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Young People, Media Use, and Voter Turnout: An Analysis of the 2000 National Election Study
Unformatted Document Text:  Young Voters and Media Use 12 impact of media use in explaining the variance in young voter turnout while controlling for all the other variables. A discriminant analysis was conducted as a next step in order to find out how well this model, as a whole, classified those who did cast a ballot and those who did not. The voter turnout variable was entered as the grouping variable, and all the variables used as predictors in regression function were entered together as independent variables. Results As Table 1 shows, some of the demographic variables such as race and education were significant predictors of young voter turnout until media use variables were introduced in the analysis. As was true in Simon’s study (1996) done among the wider range of age groups, the young people with more education were also more likely to vote (p<.01). Being white was initially a significant predictor of voter turnout (p<.01) when demographic variables were entered alone, but it was negatively associated with young voter turnout. In other words, white Americans aged 18 to 35 were less likely than non-Whites to cast a ballot on Election Day. But race became an insignificant predictor when other variables were introduced. None of the demographic variables predicted young voter turnout with statistical significance in regression 4, when all the variables were added to the equation. Interestingly, income, a significant predictor of voter turnout in Simon’s study (1996), did not predict young voter turnout with statistical significance even in regression 1, when the role of demographic variables was solely examined. The reason for this finding may be lack of variance in young people’s income levels. The majority of young people (73 percent) reported that their annual income was less than $35,000.

Authors: Kim, Eunsong.
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Young Voters and Media Use
12
impact of media use in explaining the variance in young voter turnout while controlling
for all the other variables.
A discriminant analysis was conducted as a next step in order to find out how
well this model, as a whole, classified those who did cast a ballot and those who did not.
The voter turnout variable was entered as the grouping variable, and all the variables
used as predictors in regression function were entered together as independent variables.
Results
As Table 1 shows, some of the demographic variables such as race and
education were significant predictors of young voter turnout until media use variables
were introduced in the analysis. As was true in Simon’s study (1996) done among the
wider range of age groups, the young people with more education were also more likely
to vote (p<.01). Being white was initially a significant predictor of voter turnout (p<.01)
when demographic variables were entered alone, but it was negatively associated with
young voter turnout. In other words, white Americans aged 18 to 35 were less likely
than non-Whites to cast a ballot on Election Day. But race became an insignificant
predictor when other variables were introduced. None of the demographic variables
predicted young voter turnout with statistical significance in regression 4, when all the
variables were added to the equation. Interestingly, income, a significant predictor of
voter turnout in Simon’s study (1996), did not predict young voter turnout with
statistical significance even in regression 1, when the role of demographic variables was
solely examined. The reason for this finding may be lack of variance in young people’s
income levels. The majority of young people (73 percent) reported that their annual
income was less than $35,000.


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