Presenting more dissertation work today at #APSA2019 (4pm, Marriott Harding). I argue that we need to pay more attention to the information environment to understand why public attitudes often diverge from consensus expert opinion. Another thread 👇 [1/13] #SocSciResearch 
Many citizens learn about hard or technical political issues through the news media. However, we know that pathologies in news production generate superficial content that emphasizes novelty and drama. The news media may not often convey info about expert consensus [2/13]
And even when they do cover expert consensus, bias towards conflict and balance may lead journalists to cite contrarian experts (i.e. false balance) or polarizing political opponents that may confuse readers about expert consensus or prime them to resist it [3/13]
We don't have a good sense of how or how often information about expert consensus is covered in the news media, particularly outside the context of climate change. That's the purpose of this paper [4/13]
I gathered ~300,000 news stories (since the early 1980s in the U.S.) from cable, broadcast, print and newswire sources on 10 issues where there is meaningful expert consensus. Some of these positions are resisted by conservatives, others by liberals, or a mix [5/13]
I use dictionaries to ID stories w/expert references and supervised machine learning to ID stories w/content relevant to the expert consensus. I manually code 3,000 of these stories to provide estimates of the share of content with expert messages and consensus cues [6/13]
The central takeaway finding is that expert messages are not that common and consensus cues are very rare, *even in content directly relevant to the consensus in question.* The presence of experts is notably higher in CC and vaccine coverage [7/13]
I code the "balance" of news stories - how slanted a given article is in favour of expert opinion or opposed to it (1 to -1). On average, balance tilts towards the position of the expert community (0.3). This pattern is overwhelming in CC and vaccine coverage [8/13]
Finally, I code whether expert messages are rebutted by contrarian experts (false balance) or polarizing political opponents. False balance isn't all that common (22%), but it comparably higher in GMO and nuclear power coverage [9/13]
Polarizing opponents are more commonly cited (42%), especially on economic issues. Worth noting: journalists uniquely avoid both false balance and polarizing opponents in CC and vaccine coverage [10/13]
My data set also allows me to make comparisons between news format, outlet partisan or ideological leaning, and over time [11/13]
To wrap up, worries about journalistic balance in news content may be overstated on the issues where it has received the most attention. A bigger concern is the inability of journalists to consistently provide information about expert consensus where it exists [12/13]
I just got my PhD at @UBCPoliSci. I'm currently a postdoc at the @munkschool with @PeejLoewen. If you are interested in more of my work, check out ericmerkley.com. Hire me! [FIN]
@UBCPoliSci @munkschool @PeejLoewen Working paper posted here: ericmerkley.files.wordpress.com/2019/08/merkle…
