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FINAL PAPER

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FINAL PAPER

  1. 1. 1 0999451 Dr. D. Fleming PSC-150-02 November 24, 2015 Word Count: 4150 An Analysis of How Political Awareness and Education Affects Patriotism Abstract This study examines how political awareness and level of education affects patriotism and political participation. I conducted the research using an American National Election Studies (ANES) post-election questionnaire from 2012 by analyzing frequencies, descriptives, correlations, and bivariate linear regressions. I controlled for three variables: race, party identification, and veteran status. After analyzing the results, there was a statistically significant negative correlation between education and patriotism that allowed me to reject the null hypothesis. There was no correlation between political awareness and patriotism, so the null hypothesis failed to be rejected. There was also a positive, statistically significant correlation between education and participation, and awareness and participation. Introduction For years, researchers have attempted to evaluate patriotism many different ways (Pangle 1985; Schatz, Staub, Lavine 1999; Callan 2003; Huddy and Khatib 2007; Richey 2011; Straughn and Andriot 2011; Schildkraut 2014). Historically, patriotism in its most raw form can be defined as “readiness…for awesome sacrifice,” “love of country,” and “good citizenship” (Pangle 1985, 30; Straughn and Andriot 2011, 556). In the American
  2. 2. 2 context, this form of basic patriotism may be described as Americanism, or maximizing opportunities as an American to better oneself, and consequently to better society (Pangle 1985, 30; Schildkraut 2014, 448). This existing research, however, does not explain how or why people might have differing levels of patriotism or Americanism. My research seeks to find some possible explanations. Literature Review Americans are continually evolving patriotism into so much more than just love for one’s country. First, it can be divided into two dimensions, blind patriotism and constructive patriotism. The former is experienced by disengaged citizens with “unquestioning loyalty to the nation” while the latter is “characterized by support for questioning and criticism of current group practices that are intended to result in positive change” (Schatz 1999, 1047). Patriotism can even be further divided into categories such as civic participation, such as voting, membership in government, and attendance at government meetings; social identity, as in one’s feelings and intrinsic values as an American citizen; and national attachment, or level of devotion to America and its government, laws, and cultures (Richey 2011, Straughn and Andriot 2011, Huddy and Khatib 2007). Individually, these studies on individual components of patriotism might help one better grasp an understanding of American citizenship from multiple angles, but do not provide a holistic interpretation. Additionally, these studies do not solely use patriotism as the dependent variable. Some researchers, such as Richey (2011) and Straughn and Andriot (2011), use political participation as the independent variable to study its effects on patriotism. Huddy and Khatib (2007), on the other hand, find that Americans who
  3. 3. 3 claim to feel a strong sense of patriotism, the independent variable, are more politically active than those who identify as less patriotic, with political activity as the dependent variable. My study aims to evaluate patriotism as the dependent variable in a more holistic manner in order to isolate and control the independent variables, education and political awareness. While Straughn and Andriot’s (2011) and Huddy and Khatib’s (2007) research provides insight on an effect of love for one’s country, civic participation and patriotism should be evaluated as a component of patriotism. Combining the two variables is plausible because political awareness, the independent variable of my study, induces feelings of reciprocity (Richey, 1047). As a result of heightened awareness, citizens can better appreciate what society provides them and, consequently, make efforts to give back. This increases political involvement, and transitively, patriotism (Richey 2011). Moreover, people who were more politically active possessed higher levels of constructive patriotism (Richey 2011). This can be attributed to the fact that people who are politically active feel that they can change and improve society by civic participation, further providing that patriotism can be evaluated by political involvement (Richey 2011). These findings can be beneficial to my study because if I find that political awareness increases civic participation, I can then conclude that political awareness increases patriotism. Education levels also have clear affects on different aspects of patriotism (Straughn and Andriot 2011, Callan 2004, Schatz 1999). The constructive versus blind categorical approach of understanding patriotism helps us to understand the relationship between education and patriotism. One might conclude that those with higher education
  4. 4. 4 are much more understanding of the nation’s politics and can therefore be both appreciative and critical. Similarly, those with lower levels of education might be less politically engaged, misperceive foreign threats, and be selective with pro-United States news and information (Schatz 1999, 151). Huddy and Khatib (2007, 72) refute this research by providing that national attachment actually lessens with years of education. Their study states that well-educated Americans are more politically active, but show weaker levels of national attachment than those who are less educated. A cause for this negative correlation might be attributed to the decline in civic education in schools (Callan 2004). Instead of teaching and promoting love for one’s country and discussing citizens’ rights and responsibilities, government classes tend to analyze and describe politics as an abstract doctrine rather than personal commodity. However, schools also do tend to increase pride and attachment to a specific community or society, rather than land within specific borders; so one can still be patriotic by loving the American community without having a strong national attachment to the government and its procedures (Straughn and Andriot 2011, 557; Callan 2004). By making patriotism the dependent variable, my research will benefit previous findings where patriotism was the independent variable by providing greater background information. My study will tell researchers why people may or may not be patriotic, and they can then apply that to their studies to further elaborate on their data. For example, Huddy and Khatib (2007) found a positive correlation between patriotism and political activity.
  5. 5. 5 Hypothesis My research will supplement existing research by providing background information that shows how and why people identify themselves as patriotic. This additional information will provide greater insight and more detail on others’ conclusions. The null hypothesis for this research question is that education and political awareness have no affect on patriotism and participation. Based on the existing information, I predict that there is a positive relationship between patriotism and political participation. This is because people who love their country will want to have a say in its politics, and those who regularly participate in its politics feel a stronger connection to the nation. Furthermore, I hypothesize that in a comparison of American adults, those who are more politically aware will identify as more patriotic and be more politically active than those who are less politically aware. Additionally, those with higher levels of education will also identify as more patriotic and be more politically active than those with lower levels of education. Data and Methods To conduct the research, I analyzed an American National Election Studies (ANES) post-election questionnaire from 2012 with 5,916 responses (a 38% response rate) received within two months after the 2012 election. In the tables below, N is the population, or number of responses for that particular variable. This survey asked respondents a wide range of topics including their level of political awareness, participation, and love for one’s country. To determine political awareness, I created an index composed of five different dichotomous variables (respondents answered either yes or no). The five categories asked if respondents regularly watch political television, listen
  6. 6. 6 to political radio, read about politics in newspapers or magazines, read about politics online, and visit political candidates’ websites during election times. The mean score was the average number of items that respondents answered yes to doing regularly. This was a sufficient way to gauge people’s interest in, and pre-existing knowledge of, politics. The more of these things respondents reported doing, the higher level of political awareness they possessed. To determine education level, respondents were asked to identify the highest level of education they have received. Education was measured using an ordinal level of precision. Code Grade 1 1-6 2 7-8 3 9 4 10 5 11 6 12 (no diploma) 7 High School Diploma 8 Some College 9 College Degree 10 Graduate Degree In order to better organize the data and reduce the number of categories, I combined grades 1-6 (elementary school), 7-8 (middle school), four years of college, and different types of graduate degrees. I also had to ensure that the data was ordered properly so the least amount of education was 1, and increased accordingly. The main dependent variable in my study was patriotism. Like awareness, patriotism was measured as an index. The index consisted of three ordinal categories: emotions seeing the American flag, love of country, and importance of being an American. The categories were measured on a scale from one to five.
  7. 7. 7 Level Meaning 1 Hate It/Not Important 2 Dislike It/Somewhat Important 3 Passive 4 Like It/Very Important 5 Love It/Extremely Important For emotions seeing the American flag and important being an American, I rearranged the variables in order to make one be the most negative emotions and five be the most positive. The mean score of this index is the average score that respondents gave to the three questions. Because my study intended to group participation and patriotism into one category, I created a separate political participation index to see if there was a correlation between the two indexes. The participation index was made up of six dichotomous categories (respondents answered yes or no)—in the past twelve months, has the respondent: attended a political meeting or rally, donated money to a political campaign, contacted a government official to express a concern, done community work, attended a school board or community meeting, and voted for president. Those who preferred not to answer or selected “Don’t Know” or “Other” were labeled as missing. This study contained three control variables that might have had an affect on the results: race, political party affiliation, and veteran status. For race, respondents were asked to select white, black or African American, American Indian or Alaskan Native, or Asian or Pacific Islander. The original survey asked race as one nominal variable. In order to better analyze the results, I converted race into four dichotomous variables. For those who selected “other” and “prefer not to answer,” I listed them as missing data. The mean for each race is the percentage of people who answered “yes” to being that race.
  8. 8. 8 Similarly for party affiliation, respondents were asked what political party they were registered with. Their options were originally measured using a nominal level of precision and could select Democrat, Republican, Independent/other, or prefer not to answer. The first three were converted into dichotomous variables, and those who preferred not to answer were considered missing. Like race, the mean is the percentage of people who answered “yes” to affiliating with that party. Lastly, veteran status, a dichotomous variable, allowed me to determine what percentage of respondents were veterans. The mean is the percentage of people who are veterans. I conducted five bivariate analyses in attempt to find relationships between my variables. I used the correlation method because the independent and dependent variables were either interval or ordinal with many categories. In order to determine statistical significance while attempting to reduce any type-1 errors, I used an alpha-level of 0.05. For significance levels below .05, I was able to confidently reject the null hypothesis and determine that the relationship was, in fact, statistically significant. In the tables below, significance levels marked with an asterix (*) were statistically significant. In order to determine the strength of the correlation, I examined the Pearson’s R score, which ranged from -1 (perfectly negative correlation) to 1 (perfectly positive correlation). The first correlation was between the political participation and patriotism indexes. The second correlation was between education and patriotism index. The third correlation compared the awareness index to the patriotism index. The fourth correlation was a comparison of education and political participation. The fifth and final correlation was between participation index and awareness index. For the five correlations, I evaluated Pearson’s R (range: -1, 1) to determine the strength of the correlation
  9. 9. 9 Lastly, I performed two bivariate linear regressions to determine an exact relationship between my independent variables and dependent variables. The regressions told me the amount of change in the dependent variables caused by one unit of change in the independent variables. This allowed me to easily account for the influence that the control variables have on the dependent variables. The first regression analyzed patriotism while the second looked at political participation. Both regressions used Race: White, Party Affiliation: Republican, and Veteran Status: No as the reference categories. I performed a bivariate linear regression as opposed to a logistical regression because my independent variables were ordinal (education) and dichotomous (awareness index) and my dependent variables were ordinal with many categories (patriotism index) and dichotomous (political participation). Analysis and Results Table 1: Descriptive Statistics N Minimum Maximum Mean Median Mode Education 5160 1.00 10.00 7.76 8.00 7.00 Awareness Index 4534 1.00 5.00 2.55 3.00 3.00 Patriotism Index 5453 1.00 5.00 3.22 3.33 3.67 Participation Index 5494 1.00 6.00 1.65 1.00 1.00 The first independent variable, education, was measured using an ordinal level of precision. The mean, or average level of education of survey respondents, was 7.76 (between graduating high school and attending college for some amount of time). The mode, or the most common education level, was 7.00 (high school diploma). The median, or central education level, was 8.00 (some college). Because the mean was less than the median, there was a negative skew. This occurred because the median only looked at the
  10. 10. 10 middle 50% of respondents while the mean factored in all variables, including any outliers. The second independent variable was political awareness. This variable was an index composed of five different dichotomous variables (respondents answered either yes or no). The five categories asked if respondents regularly watch political television, listen to political radio, read about politics in newspapers or magazines, read about politics online, and visit political candidates’ websites during election times. According to the data, the average number of political awareness factors that respondents took part in was 2.55. This meant that the average number of political awareness activities that respondents answered yes to partaking in was 2.55 out of the five available options. Both the median and mode were 3. Again, there is a positive skew. The main dependent variable in my study is patriotism. Like awareness, patriotism was measured as an index. The index consisted of three ordinal categories: emotions seeing the American flag, love of country, and importance of being an American. The categories were measured on a scale from 1 to 5, with 1 being the worst and 5 being the best. This meant that the average score respondents gave to the three questions of the index was a 3.22 out of five. The mean score for these three categories combined was 3.22. The median was 3.33 and the mode was 3.67. Again, this was a negative skew because the mean was less than the median. This study contained three control variables: race, political party affiliation, and veteran status. For race, respondents were asked to select white, black or African American, American Indian or Alaskan Native, or Asian or Pacific Islander. Since these were dichotomous variables, the mean represented the percentage of people who
  11. 11. 11 answered yes to being that race. 82% of respondents selected white, 15% Black or African American, .8% American Indian or Alaska Native, and 2.1% Asian or Pacific Islander (Table 2). Table 2: Control Variable Descriptives and Frequencies N No Yes Mean Republican 5595 4206 1389 0.25 Democrat 5595 3234 2361 0.42 Independent/Other 5561 3750 1911 0.34 Veteran Status 5914 5135 775 0.131 White 5914 670 3018 .82 Black/African American 5914 3123 565 0.15 American Indian or Alaskan Native 5914 3660 28 0.008 Asian or Pacific Islander 5914 3611 77 .021 For party affiliation (Table 2), respondents chose from Republican, Democrat, or Independent/Other. Like race, these were dichotomous variables so the mean represented the percentage of those who identify as that race. According to the data, 25% affiliated with the Republican Party, 42% with the Democratic Party, and 34% claimed to be either Independent or another political party not listed. Lastly, for veteran status, a dichotomous variable, the mean, 0.131, represented the percentage, 13.1%, of respondents who answered yes to being a veteran. I conducted five bivariate analyses in attempt to find relationships between my variables. I used the correlation method because the independent and dependent variables are either interval or ordinal with many categories.
  12. 12. 12 Patriotism Index vs. Participation Index Correlation ParticipationIndex PatriotismIndex Pearson’s R Significance .033 .016 The table above shows a .033 correlation, with an alpha level of .016, making the small, but present positive correlation statistically significant. This allowed me to conclude that participation can, in fact, be considered a form of patriotism. Table 3: Education vs. Patriotism Index Correlation PatriotismIndex Education Pearson’s R Significance -.096 .000* *=Statistically significant; Reject null hypothesis The second correlation was between education and patriotism index. The results, seen in Table 3, show a statistically significant -.096 correlation. This told me that as education level increases, patriotism decreases. Table 4: Awareness Index vs. Patriotism Index Correlation PatriotismIndex AwarenessIndex Pearson’s R Significance .004 .778 The third correlation, comparing awareness index to patriotism index, shows a .004 correlation, meaning as awareness increases, patriotism slightly increases as well (Table 4). However, since the significance level was .778, much greater than my established alpha level of .05, results were not statistically significant and I would fail to reject the null hypothesis. Based on these results, I concluded that there is no relationship between awareness and patriotism.
  13. 13. 13 Table 5: Education vs. Participation Index Correlation ParticipationIndex Education Pearson’s R Significance .274 .000* *=Statistically significant; Reject null hypothesis The fourth correlation was a comparison of education and political participation (Table 5). This calculation yielded a .274 correlation that is statistically significant, meaning as education increased, political participation increased as well. Table 6: Control Variable Descriptives and Frequencies AwarenessIndex AwarenessIndex Pearson’s R Significance .452 .000* *=Statistically significant; Reject null hypothesis The final correlation was between participation index and awareness index (Table 6). Due to the statistically significant .452 correlation, I rejected the null hypothesis and concluded that as participation increases, so does political awareness. Table 7: Multivariate Linear Regression-Patriotism Index Beta Coefficient Significance Level Constant 3.661 .000* Education* -.041 .000* Awareness Index .012 .105 Black .009 .729 American Indian or Alaskan Native 0.00 1.000 Asian or Pacific Islander -.058 .353 Veteran Status* .100 .000* Democrat* -.244 .000* Independent -.228 .000* N=2894; R2=.060; *=Statistically significant, Reject null hypothesis The first bivariate linear regression sought to find the exact relationship that the independent and control variables have on patriotism. The adjusted R2, .060, showed that the independent and control variables explained 6% of the total variation of patriotism.
  14. 14. 14 Since education, one of the independent variables, was ordinal with no “zero level,” I could not interpret the constant because respondents did not have an option to say they had no education. Controlling for all other variables: with every one point increase in education, the Predicted Patriotism Score (PPS) decreased by .041; with every one additional aspect of political awareness, the PPS increased by .012; Black people’s PPS were expected to be .009 points higher than that of white people’s; American Indians or Native Alaskans were expected to see no difference from white people; Asians or Pacific Islanders were expected to score -.058 points less than white people; veterans are expected to score .1 points higher than non-veterans; Democrats were expected to score .244 points lower than Republicans; and Independents or Others were expected to score .228 points less than Republicans. For the variables that were statistically significant, I rejected the null hypothesis that the independent variable had no effect on patriotism. Table 8: Multivariate Linear Regression-Participation Index Beta Coefficient Significance Level Constant -.226 .063 Education* .108 .000* Awareness Index* .453 .000* Race (Black)* .259 .000* Race (American Indian or Alaskan Native) -.302 .207 Race (Asian or Pacific Islander) -.283 .057 Veteran Status .057 .360 Party Affl. (Democrat) .032 .576 Party Affl. (Independent/Other) -.095 .096 N=2908; R2=.25; *=Statistically significant, Reject null hypothesis The Adjusted R2 for the second regression is .25, meaning 25% of the variation of political participation was attributed to the independent variables. Similar to the first regression, the constant could not be interpreted because Education is measured
  15. 15. 15 ordinally. For every one level increase in education level, the expected participation score was expected to increase by .108. For every additional aspect of awareness, the expected score is expected to increase by .453. Black people are expected to score .259 points higher than White people, American Indians or Native Alaskans are expected to score .302 points less than White people, Asian or Pacific Islander were expected to score .283 points less than White people. Veterans were expected to score .057 points higher than non-veterans. Democrats were expected to score .032 points higher than Republicans. Lastly, Independents or others were expected to score .096 points less than Republicans. For the variables that were statistically significant, I rejected the null hypothesis that the independent variable had no effect on political participation. Conclusion For this study, I sought to find a relationship between patriotism and political participation and attempted to examine the effect that education and political awareness had on patriotism and participation. I analyzed frequencies, descriptives, correlations, and multivariate regressions to see if any significant relationships existed. According to the results of the bivariate and multivariate analyses, my hypothesis, that those with a higher education and those who are more politically aware will be more patriotic and more politically aware, is partially supported by the data. First of all, as awareness increased, political participation increased as well. With more knowledge, people might be more inclined to practice their civic duties. However, as education increased, patriotism actually decreased. This might be due to the fact that higher educational institutions focus more heavily on the shortcomings of America. This, perhaps, is due to the fact that schools tend to shy away from civics classes, and focus more on factual history (Callan
  16. 16. 16 2003). Another possible explanation as to why patriotism decreases and education increases is because a person with higher education is more in control of their finances and therefore rely less on the government safety net than somebody with less education. Furthermore, as education increased, so did political awareness. With that, one might transitively conclude that patriotism would decrease with political awareness, but there was no statistically significant data to support that. However, there was statistically significant data to conclude that greater political awareness increases participation. A possible reason for this discrepancy might be due to the fact that only 6% of patriotism and 25% of participation results were attributed to the variables I included in the study. These proportions might have increased if I took into account other control variables such as region, socioeconomic status, and separate public and private education levels. Future researchers might investigate these alternative variables. A second possible improvement for this study might be using better questions to determine the dependent and independent variables. For example, patriotism might have been better explained if I examined questions that asked respondents about their level of support for the military, if they have an American flag hanging at their place of residence, if they put their hand over their hearts when they say the Pledge of Allegiance, and if they say the pledge at all. This research serves previous studies on patriotism and participation because it provides them with background on how and why people might feel or act a certain way. My study also might be useful to those interested in studying or increasing civic participation and patriotism. The data provide future researchers with information on how demographics affect patriotism and participation. Future researchers who wish to study ways to improve these things can reference my study to determine the best way to go
  17. 17. 17 about doing so. My study provides them with the necessary information to target specific groups, races, political parties, and people with differing levels of education.
  18. 18. 18 Literature Cited Callan, Eamonn. 2003. “Citizenship And Education.” Annual Review of Political Science 7: 71–90. Huddy, Leonie, and Nadia Khatib. 2007. “American Patriotism, National Identity, and Political Involvement.” American Journal of Political Science 51(1): 63-77. Pangle, Thomas. 1985. “National Review.” National Review: 30–34. Richey, Sean. 2011. “Civic Engagement And Patriotism.” Social Science Quarterly 92(4): 1044–56. Schatz, Robert T., Ervin Staub, and Howard Lavine. 1999. “On the Varieties of National Attachment: Blind Versus Constructive Patriotism.” Political Psychology 20(1): 151-74. Schildkraut, Deborah J. 2014. “Boundaries Of American Identity: Evolving Understandings of ‘Us.’” Annual Review of Political Science 17: 441–60. Straughn, Jeremy Brooke, and Angie L. Andriot. 2011. “Education, Civic Patriotism, And Democratic Citizenship: Unpacking the Education Effect on Political Involvement1.” Sociological Forum 26(3): 556–80.

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