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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Election Administration Harms and Ballot Design: A Study of Florida's 2018 United States Senate Race |
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Identification Number: |
doi:10.7910/DVN/3FNP7Q |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-09-21 |
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Version: |
1 |
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Bibliographic Citation: |
Morse, Michael; Herron, Michael C.; Meredith, Marc; Smith, Daniel A.; Martinez, Michael D., 2024, "Replication Data for: Election Administration Harms and Ballot Design: A Study of Florida's 2018 United States Senate Race", https://doi.org/10.7910/DVN/3FNP7Q, Harvard Dataverse, V1 |
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Citation |
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Title: |
Replication Data for: Election Administration Harms and Ballot Design: A Study of Florida's 2018 United States Senate Race |
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Identification Number: |
doi:10.7910/DVN/3FNP7Q |
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Authoring Entity: |
Morse, Michael (University of Pennsylvania) |
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Herron, Michael C. (Dartmouth University) |
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Meredith, Marc (University of Pennsylvania) |
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Smith, Daniel A. (University of Florida) |
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Martinez, Michael D. (University of Florida) |
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Producer: |
Michael Morse |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Michael Morse |
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Depositor: |
Morse, Michael |
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Date of Deposit: |
2024-05-09 |
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Holdings Information: |
https://doi.org/10.7910/DVN/3FNP7Q |
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Study Scope |
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Keywords: |
Social Sciences, election administration, ballot design |
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Abstract: |
We introduce a typology of election administration harms and apply it to empirically study the consequences of ballot design. Our typology distinguishes between individual, electoral, and systemic harms. Together, it clarifies why ballot design can be a particular vulnerability in election administration. Using both ballot-level and precinct-level data, we revisit Florida's 2018 United States Senate race, in which Broward County's ballot design flouted federal guidelines and, according to critics, was pivotal to the outcome. We estimate that Broward's ballot design induced roughly 25,000 voters to undervote in a race determined by about 10,000 votes and that these excess undervotes were concentrated among low-information voters. Broward's ballot did not, however, affect the outcome of the election. Nonetheless, flawed ballot designs are still concerning in an age of voter distrust. Given the risk that flawed ballots can cause systemic harm, we offer a roadmap for procedural reforms to improve ballot design. |
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Notes: |
This dataset underwent an independent verification process, complying with the AJPS Verification Policy updated June 2023, which replicated the tables and figures in the primary article. For the supplementary materials, verification was performed solely for the successful execution of the code. The verification process was carried out by the Cornell Center for Social Sciences at Cornell University. <br></br> The associated article has been awarded the Open Materials Badge. Learn more about the Open Practice Badges from the <a href="https://www.cos.io/">Center for Open Science</a>. <br></br> <img src="https://socialsciences.cornell.edu/sites/default/files/2024-04/materials_large_color.png" alt="Open Materials Badge " width="60" height="60"> <br></br> Open Materials Badge |
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Methodology and Processing |
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Sources Statement |
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Data Sources: |
As described in the article, the precinct and demographic data comes from data made publicly available by the Florida Secretary of State, while the cast vote records come from public information requests made to Florida local election officials. |
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Data Access |
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Disclaimer: |
The <i>American Journal of Political Science</i> and the Cornell Center for Social Sciences are not responsible for the accuracy or quality of data uploaded within the <i>AJPS</i> Dataverse, for the use of those data, or for interpretations or conclusions based on their use. |
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Other Study Description Materials |
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Codebook.pdf |
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Notes: |
application/pdf |
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data-ballots_for_model.parquet |
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application/octet-stream |
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data-demographics_2016.rds |
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application/octet-stream |
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data-demographics_2018.rds |
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application/octet-stream |
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data-election_results_aggregated.rds |
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application/octet-stream |
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data-model_estimates.rds |
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application/octet-stream |
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data-model_function.R |
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type/x-r-syntax |
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data-model_run.R |
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type/x-r-syntax |
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data-model_uncertainty.rds |
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application/octet-stream |
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data-precincts_2016.rds |
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application/octet-stream |
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data-precincts_2018.rds |
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application/octet-stream |
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data-precincts_over_time.rds |
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application/octet-stream |
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fig_3.R |
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type/x-r-syntax |
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fig_4.R |
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type/x-r-syntax |
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fig_5.R |
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type/x-r-syntax |
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fig_6_A7.R |
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type/x-r-syntax |
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fig_7.R |
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type/x-r-syntax |
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fig_8.R |
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fig_A3.R |
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fig_A4.R |
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fig_A5.R |
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footnote_9.R |
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type/x-r-syntax |
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Readme.txt |
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text/plain |
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tbl_1.R |
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type/x-r-syntax |
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tbl_3_A1.R |
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type/x-r-syntax |
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tbl_4_A2.R |
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type/x-r-syntax |
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tbl_5.R |
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type/x-r-syntax |
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_install_or_load_required_packages.R |
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type/x-r-syntax |