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Changing the Scope of Conflict? Voter Registration and George Floyd’s Murder

Published online by Cambridge University Press:  23 April 2026

Hans J. G. Hassell
Affiliation:
Florida State University, Tallahassee, FL, USA
John Holbein*
Affiliation:
University of Virginia, Charlottesville, VA, USA
*
Corresponding author: John Holbein; Email: holbein@virginia.edu
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Abstract

Prior work has often studied how focusing events – in particular police killings of unarmed people – affect citizens’ attitudes. Do focusing events also affect citizens’ behaviors – changing the scope of conflict by incorporating prospective voters into the political system? We take as an empirical case the murder of George Floyd. Using nationwide voter file data from the United States, we leverage regression discontinuity in time methods to show that Floyd’s murder noticeably increased voter registration. These effects are present across many individual subgroups, providing evidence of mobilization and counter-mobilization. Floyd’s untimely death sparked many people from previously marginalized backgrounds to register, but simultaneously also increased registrations among the politically advantaged – thus mitigating any impact on the partisan balance of power. In short, high-profile traumatic events like Floyd’s death do not appear to disproportionately advantage groups seeking reforms to change the circumstances surrounding such events.

Information

Type
Letter
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press
Figure 0

Figure 1. Effect of George Floyd’s murder on voter registration.Note: coefficient plots for the effect of Floyd’s murder on registration counts broken by various individual subgroups. Points are coefficient estimates; bars are 90 per cent and 95 per cent confidence intervals. Voter registration counts drawn from L2 data. Results from RDiT models using a polynomial of order 1, employing a triangular kernel that gives additional weight to observations near the cut-off, and leveraging the mean-squared-error (MSE) optimal bandwidth.

Figure 1

Figure 2. Effect of George Floyd’s murder on the net balance of partisan voter registration.Note: coefficient plots for the effect of Floyd’s murder on registration counts broken down by state. Points are coefficient estimates; bars are 90 and 95 per cent confidence intervals. Voter registration counts drawn from L2 data. Results from RDiT models using a polynomial of order 1, employing a triangular kernel that gives additional weight to observations near the cut-off, and leveraging the mean-squared-error (MSE) optimal bandwidth. Points are sized by the number of county-day observations and are shaded by the presidential vote share in the county – black = Most Republican tercile, Light gray = Most Democratic tercile.

Figure 2

Figure 3. The effect of George Floyd’s murder on voter registration was larger in areas with high protest incidence.Note: coefficient plots for the effect of Floyd’s murder on registration counts broken by whether a protest was present in the county prior to Floyd’s murder (on the left) and whether a BLM protest was present in the county prior to Floyd’s murder (on the right). Points are coefficient estimates; bars are 90 and 95 per cent confidence intervals. Voter registration counts drawn from L2 data. Protests data drawn from the Crowd Counting Consortium (CCC). Results from RDiT models using a polynomial of order 1, employing a triangular kernel that gives additional weight to observations near the cut-off, and leveraging the mean-squared-error (MSE) optimal bandwidth. As we note in the Online Appendix, these effects are robust to slight variations in treatment date, including the day after the event when news of the murder spread on social media. The BLM coefficients on the right have wider error bars because there are fewer pre-treatment BLM protests than overall protests.

Figure 3

Figure 4. Effect of George Floyd’s murder relative to other murders of unarmed black people.Note: the figure above shows the differences-in-discontinuities estimates between 2016 and 2020 of Floyd’s murder and the murders of other unarmed black people. Points are coefficient estimates; bars are 90 and 95 per cent confidence intervals. Points are sorted by coefficient size. Voter registration counts drawn from L2 data. To ensure equivalent power across model, h = 5 and b = 10. As can be seen, Floyd’s murder appears unique in terms of the voter registration boost that we document.

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Hassell and Holbein supplementary material

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