Read on Twitter
After thinking on it over the weekend, I have a couple of thoughts about this panel (both a bit negative + a tad contrarian it seems, though maybe just among the 6 panelists): https://twitter.com/RoperCenter/status/1351963978822537216
1. A constant refrain I hear from public opinion researchers is that the public wants (& practitioners should focus on) public opinion polling on policy & political 'issues', not election / candidate polling
The argument is reminiscent of anti-fast food dietary rhetoric. People should / do want issue polls because this is the 'healthy' way to engage in public opinion as opposed to the "guilty pleasure" of election polling
I think people are drawn to election polling because who ends up being an elected official is insanely consequential to the lives of many Americans. Political leaders also help "determine" the ideological focus of our politics, especially among co-partisans
It makes sense that researchers love "issue polling". We are really deeply interested in politics and what the public thinks and it's repercussions on politics. It also adds important extra dimensions to our work, especially when elections aren't ongoing.
I'm surprised the panelists didn't think that a recent conservative bias in election polling somehow wouldn't imply that estimates of issue opinion have similar (or even worse) biases. Correlational and experimental studies shouldn't be immune either just because of randomization
Election polling is one of the few times in public opinion research when we are asked to measure a clear and easily validated construct and should be an important criterion for understanding the public (though it of course can be easily manipulated and gamed, see Goodhart's Law)
2. Should we be positive about the future of public opinion research? Maybe? I'm a bit indifferent here. On the one hand, I'm sure if you asked this panel the same question about 2016 in the run-up to 2020 I'm sure they would be similarly positive. It's important to be realistic
On the other hand, we've never had better tooling to analyze survey data. @doug_rivers & team has been at the forefront of pushing the modern statistical toolkit & others have followed, but too much of the work being done has been decidedly uncreative
Academic work may be promising but their timelines & incentive structures don't seem to align on some of these core problems. I have a strong sense of what the future should look like here, but I've grown pessimistic about who will drive this innovation in the public sphere
Anyways, thanks @RoperCenter for the engaging discussion & the panelists for their wisdom. We get better when we work and talk together. Here's to finding those solutions :)
