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Public Accountability and Political Participation: Effects of a Face-to-Face Feedback Intervention on Voter Turnout of Public Housing Residents.

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Title: Public Accountability and Political Participation: Effects of a Face-to-Face Feedback Intervention on Voter Turnout of Public Housing Residents.
Authors: Davenport, Tiffany
Source: Political Behavior. Sep2010, Vol. 32 Issue 3, p337-368. 32p. 6 Charts.
Subjects: Political participation, Voter turnout, Voters, Poor people, Face-to-face communication, Political communication, Urban poor, Local elections
Abstract: Low turnout among the urban poor has implications for democratic representation. The fact that turnout among the economically disadvantaged is especially low in municipal elections means that citizens most in need of services provided at the local level may not be represented in policy decisions that affect their daily lives. This paper reports the results of an experiment that compares the effects of two voter mobilization interventions: traditional canvassing appeals and face-to-face exchanges in which canvassers distribute a feedback intervention consisting of printed records of individual voter histories. In contrast to previous studies, this experiment measures the effectiveness of using social pressure to mobilize turnout among relatively infrequent voters in a low salience election. The campaign was implemented by a credible tenant advocacy organization within the context of a municipal election; the sample consisted of registered voters in two Boston public housing developments. I find that the feedback intervention dramatically increased voter turnout. Turnout among those reached by canvassers with voter histories was approximately 15–18 percentage points higher than turnout in the control group, an effect that is approximately 10 percentage points larger in magnitude than that of standard face-to-face mobilization. [ABSTRACT FROM AUTHOR]
Copyright of Political Behavior is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Low turnout among the urban poor has implications for democratic representation. The fact that turnout among the economically disadvantaged is especially low in municipal elections means that citizens most in need of services provided at the local level may not be represented in policy decisions that affect their daily lives. This paper reports the results of an experiment that compares the effects of two voter mobilization interventions: traditional canvassing appeals and face-to-face exchanges in which canvassers distribute a feedback intervention consisting of printed records of individual voter histories. In contrast to previous studies, this experiment measures the effectiveness of using social pressure to mobilize turnout among relatively infrequent voters in a low salience election. The campaign was implemented by a credible tenant advocacy organization within the context of a municipal election; the sample consisted of registered voters in two Boston public housing developments. I find that the feedback intervention dramatically increased voter turnout. Turnout among those reached by canvassers with voter histories was approximately 15–18 percentage points higher than turnout in the control group, an effect that is approximately 10 percentage points larger in magnitude than that of standard face-to-face mobilization. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Political Behavior is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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