Validity Behind Stereotypes: Analysis of Perceptions on the Death Penalty & Immigration
Introduction
I was intrigued by the prevailing stereotypes concerning Americans and aimed to investigate their validity and extent. Utilizing data from the 2021 General Social Survey (GSS), I explored perceptions of the death penalty (V1) and the necessity of limiting immigration to preserve the American way of life (V2). The GSS is an annual national survey conducted by the National Opinion Research Center (NORC) at the University of Chicago, offering valuable insights into contemporary American society and tracking trends in opinions, attitudes, and behaviors.
Summary of Findings
Regarding the death penalty (V1), native-born Americans, conservatives, Republicans, those with a college education, and Trump voters were more likely to support it. Older individuals (50 years and older) also favored the death penalty. As for attitudes toward limiting immigration, US-born participants were more likely to oppose it. Political leanings, education, race, and age played a role in shaping opinions, with liberals strongly opposing limits and conservatives strongly supporting them. Geographic location, religion, and marital status also influenced immigration attitudes.
Our first hypothesis, unhappy older males who voted for Trump are likelier to favor the death penalty, was statistically validated and proven accurate. The second hypothesis that individuals who strongly favor limiting immigration are primarily Christian or Catholic white conservatives who own guns and businesses was partially supported by the findings showing that older individuals identifying as Christian and maintaining conservative political views were more likely to advocate for restricted immigration.
Study Implications
These findings carry substantial policy significance, particularly in criminal justice and immigration reform. Policymakers should consider the influences of religious and political affiliations, education, age, and marital status when crafting policies related to the death penalty and immigration. By devising targeted and strategic public education campaigns, it is possible to engage specific demographic profiles, encouraging reform to abolish the death penalty and fostering support for diversity through immigration reform.
Summary of the Viewpoints & the Participants’ Characteristics
The study involved 1,016 observations (obs), with 53% (n=541) supporting the death penalty and 47% (n=475) opposing it. Views on immigration limits were divided: 43% (n=437) strongly disagreed, 34% (n=342) strongly agreed, and 23% were neutral. The participants were predominantly White (81%, n=827), with a near-even gender split (46% male, n=470; 54% female, n=546) and an average age of 56. They exhibited diverse political affiliations, leaning slightly liberal (39%, n=397) and Democratic (42%, n=429). Most participants were married (53%, n=539), US-born (95%, n=963), and employed by someone else (89%, n=906). They were generally happy (62%, n=634) and geographically dispersed across the US.
The sample primarily identified as Protestant (44%, n=451) and held at least a bachelor's degree (53%, n=534). Income disparities were significant, with 31% (n=319) reporting no income. A large segment was from the South (38%, n=386). Most had neighbors of the opposite race (82%, n=846) and did not own a gun (58%, n=593). Regarding national spending to address rising crime rates, 64% (n=430) believed it was too little, 27% (n=183) considered it about right, and 8% (n=56) found it excessive.
Relationship between Participants’ Characteristics & Viewpoints
Comparing the respective viewpoints with the participants’ characteristics revealed intriguing patterns across various demographic and contextual factors. Regarding the death penalty, native-born Americans (n = 521) were more likely to support it than foreign-born residents (n = 20), with a statistically significant difference (chi2 = 5.40, df = 1, p < 0.05). However, no statistically significant difference was found between genders. Support for the death penalty was most prominent among conservatives (n = 259), Republicans (n = 213), those with a college education (n = 282), and Trump voters (n = 289). Also, the opposition was highest among Clinton voters (n = 359). Older individuals (50 years and older) were more likely to favor the death penalty (chi2 = 18.71, df = 3, p < 0.001), and Southerners had the highest representation of proponents (n = 223).
Regarding attitudes towards limiting immigration, similarly, no noticeable difference was found between genders. US-born participants were more likely to oppose limiting immigration (n = 407), while those who lived with neighbors of the opposite race were more likely to strongly oppose it (n = 375, chi2 = 6.90, df = 2, p < 0.05). Gun ownership (n = 189, chi2 = 43.85, df = 4, p < 0.001), political leanings, education, race, and age all played a role in shaping opinions on immigration limits, with liberals (n = 288) strongly opposing limits and conservatives (n = 206) strongly supporting them (chi2 = 295.73, df = 4, p < 0.001). Whites were the most strongly opposed (n = 355) and the most strongly supportive of immigration limits (n = 294, chi2 = 13.56, df = 4, p < 0.01). Geographic location, religion, and marital status also influenced immigration attitudes (p < 0.001).
The findings carry crucial implications for policy formulation. Recognizing the demographic factors and attitudes associated with support for the death penalty can help policymakers tailor their messaging and advocacy efforts. Additionally, understanding the intersection of political leanings, happiness, age, and regional differences offers a more nuanced perspective on the death penalty debate, informing more effective policy strategies. Likewise, the complex interplay between demographic and contextual factors in shaping attitudes toward immigration policy is noteworthy. Policymakers should consider the diversity of opinions and the influence of political leanings, education, race, and age when designing and implementing immigration policies. By considering these aspects, they can ensure that policies address the concerns and needs of various population groups in a more comprehensive and targeted manner.
Binary Logistic Regression Analysis
After addressing data anomalies, logistic analysis was employed, presenting both a logit model and an ordinal logit model. These models are detailed in Appendix A, with a summary of the data processing and resulting variables in Appendix B. To evaluate my first hypothesis, I employed logistic analysis to identify the factors significantly influencing attitudes toward capital punishment. I developed a binary logistic regression model with two classifications: 'yes' or 'no,' transforming the original variable, cappun, to assume values of '0' and '1.' The independent variables considered included sex, age, religion, income, political views, party affiliation, educational years, marital status, number of children, country of birth, 2016 presidential vote, perception of public spending on crime, happiness level, and region.
I maintained the number of children as a continuous variable while representing ordinal and nominal variables using dummy variables. For a categorical variable consisting of 'k' categories, I generated 'k-1' dummy variables and incorporated them into the model. Table 1.1 in Appendix A displays the overall model (chi2 = 224.37, p < 0.001). The analysis utilized 660 observations and yielded a significant pseudo R-squared value of 0.25, suggesting that the chosen model effectively explains capital punishment's dependent variable. To further investigate the estimated coefficients of individual categories, I created Model 2 based on variables that were statistically significant at the 5% level – age (mature adult – aged 50 to 64) (p < 0.01), political views (moderate and conservative) (p < 0.001), voted for Trump (p < 0.001), and unhappy (p < 0.01).
The results indicate that being middle-aged, having lower education levels, being a Trump supporter, having a lower income, and being divorced or never married were significantly associated with a greater likelihood of supporting the death penalty. Conversely, being female, being born in the United States, being pretty happy or not too happy, and residing in certain regions were not significantly associated with the dependent variable. Consequently, my hypothesis that unhappy (significant), older males (significant) who voted for Trump (significant) are more likely to favor the death penalty is statistically validated and proven to be accurate.
Ordinal Logistic Regression Analysis
To discern the factors influencing views on limiting immigration, I developed an ordinal logistic regression model with three classifications, combining the original five categories into "strongly disagree," "neutral," and "strongly agree." The independent variables considered were sex, age, race, religion, political view, educational years, gun ownership, income, marital status, self-employed, and whether their neighbor is of a different ethnicity and region. Table 2.1 in Appendix A displays the overall model (chi2 = 455.07, p < 0.001), indicating that the selected model effectively explains the dependent variable, limiting immigration. The analysis aimed to identify the characteristics of individuals who favor limiting immigration.
The significant findings correspond to variables with p-values less than 0.05. There is a higher likelihood that older adults (middle-aged adults, mature adults, and older adults) favor limiting immigration. Conservatives and moderates are more inclined to support immigration restrictions. The probability of supporting immigration limits is lower among those with higher education levels, such as bachelor's or advanced degrees. Additionally, individuals identifying as Catholic or Christian are less likely to support limiting immigration, whereas those with no religious affiliation exhibit greater support. Higher-income individuals, including those in high and very high-income brackets, are more likely to favor limiting immigration. Divorced individuals are more likely to support immigration restrictions, while never-married individuals are less likely.
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