Does cross-cutting exposure help or hinder participation?
Somewhat predictably, I fell off the seminar-blogging wagon shortly after the break. But hey, this is a digital semester, so we have actual archived notes of our virtual meetings.
One of the first texts we read in the new year was this one: a specimen of the meta-analytic approach that is becoming more and more popular in Political Science. In this one, the authors want to find out if cross-cutting exposure (i.e. escaping from the filter bubble) has any positive or negative effects on political participation. Turns out that there is insufficient evidence for either.
Matthes, J., Knoll, J., Valenzuela, S., Hopmann, D. N., & Sikorski, C. v. (2019). A meta-analysis of the effects of cross-cutting exposure on political participation. Political Communication, 36(4), 523–542. http://dx.doi.org/10.1080/10584609.2019.1619638
What we liked
Most students had never heard of meta-analyses and were quite intrigued. They found the idea of pooling evidence from several published studies “stimulating” (their words) and were particularly happy that the authors had carefully documented each of their steps. They also liked the presentation of research questions and hypotheses.
Finally, some students had previously heard of publication bias. They were impressed that the authors applied a test for that, and were even more impressed that a journal had the guts to publish null results.
What we did not like so much
Some students were disappointed that the authors did not conduct any primary analysis, but (wait for it!), that’s the whole point of a meta analysis, right? A more serious criticism (levelled more at the journal and its page limit than at the authors) was that at least two interesting graphs were relegated to the appendices. And finally, students said that the summary & outlook section was too short. While I agree, I can also relate to the authors: you do all the work, you write it up, why should you have to summarise it again?