Communicating safety precautions can help maintain in-person voter turnout during a pandemic.

Eric Merkley, Thomas Bergeron, Peter John Loewen, Angelo Elias, Miriam Lapp

Open access · greenAbstract 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. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

1.6field-weighted citation impact, top 15% of its field

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

1 citing paper in PubMed, 13 citations in OpenAlex.

Mass gatherings for political expression had no discernible association with the local course of the COVID-19 pandemic in the USA in 2020 and 2021.Nature human behaviour · 2023
Article

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

5 authors at 2 institutions in 1 country.

Eric MerkleyDepartment of Political Science, University of Toronto, SS 3018, 100 St. George Street, Toronto, ON, M5S 3G3, Canada.

Thomas BergeronDepartment of Political Science, University of Toronto, SS 3018, 100 St. George Street, Toronto, ON, M5S 3G3, Canada.

Peter John LoewenDepartment of Political Science, University of Toronto, SS 3018, 100 St. George Street, Toronto, ON, M5S 3G3, Canada.

Angelo EliasElections Canada, 30 Victoria Street, Gatineau, QC, K1A 0M6, Canada.

Miriam LappElections Canada, 30 Victoria Street, Gatineau, QC, K1A 0M6, Canada.

University of Toronto · CAPublic Works and Government Services Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scholars have linked cost and life stress to lower voter turnout with clear implications for voting during the COVID-19 pandemic. We ask whether COVID-19 reduces turnout intention and how election agencies can mitigate this effect. We use a series of six survey and conjoint experiments implemented in samples totalling over 28,000 Canadian respondents collected between July and November of 2020 to show that: 1) priming people to think about COVID-19 reduces turnout intention, especially among those who feel most threatened by the disease; 2) safety measures for in-person voting, such as mandatory masks and physical distancing, can improve safety perceptions and willingness to vote in-person, and 3) providing people information about safety precautions for in-person voting mitigates the negative effect of priming COVID-19. These studies illustrate the importance of both the implementation and communication of measures by election agencies designed to make people safe - and feel safe - while voting in-person.

Indexed as

Cost of votingCOVID-19Election administrationElection safetyVoter turnout

Identifiers

PMID35125592

DOI10.1016/j.electstud.2021.102421

PMCPMC8796996

OpenAlexW3214080342

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.