Replication Data for: The Effect of Human vs. Automated Interaction on Willingness to Participate in Government Programs: The Role of Representation
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
View Archive InfoField | Value | |
Title |
Replication Data for: The Effect of Human vs. Automated Interaction on Willingness to Participate in Government Programs: The Role of Representation
|
|
Identifier |
https://doi.org/10.7910/DVN/SQSNFY
|
|
Creator |
Miller, Susan
Song, Miyeon Keiser, Lael R. |
|
Publisher |
Harvard Dataverse
|
|
Description |
Increased reliance on automated systems in government raises important questions about the impact of these systems on program participation. We look at the relationship between an automated application process and program participation through a representation lens. From a representative bureaucracy perspective, we examine whether gender representation increases participation intentions compared to interacting with an automated system. We also consider a political dimension of representation, investigating whether interacting with an automated system increases participation intentions among those whose policy preferences do not align with program goals. While we do not see differences based on gender representation in our survey experiment, we do find evidence that an automated system leads to greater willingness to participate among those whose policy preferences do not align with the program. These results provide insight into when automated systems may influence participation, suggesting a potential positive role among those who are not politically favorable towards a program.
|
|
Subject |
Social Sciences
|
|
Language |
English
|
|
Contributor |
Miller, Susan
|
|