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Essay: The Death Penalty and the 2016 General Election

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  • Subject area(s): Politics essays
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  • Published: 30 January 2022*
  • File format: Text
  • Words: 1,342 (approx)
  • Number of pages: 6 (approx)
  • Tags: Death penalty essays

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The death penalty has long been a controversial issue of much debate among the American public. It has drawn support as well as opposition across the ideological spectrum, often resulting in contentious viewpoints. It is generally known that support or opposition to the death penalty aligns with ideological position. Unnever (2010) indicates that “conservatives are more willing to support capital punishment than liberals.” The question is whether ideological orientation will influence issue position, and thereby influence presidential vote. This paper will illustrate that people who opposed the death penalty were more likely to vote for Hillary Clinton in the 2016 General Election.
The independent variable in this hypothesis is an individual’s attitude toward the death penalty and is operationally defined as a person’s position on whether they support or oppose the death penalty. The dependent variable is the presidential vote and is operationally defined as the percentage of votes cast by respondents for Hillary Clinton or Donald Trump in the 2016 General Election. Furthermore, political ideology will be included as a control variable to determine if a spurious relationship exists and is defined as a respondent’s ideological identification of liberal, moderate, or conservative. These variables are valid measures of the hypothesis because they specifically identify a person’s support of or opposition to the death penalty and the presidential candidate they voted for in 2016. Therefore, the variables accurately represent and capture the intended concept of the hypothesis. Additionally, these variables are reliable measures because the conventional expectation is that liberals are more likely than conservatives to oppose the death penalty. As Silos-Rooney (2014) comments, “liberals argue that the death penalty is merely state-sponsored murder that violates the human right to life” and Jones (2016) notes that, “the ideological makeup of probable supporters of the two presumptive nominees largely reflects the views of the party bases they will represent in the November election.” This information shows that voters that oppose the death penalty are more likely to identify as liberal and vote for a democratic candidate, thus making these variables reliable measures for the hypothesis.
Original Frequency Distribution
Table 1 consists of two columns and two rows that illustrate the presidential vote cast by respondents that either favored or opposed the death penalty. The independent variable listed at the top of the table is the death penalty while the dependent variable on the left side of the table is the presidential vote. There is a clear distinction between the percentage of respondents that approve and oppose the death penalty for both candidates. As expected, respondents that voted for Hillary Clinton show a higher percentage of opposition to the death penalty at 76.0 percent. Additionally, the summary statistics for Table 1 generate a p-value of 0.00, which indicates that the null hypothesis can be rejected and that a statistically significant relationship exists between these two variables. Furthermore, the summary statistics include a Gamma coefficient of -0.64, which indicates that these two variables have a fairly strong but negative relationship. In other words, as the independent variable for Hillary Clinton voters increases, the independent variable for Donald Trump voters decreases. Although Table 1 demonstrates a relationship between the death penalty and presidential vote, the question is whether the relationship is causal or spurious.
Ideology as a Confounding Variable
Confounding variables influence both the independent and dependent variables, resulting in a distortion of the causal connection. Miller and Shanks (1996) indicate that, “… general ideological orientations influence voting”, so to investigate the possibility of a spurious relationship, ideology is included as a control variable. Ideology is recoded to consist of three categories: Liberal, Moderate, and Conservative. Table 2 consists of two columns and two rows that illustrate the presidential vote cast by liberal respondents that either favored or opposed the death penalty. The independent variable is listed at the top of the table and the dependent variable is listed on the left side of the table. The summary statistics for Table 2 generate a p-value of 0.00, which indicates that the null hypothesis can be rejected and that a relationship exists between these two variables. Additionally, the summary statistics include a Gamma coefficient of -0.59, which indicates that these variables have a negative relationship that is slightly weaker than in Table 1. The data show that as the independent variable for Hillary Clinton voters increases, the independent variable for Donald Trump voters decreases. When ideology is controlled, the independent variable percentages are much higher for Hillary Clinton at 95.4 percent. Furthermore, the approval percentage for the death penalty for Clinton voters also increase to 84.2 percent. Although these numbers are not significantly different, they indicate that liberals were more likely to vote for Hillary Clinton despite their position on the death penalty.
Table 3 consists of two columns and two rows that illustrate the presidential vote cast by moderate respondents that either favored or opposed the death penalty. The independent variable is listed at the top of the table and the dependent variable is listed on the left side of the table. The summary statistics for Table 3 generate a p-value of 0.00, which indicates that the null hypothesis can be rejected and that a relationship exists between the death penalty and presidential vote. Furthermore, the summary statistics include a Gamma coefficient of -0.36, which indicates that these variables have negative relationship, but one that is not as strong as the original relationship in Table 1. In following the same pattern, these data show that as the independent variable for Hillary Clinton voters increases, the independent variable for Donald Trump voters decreases. Table 3 shows that 75.7 percent of moderates who opposed the death penalty voted for Clinton, which continues to support the original hypothesis but it must be noted that the percentages hardly changed from the original 76.0 percent in Table 1. This shows that ideology did not have a significant effect on moderate voters.
Table 4 consists of two columns and two rows that illustrate the presidential vote cast by conservative respondents that either favored or opposed the death penalty. The independent variable is listed at the top of the table and the dependent variable is listed on the left side of the table. The summary statistics for Table 4 generate a p-value of 0.00, which indicates that the null hypothesis can be rejected and that a relationship exists between the two variables. Furthermore, the summary statistics include a Gamma coefficient of -0.48, which indicates that these variables have a negative relationship that is not as strong as the original relationship in Table-1. The percentages in Table 4 follow the same pattern where the independent variable for Clinton voters increases as the independent variable for Trump voters decreases. In this table, 35.4 percent of conservatives that opposed the death penalty voted for Hillary Clinton. This is only occurrence where opposition to the death penalty did not favor Hillary Clinton, and shows the effect of ideology on the presidential vote. As Table 4 illustrates, conservative voters were more likely to vote for Donald Trump despite their opposition to the death penalty.
Findings
The data in this research indicate that the death penalty and presidential vote have a spurious relationship when ideology is controlled. As Tables 2 and 4 illustrate, ideology greatly influences voting behavior. More conservatives that opposed the death penalty voted for Donald Trump and an almost an equal number of liberals that voted for Hillary Clinton supported and approved the death penalty. These findings disconfirm the original hypothesis because ideology clearly had a greater influence on the presidential vote than policy position in the 2016 election.
Conclusion
The purpose of this paper was to explore if people who opposed the death penalty were more likely to vote for Hillary Clinton in the 2016 General Election. Table 4 disconfirms this hypothesis when ideology is a controlled variable. Although each table had statistically significant relationship, the ideology variable decreased the Gamma coefficient in each table making the relationship weaker. The data in Tables 1-3 show a higher percentage of Clinton voters opposed the death penalty but Table 4 shows a higher percentage that voted for Trump. These data illustrate that ideology had a greater influence on the presidential vote in 2016 than voter position on the death penalty.
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