impressionistic, but linked to my own qualitative research and the five years I lived in the US—that while Donald Trump clearly spoke to deeply held grievances amongst many (especially White) Americans, a billionaire member of 1% with a history of personal and professional scandals who did not have the support of his party was unlikely to make major gains during the campaign itself, especially as his organization itself seemed disorganized and inefficient.
Again, I was wrong. We were wrong. Very publicly, both in terms of academics who have had the courage and sense of citizenship to publish their predictions along the way and in terms of data journalists working in large part on the basis of social science data and methods, only doing so in real time with running commentary.
It is a humbling moment. The scientific response is to re-examine our assumptions, methods, and data, and see what we can do better.
One result, however important and high-profile, does not disprove everything we thought we knew as scientists about politics and everything we thought we knew about how to study politics scientifically.
Science is hard. We are in the dark, poking at the world with different sticks.
But we shouldn’t trivialize just how important this is, and I think addressing it will take more than tweaking and paradigm repair.
As powerful as I believe quantitative analysis and survey research can be, I can’t help but feel that part of the problem is that many of us as social scientists have lost track of what politics means for many people. For me, the 2016 UK Brexit result and the 2016 US election results both illustrate this wider problem.
It is easy to look back and identify prescient observations, but in terms of trying to make sense of November 8, I can’t help but feel the most insightful books might have been Katherine Cramer’s The Politics of Resentment and Arlie Hochschild’s Strangers in Their Own Land. Neither of them aimed to predict the election outcome. Neither of them focused on the kinds of large quantitative data sets, detailed polling, or scraped digital trace data that most social scientists work with.
Instead of looking at the numbers, Cramer and Hochschild went and talked to people to find the feelings, emotions, and meanings that are hard to get at with the most widely used social science methods.
I want to be clear this is not about qualitative methods being good and quantitative methods being bad. They are good at different things and should compliment each other. We need to capture both stories and numbers to understand the world (and in the social sciences, to understand how people understand the world, and act on their understanding).
But I think that, beyond re-examining what can be done incrementally with existing approaches to improve the models, the samples, the assumptions about who will vote, this (along with the Brexit result in the UK) is also a moment where we have to confront a more basic issues—
We as social scientists do not have a good, evidence-based understanding of how most people understand and relate to politics and the world around them. And if we don’t have that qualitative understanding, it is very hard to develop quantitative analysis and methods that will capture it. We know a lot about what people do, but very little about what it means for them.
And no, “big data” scraped from digital media or other sources will not solve this problem by itself. Facebook and Google, who have more of this data than probably anybody else, are very conscious that behavioural data does not in itself reveal what things mean, and as a consequence invest heavily in qualitative research. I think the social sciences should walk on two legs, quantitative and qualitative, too. (And have written about that, with colleagues, before.)
As Stephen Coleman has written in his study of How Voters Feel, “the sustainability of any social practice depends to a large measure on how it feels to participate in it.”
I think it is clear we don’t know how most people feel about politics and how it ties in with other aspects of their lives and identities. Yes, we may know that some of them are not very interested, don’t like it very much, or a quite partisan. But what does that actually mean? I don’t think we know.
Historically, I think it is fair to say social scientists have simply assumed we knew, and primarily asked qualitative questions about the lived experience and perspective of groups that were considered minorities.
In my view 2016 shows we need to start qualitatively researching the (diverse, fractious, fascinating) majority to, and see whether a better, evidence-based understanding of how people relate to politics and public life can help us get it right next time.
Doing this might mean more social scientists have to actually talk to and spend time with the people they study. As John le Carré has noted, “A desk is a dangerous place from which to view the world.”