35476 California Families Project [Sacramento and Woodland, California]
36531 An Analysis of the Effects of an Academic Summer Program for
Middle School Students, 2012
36612 Los Angeles Metropolitan Area Surveys [LAMAS] 2, 1970
36687 Afrobarometer Round 6: The Quality of Democracy and Governance in
36722 National Survey of Midlife Development in the United States (MIDUS
Refresher): Milwaukee African American Sample, 2012-2013
36738 Sit Together and Read in Early Childhood Special Education
Classrooms in Ohio (2008-2012)
Academia isn’t like the public sector or firms or nonprofits. These days, people in those sectors are trying to read the tea leaves about what’s coming next. In a post-truth world, everything is negotiable, so it’s all about reading the fault lines of debates, figuring out who wants what.
I became an academic because I believe in evidence. It’s easy for critics to wrongly claim that universities are full of informational relativism, but I don’t see it. Instead I see groups of people trying to find the best ways to discover evidence about truth. The most bitter fights are about how we assemble that evidence because it isn’t easy to demonstrate causality.
Academics are also facing the decision of whether to invest time reading the political fault lines – or to double down on evidence.
If I was gifted with reading those political tea leaves I would have run for office. I’m not, so I’m doubling down on evidence. I’m doing so because post-truth, like other movements, is a fad. Assuming we survive it, after it fades, there will be a great demand for evidence. Somewhere, sometime, people will want evidence about how to make policy or manage organizations.
In the end, this is the primary responsibility of academics – to double down on evidence, not to translate or write opeds or whatever. If we don’t discover, who will?
New with Derrick Anderson of Arizona State University, this paper is now forthcoming at the Review of Policy Research. Here’s the abstract:
National statistical systems are enterprises tasked with collecting, validating and reporting societal attributes. These data serve many purposes–they allow governments to improve services, economic actors to traverse markets, and academics to assess social theories. National statistical systems vary in quality, especially in developing countries. This study examines determinants of national statistical capacity in developing countries, focusing on the impact of technological attainment. Just as technological progress helps to explain differences in economic growth, we argue that states with greater technological attainment have greater capacity for gathering and processing quality data. Analysis using panel methods shows a strong, statistically significant positive linear relationship between technological attainment and national statistical capacity.
Please feel free to contact me for a pre-publication version of the paper.