Evidence map›Paper›PMID 36311165›Full record

ArticleElectoral studies2022

The impact of the Covid-19 pandemic in a polarized political system: Lessons from the 2020 election.

Jon D Miller, Logan T Woods, Jason Kalmbach

Abstract read
In one paragraph

Article in Electoral studies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jon D MillerInternational Center for the Advancement of Scientific Literacy, Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48106, USA.
Logan T WoodsDepartment of Political Science, University of Michigan, 5700 Haven Hall, 509 S. State Street, Ann Arbor, MI, 48109, USA.
Jason KalmbachNational Coalition of Independent Scholars (NCIS), USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the deep polarization of the American political system in recent decades, was the 2020 presidential election an extension of the pre-existing partisan coalitions or did the Covid-19 pandemic and its economic consequences have a significant impact on the outcome? Using a national probability sample provided by AmeriSpeak and voter verification provided by Catalist, we construct a structural equation model to examine the relative influence of age, race, gender, education, religious fundamentalism, ideological partisanship, affective partisanship, and measures of Covid-19 experiences and understanding to predict the 2020 vote. We re-construct the partisan polarization landscape to examine the role of politically interested non-partisans in the center of the ideological spectrum and examine their ability to select candidates in response of specific issues. The Covid-19 pandemic had a significant marginal impact on the outcome of the 2020 presidential election.

Indexed as

Affective partisanshipAnd Covid-19 knowledge and understandingIdeological partisanshipPresidential voteReligious fundamentalism

Identifiers

PMID36311165
PMCPMC9595380

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.