The Legislative Legacy of Strict Voter Identification Laws

2021 ◽  
Author(s):  
Alejandra Campos ◽  
Jeff Harden
Keyword(s):  
Voter Identification

Understanding the Adoption of Voter Identification Laws in the American States

2017 ◽  
Vol 45 (4) ◽  
pp. 560-588 ◽  
Author(s):  
Daniel R. Biggers ◽  
Michael J. Hanmer
Keyword(s):  
Event History Analysis ◽  
Political Power ◽  
The State ◽  
Event History ◽  
Federal Legislation ◽  
The Past ◽  
Voter Identification ◽  
Extensive Analysis ◽  
American States ◽  
History Analysis

Recently, many states have reversed the decades-long trend of facilitating ballot access by enacting a wave of laws requesting or requiring identification from registrants before they vote. Identification laws, however, are not an entirely new phenomenon. We offer new theoretical insights regarding how changes in political power influence the adoption of identification laws. In the most extensive analysis to date, we use event history analysis to examine why states adopted a range of identification laws over the past several decades. We consistently find that the propensity to adopt is greatest when control of the governor’s office and legislature switches to Republicans (relationships not previously identified), and that this likelihood increases further as the size of Black and Latino populations in the state expands. We also find that federal legislation in the form of the Help America Vote Act seems to enhance the effects of switches in partisan control.

Data Mining Based Intelligent System for Voting Behavior Analysis

2013 ◽  
Vol 284-287 ◽  
pp. 3070-3073
Author(s):  
Duen Kai Chen
Keyword(s):  
Data Mining ◽  
Behavior Analysis ◽  
Voting Behavior ◽  
Intelligent System ◽  
Data Sets ◽  
Tree Model ◽  
Mining Technology ◽  
Identification Rate ◽  
Voter Identification ◽  
Election Studies

In this study, we report a voting behavior analysis intelligent system based on data mining technology. From previous literature, we have witnessed increasing number of studies applied information technology to facilitate voting behavior analysis. In this study, we built a likely voter identification model through the use of data mining technology, the classification algorithm used here constructs decision tree model to identify voters and non voters. This model is evaluated by its accuracy and number of attributes used to correctly identify likely voter. Our goal is to try to use just a small number of survey questions while maintaining the accuracy rates of other similar models. This model was built and tested on Taiwan’s Election and Democratization Study (TEDS) data sets. According to the experimental results, the proposed model can improve likely voter identification rate and this finding is consistent with previous studies based on American National Election Studies.

An Enhanced Computational Fusion Technique for Security of Authentication of Electronic Voting System

2020 ◽  
Vol 7 (2) ◽  
pp. 22-37
Author(s):  
Adewale Olumide Sunday ◽  
Boyinbode Olutayo ◽  
Salako E. Adekunle
Keyword(s):  
Acceptance Rate ◽  
Electronic Voting ◽  
Biometric System ◽  
Voter Identification ◽  
Voting System ◽  
Mathematical Equations ◽  
One Time Password ◽  
Authentication Security ◽  
Electronic Voting System ◽  
False Acceptance

The detection of a false individual who had not been enrolled as a genuine participant in an election could be potentially detected in electronic voting systems as against paper-based methods. In recent time, one-time password and biometrics have been used to curtail false acceptance of imposters. However, imposters had unlawfully stolen the credentials of genuine individuals, gained unauthorized access, and polled illegitimate votes due to poor authentication methodology. The accuracy of a multi-biometric system is a function of the data type used and fusion method adopted. This paper presented a computational fusion approach that involved the use of fingerprint and randomly generated voter identification number to effectively satisfy the authentication security requirement of the electronic voting system. New architectural and mathematical equations on the proposed approach were presented to tackle the problem of false acceptance rate and improve on the true acceptance rate of a biometric system. Algorithm to achieve the proposed approach was presented in this paper as well.

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