Journal of Political & Military Sociology

Knowledge of War and the War on Knowledge: What Affects One’s Decision to Support War?

Daniel Patten

McMurry University

Several scholars have referenced the US public’s lack of knowledge on foreign policy. Yet, many fewer studies have actually explored the impact of this supposed lack of awareness. This study examines the relationship between the media, knowledge held of war and military foreign policy, and attitudes towards war. Online survey data were collected from a four-year university located in a heavily militarized area. The findings suggest that having knowledge of Afghanistan and Iraq War facts negatively affected one’s decision to support war and was the strongest predictor of this decision. The media was not found to be a significant predictor impacting this knowledge when controlling for other variables. Political ideology and other related variables were found to be more influential regarding this knowledge. These findings imply that the public may be imprudently supporting war without proper exposure to the facts or without regard to reality. Future research is needed to investigate how knowledge of war is formulated.

 

 

Walter Lippmann once wrote, “All the world thinks of the United States today as an empire, except the people of the United States” (1927, 215). Much later, Roger Morris would write that American citizens are burdened by daily life and hardly even glance at issues abroad (1980). More recently, Andrew Bacevich wrote in his book Washington Rules that the public pays little attention to foreign policy: “It’s only when something especially egregious occurs—most commonly a botched war—that members of the public take notice, and even then only briefly” (2010, 23). Indeed, many researchers investigating public support for war have noted that the American general public knows very little about its country’s foreign policy (Lippmann 1955; Converse 1964; Erskine 1963; Edwards 1983; Sobel 1993).

However, despite decades of scholarly demonstration that the public is inattentive when it comes to foreign policy issues (Almond 1950; Rosenau 1961; Hughes 1978; Neuman et al. 1992), Jentleson has argued that the public is actually “pretty prudent” (1992; Jentleson and Britton 1998). In 1992, he analyzed public opinion data from eight different cases of US military interventions and showed that the public were more likely to support military action aimed at stopping aggression as opposed to affecting internal policy change. In 1998, he replicated his earlier research and also found that humanitarian intervention as a goal received a similar level of support as stopping aggression. Jentleson’s findings suggest that members of the public possess a moral reasoning about war—specifically, they tend to disagree with wars of aggression and believe that war should be reserved for defense or humanitarian reasons.

Kull, Ramsay, and Lewis (2003) concluded that the main culprit linked to Americans’ lack of knowledge concerning the Iraq War was the media. Thirty percent of the 8,634 respondents in their national survey had at least one of three misperceptions about the Iraq War. The number of misperceptions varied by news source, suggesting that some sources are more (mis)informative than others. Earlier, Putney and Middleton (1962) found that the media influenced the likelihood of whether individuals were pacifistic or militaristic through misinformation regarding nuclear war. Individuals were more likely to be militaristic if they had not read scientific information on nuclear war. By contrast, those who had read scientific information on nuclear war were more likely to be pacifistic, suggesting a media influence on their attitudes. Other researchers have highlighted legislation used to inhibit military awareness (Garson 2005), the mass conglomeration of media corporations and its control over politics (Arsenault and Castells 2008), and the self-preservation of the media through advertisers (LeCount and Wasburn 2009). All of these factors can contribute to a structure of media misinformation.

The purpose of this study is twofold: to investigate the impact of the media on individuals’ “awareness level of military foreign policy” (AMFP) and the impact of AMFP on support for war. For the sake of clarity, AMFP conceptually encompasses two concepts: (1) knowledge of war (particularly that of the Afghanistan and Iraq Wars); and (2) knowledge of the size of the US military and government expenditure on it. I begin with a review of the relevant literature on effects of media, knowledge of war, and individual predispositions on support for war, as well as the theoretical framework of the current study.

The Impact of the Media

A number of theoretical approaches have been developed with respect to the role of the media in shaping attitudes. One important approach is the information updating model which contends that when “people are exposed to new, attitude-relevant information, they update their views accordingly” (Althaus and Coe 2011, 66).1 In contrast, Price’s (1989) social identification model argues that public opinion can change without access to new information; instead, it may change as a result of a subconsciously processed stimulus. For example, research has found that the more media coverage of a current foreign military action—regardless if the coverage was positive or negative—leads to an increase in support for war (Althaus and Coe 2011). Consistent with the information updating model, the current study suggests that when people learn more about war, they will update their views towards war accordingly. Clearly, the media play a very important role in this regard as a supplier of information. The current study explores the role that knowledge of war plays as a mediating variable between the media and support for war.

The argument that more media coverage of a military action leads to more support for it regardless of how that action is covered neglects the likelihood that media coverage will be disproportionately positive. Several reasons exist for this bias. First, the mass media must please advertisers (their clients and source of income), and their advertisers are more interested in maintaining the political status quo because it has provided the conditions for their success. In turn, the mass media as profit-based institutions succumb to heavy political pressures to deliver positive messages related to foreign policy (Harper and Yantek 2003). Second, LeCount and Wasburn (2009) demonstrated that positive media newscasts of the George W. Bush administration were more frequent after a terrorist threat had been issued. Third, the same Bush administration included journalists on the federal payroll in direct violation of “domestic propaganda laws” (Kornblut 2005). At least three journalists received payments from governmental departments which threatens their independence to be critical of the administration’s policies. In addition, a history of legislation in favor of information suppression along with governmental encouragement of misinformation have likely reduced the amount of information critical of the government.2 Fourth, several articles call attention to partnerships between news media and politicians (Arsenault and Castells 2008; 2006; Iskander 2005; Greenslade 2003).

According to the information updating model, when casualties are low, political consensus is high, and prospects of success are high, then support for war should increase. However, Althaus and Coe (2011) did not find this to be the case. Many facets are left unconsidered, all of which relate to the reliability of the information available to the public.

First, explicit mention of casualties reduces support for war (Eichenberg 2005). Mueller (1971) described a phenomenon called “rally-around-the-flag” which described the initial support for war; however, he documented a decline in support that later followed and attributed this diminution to American casualties rising. Burk (1999) called this phenomenon the “casualties hypothesis.” Consequently, the media may censor or downplay the true number of casualties. In fact, the Pew Research Center (2008a) in a survey asking about American casualties in Iraq found that the majority of respondents underestimated the number of casualties.3

Second, it almost goes without saying that the higher the prospects for a successful outcome of war, the more likely people will be to support it. The notion that the United States would tell the public that the country is entering a losing war but nonetheless must intervene is nonsensical. Nonetheless, studies have argued that support for war does not fluctuate as a function of American casualties, but instead does so according to the prospects of success (Feaver and Gelpi 2004; Gelpi, Feaver, and Reifler 2006), contrary to the casualties hypothesis. In other words, the likelihood of a successful outcome of war is more important than the number of casualties in garnering support for war. Yet, Eichenberg (2005) counters these critiques by comparing respondents’ support for US use of force over a multitude of surveys with regard to various US foreign interventions, ranging from Iraq to Panama. He found questions that did not mention casualties tended to receive higher levels of support.

Third, political consensus in support of war is likely to be displayed as high by the media for reasons discussed earlier in this section, such as the collusion between media and politicians and the economic incentive for the media to positively favor political agendas. In addition, various studies reveal that the public build an understanding of politicians through media coverage (Altheide 2002; Bennett 2003; Edelman 1988; Krosnick and Kinder 1990). For instance, elite discourse can be instrumental in determining support for war (Zaller 1992). Zaller argued that as political conversations in favor of a particular war became more numerous in the media, individuals sharing similar political proclivities would support the same, echoed position. Furthering this finding, Berinsky (2007) highlights the salience of consensus among politicians in the political arena by developing the elite cue theory, which states that people will look to prominent political figures in the media to guide their own positional decisions

Awareness Level of Military Foreign Policy (AMFP)

The media also affects the public’s levels of awareness of foreign military interventions. Kull et al. (2003) investigated the public’s misperceptions about the Iraq War and its relation to the media. They tested for three common misperceptions: (1) evidence of links between Iraq and al-Qaeda have been found; (2) weapons of mass destruction have been found in Iraq; (3) world public opinion favored the United States going to war with Iraq. Surprisingly, only 30 percent of respondents had no misperceptions (answered all three factual questions correctly).

Kull et al. (2003) also found that the amount of news watched was not related to the number of misperceptions held. Rather, the actual news source was the most important variable affecting misperceptions. For example, Fox News viewers were significantly more likely to be misinformed than CNN viewers. Not surprisingly, individuals who held misperceptions were far more supportive of the Iraq War, implying that the media may influence support for war via military awareness.

Other studies have found differences among news sources in viewers’ knowledge of political fact-based questions (Pew Research Center 2007; 2008b; 2010). Fox News is near the bottom in all of these studies, but some conservative news programs score better: The Rush Limbaugh Show, The Sean Hannity Show, and to a lesser extent The O’Reilly Factor. First, it is important to emphasize that the questions asked have little or nothing to do with the military or foreign policy.4 Second, a relatively large number of people answered some of these questions incorrectly regardless of news source.5

A similar study that investigated misinformation and public support for the Gulf War found that public opinion is not necessarily based in fact. Jhally et al. (1991) conducted a survey that showed strong support (84 percent) for the Gulf War while showing little awareness held by the respondents on issues pertaining to the war. For instance, only 13 percent correctly identified that the United States indicated it would take no action against an Iraqi invasion of Kuwait.6 Only two percent were aware of Saddam Hussein’s stated justification for invading Kuwait (Kuwait putting strain on the Iraqi economy by pushing down oil prices). By contrast, a large number of respondents (80 percent) were aware of certain facts such as Saddam using chemical weapons against Iran and his own population. The authors document a direct negative correlation between knowledge of war and support for war and conclude that the public is “selectively misinformed” (Jhally, et al. 1991, 50).

Several other studies have investigated the impact of learning information about war on levels of support for war. Putney and Middleton (1962) measured where participants fit on a militarism-pacifism scale before and after exposure to information on war not commonly found in the mass media. One group read Community of Fear by Harrison Brown and James Real. After reading this document, the readers’ knowledge related to nuclear weapons increased and 70 percent of the participants scored higher on pacifism. Another group attended lectures on war and international relations while also reading The Causes of World War III by C. Wright Mills. These participants increased their knowledge of war and nuclear weapons and 90 percent of them increased their score on pacifism. In a more recent, related study, Kowalewski (1994) tracked 25 students in his Conflict in International Affairs course to assess the effects of war knowledge on student pacifism. He found that students showed some greater signs of pacifism after being exposed to empirical facts from the peace studies literature. For instance, students were more likely to support peace studies organizations on campus, and oppose wars serving US interests and the jailing of war protesters. However, students actually grew more militaristic when exposed to war heroes. The pacification effect occurred in all students except those with prior military experience. In fact, students with military experience grew more bellicose by taking the course.

The media was not a central component of every study investigating the effects of knowledge of war. In Cohrs and Moschner’s (2002) survey research of 165 German students, they found that militaristic people tended to support the Kosovo War even, at times, in the face of antiwar facts. Participants’ belief in antiwar facts outweighed their certainty of the fact—that is, In other words, people who believed antiwar facts were less likely to support war regardless of how certain they were that the fact was true. Furthermore, how knowledgeable participants were about antiwar facts only strengthened pacifistic people to be more likely to reject the Kosovo War, whereas knowledge of war facts had no effect on militaristic people. Although Cohrs and Moschner use militarism-pacifism as a measure of the predisposition to be pro- or anti-war, the current study investigates if these “predispositions” are influenced by actual knowledge of war.

The Role of Predispositions

Although the information updating model suggests that individuals exposed to new information will change their views accordingly, predispositions to receiving information has been a common theme in much of the research. In an analysis of Gallup polls over a period of five decades and four wars, Boussios and Cole (2010) found political party to be the most influential factor impacting support for war among a series of demographic (race, gender, age, education, and religion) and ideological (political party, political ideology, hawk/dove, optimism/pessimism, and isolationism/internationalism) variables. In their study, political ideology was mostly subsumed by political party. Alternatively, other studies have shown conservatism to be directly related to stronger support for war (Agnew, et al. 2007; Grote, et al. 1997). In addition, Mueller (1973) showed that many members of the public rely on their political party as a heuristic to decide whether to support war or not. Given the data available, the current study investigates the role of predispositions primarily through political party affiliation and political ideology.

The various arguments suggesting the importance of predispositions towards war must be considered within Klein’s (2012) framework of a war culture—designed for exploring the cultural and ideological contributors to war that are present well in advance of any military action. According to Klein, elites via several neutralizing processes, of which the media is one, legitimate war as a feasible response for the public. In essence, elites foster an environment that is conducive to war, while the public operating within that social environment accept the militaristic culture and perpetuate it, resulting in widespread pro-war beliefs. Thus, most Americans are predisposed, through their socialization within the US culture of war, to harbor pro-war attitudes. In other words, top-down ideological domination is at work, but the public play an integral role in reinforcing the war culture. In Klein’s formulation, between the power elite and general public, ideological and meaning-producing institutions such as the media or schools act as an intermediary in establishing the culture of war.

Theoretical Framework of the Current Study

The current study builds primarily from the information updating model (Althaus and Coe 2011) and Klein’s (2012) culture of war. Since Klein demonstrates that Americans are bombarded by pro-war imagery and information from multiple socializing agents, they are likely to support war. To some degree, Klein’s propositions are congruous with the information updating model in that when people are exposed to information that is pro-war, they are more likely to support war. Furthermore, Klein emphasizes the media as an important agent in fostering the pro-war attitudes of individuals. The current study explores two particular relationships derived from these theoretical frameworks. First, how does the media impact AMFP? Based on both theoretical frameworks and various past research, it is likely that certain forms and types of media and time spent exposed to the media will impact one’s knowledge of war and the extent of US influence worldwide. Although Klein’s culture of war predicts mostly pro-war information on media, are there other types or forms of media that might allow one to achieve a higher level of knowledge? Second, another crucial question of this research asks if knowing more about war or having knowledge of the vastness of the US military affects an individual’s support for war. Given the recent findings that predispositions may outweigh the importance of information exposure, several other variables of individual characteristics are of importance, such as political party affiliation, political ideology, military affiliation, effects from terrorism, and affiliations with the Tea Party and Occupy Wall Street movements which were popular at the time of the study. Due to the importance of political party in Boussios and Cole’s (2010) study, the current study is particularly interested in its effect. The following section will outline the current study’s method and conclude with the hypotheses once the variables are operationalized.

Research Design

Setting and Sample

Data for this study were collected at a large east coast university in a military city in January/February 2012. Each day, all enrolled students receive student announcements via email. Students were invited to complete the survey via these student announcements (see Appendix A for full survey instrument). Convenience sampling was chosen because of the difficulty and lack of resources to conduct a random sample of the entire student population.7 Descriptive statistics of the sample are reported in the results section. The current study benefits from having a unique sample of about a 50/50 split between military personnel and civilians.

Procedure

An anonymous questionnaire was administered to anyone receiving the student announcements via email at an East Coast university. A link was posted in the student announcements explaining the study and asking students to participate. Therefore, every student registered at the university was a potential participant. The questionnaire was designed using Survey Monkey—a website/company established to help researchers design web-based surveys. Consent was given electronically. Participants were told that the survey was completely voluntary, that they had the right to refuse to answer any question, and at any time during the survey, they could choose to not continue. Once finished with the survey, participants were thanked for their time.8

Variables

Dependent variables. The components of awareness level of military foreign policy (AMFP) were analyzed as dependent variables as well as independent variables. The other dependent variable was support for war which was measured using the Cohrs et al. (2002) militarism-pacifism scale.9 For the current study, one minor amendment was made to the scale regarding the response options10. The Cronbach’s alpha for the Cohrs et al. militarism-pacifism scale in the current study was. 86 (N=329)11. The 10 items from the Cohrs et al. militarism-pacifism scale are listed in Appendix A (items 13–22). Other similar scales were considered before adopting the militarism-pacifism scale.12

Independent variables. AMFP is more of a concept than a variable. Within the concept of AMFP, multiple variables were used. However, for the purpose of this study, one of these variables was of particular interest. That variable was a scale designed specifically for this study that measures an individual’s level of awareness about war-specific facts pertaining to the Afghanistan and Iraq wars; this scale will be referred to as the Afghanistan and Iraq Wars Awareness Scale (AIWA). The AIWA scale attempts to measure one’s awareness of the wars in both Afghanistan and Iraq by asking the participants fact-based questions relating to the wars. Although the questions are fact-based, the items on the scale are not simple “yes” or “no” responses, instead 5-point Likert scale response varying from “strongly disagree” to “strongly agree” were utilized. A response of “disagree” has a semblance of uncertainty whereas a “strongly disagree” response is a more confident answer. This understanding of certainty was confirmed by students in a pretest.13 The coding was then designed so that individuals with a higher aggregate score were more aware of Afghanistan and Iraq war facts and a lower aggregate score signified a lower level of awareness.

Since the AIWA scale is only measuring fact-based knowledge of the wars in Afghanistan and Iraq, generalizing the findings to all war knowledge would be imprudent. A sample largely comprised of undergraduate college students was expected considering the method of recruiting subjects. Therefore, the assumption is that the wars in Afghanistan and Iraq are the only major wars occurring within their adult lifetime, which presumably has been relatively short. Most students at the ages of 18, 19, or 20 would likely not have extensive knowledge about wars that occurred before they were born. With these limitations in mind, the current study measures only the knowledge about the wars in Afghanistan and Iraq. The seven items consisting of the AIWA scale are listed in Appendix A (items 1–7) with a citation for each item to ensure the questions are fact-based. The Cronbach’s alpha for the AIWA scale was .73 (N=337).

The other component of AMFP is a series of five questions gauging respondents’ awareness of the American military’s vastness in expense and size globally. Each of these questions was treated as an individual variable and are listed in Appendix A (items 8–12) along with a citation as well. All questions are fact-based and a citation has been provided for each to confirm the correct response. These citations were not visible to the respondents. A “write-in” involves an open-ended question seeking a numerical response. The news source utilized by an individual is another independent variable measured. Respondents were given a list of various news sources and asked “from which news source do you get the majority of your news?”14 In addition, they were asked, “from which medium (i.e. television, radio, print, internet) do you get the majority of your news?” and “how much time do you spend a week watching/listening/reading the news regarding US foreign policy issues?”15

Control variables. Several variables have been found to have an impact on support for war and were controlled for in this study, including age, race, gender, political party and ideology, university major, and grade level.16 In addition, two questions pertaining to the participants’ military involvement were included.17 Lastly, two additional questions were added to control for the fear of terrorism and how affected someone was by 9/11.18

Hypotheses

Based on the theoretical framing of the information updating model (Althaus and Coe 2011), Klein’s (2012) culture of war concept, and the influence of predispositions, five hypotheses were tested.

Hypothesis one: Increases in an individual’s AIWA score will lead to increases in pacifism on the militarism-pacifism scale. Hypothesis two: Individuals who utilize a conservative news source as their primary news source will be more militaristic on the militarism-pacifism scale than individuals who access a liberal news source as their main new source, controlling for the other media variables. Hypothesis three: Individuals who utilize a conservative news source as their primary news source will have a lower AIWA score than individuals who access a liberal news source as their main new source, controlling for the other media variables. The fourth and fifth hypotheses are predicted based on the findings of predispositions. Hypothesis four: Individuals who identify themselves as Republicans will be more militaristic on the militarism-pacifism scale than individuals who identify themselves as Democrats or Independents. Hypothesis five: Individuals who identify themselves as Republicans will have a lower AIWA than individuals who identify themselves as Democrats or Independents.

Results

Descriptive Statistics

The descriptive statistics are listed in their entirety in Appendix B and C. However, the variables assessing war support and knowledge are most notable. Results on the Cohrs et al. (2002) militarism-pacifism scale ranged from 50 (most militaristic) to 10 (most pacifistic).19 The sample mean for militarism-pacifism score was 33.28 (sd=7.91) suggesting a slightly militaristic sample. Similarly, the AIWA scale ranged from 7 (most misinformed) to 21 (most uninformed) to 35 (most informed). The sample mean for AIWA score was 21.65 (sd=5.16) suggesting an overall uninformed sample. When asked about the number of United States foreign military bases, participants’ mean response was 211.82 (sd=271.92). The mean response for the amount of US dollars spent on the military annually (in billions) was 329.50 (sd=272.11).20 Respondents were also asked to report the percent of countries outside the United States that had US military troops present in them and the percent of the US discretionary budget spent on defense. The mean responses were respectively 43.20 (sd=27.90) and 40.82 (sd=21.97). Lastly, a majority of respondents (76.7%) believed that the United States spent more on its military than any other country in the world; the other respondents answered China (18.7%), Russia (3.8%), and United Kingdom (0.9%). Overall, the sample means for the second component of AMFP suggested the sample underestimated by a wide margin the size and scope of the US military.21

Multivariate Analyses

Multivariate linear regression analyses were conducted to determine if relationships continued to be significant even while controlling for other variables and factors. Table 1 displays the standardized beta coefficients for all variables potentially impacting one’s militarism-pacifism score.22 The variables related to the media were not found to be statistically significant when controlling for other variables and therefore were excluded from the models. All three of the models in Table 1 are statistically significant.

Table 1. Multivariate Linear Regression Models Predicting Militarism-Pacifism Score (N=281)

Variable Model 1 Model 2 Model 3
Age .013 (.042) .017 (.043) .005 (.038)
Grade –.081 (.347) –.082 (.345) –.028 (.304)
Race White .039 (.938) .054 (.948) .009 (.835)
Gender Male .054 (.823) .058 (.865) .085 (.757)
Family in Military .007 (.963) .010 (.964) –.018 (.845)
In Military .069 (.882) .056 (.882) .003 (.777)
Ideology Liberal –.405*** (1.270) –.404*** (1.286) –.296*** (1.144)
Ideology Moderate –.113 (1.000) –.097 (1.013) –.059 (.888)
Support OWS –.265*** (.334) –.271*** (.338) –.112* (.315)
Support Tea Party .131* (.414) .132* (.430) .064 (.380)
Percent Military Spending   –.116* (.019) –.114* (.017)
Percent US Troops   .028 (.015) .014 (.013)
Number of US Bases   –.044 (.001) –.016 (.001)
US Military Spending   –.097 (.002) –.041 (.001)
US Spends Most on Military   .039 (.964) .040 (.843)
AIWA Score     –.466*** (.080)
Model Adjusted R Square .391*** .399*** .541***
Model R Square Change   .019 .136***

Notes: numbers in table are standardized beta coefficients and (standard errors)

***significant at p<.001, **significant at p<.01, *significant at p<.05

Model one contains the demographic variables as well as some of the political variables [political ideology, support for the Occupy Wall Street (OWS) movement, and support for the Tea Party (TP)].23 Model one explained 39.1 percent of the variance in militarism-pacifism scores with three variables being statistically significant: (1) political ideology (liberals vs. conservatives); (2) support for the OWS; and (3) support of the TP. First, liberals scored .405 standard deviations lower on the militarism-pacifism scale compared to conservatives. Second, for every one standard deviation increase in support for the OWS, there is a .265 standard deviation decrease in militarism-pacifism score. Third, for every one standard deviation increase in support of the TP, there is a .131 standard deviation increase in militarism-pacifism score.

Model two included all the AMFP variables except AIWA. Model two explained an additional 1.9 percent of the variation in militarism-pacifism score, but this change was not statistically significant. All three of the previously statistically significant variables from model one maintained similar predictive power. Only one of the additional variables (percent of discretionary budget the participant thought was spent on the US military annually) was found to be statistically significant. For each standard deviation increase in percent of discretionary budget participant thought spent on the US military annually, there is a .116 standard deviation decrease in militarism-pacifism score.

Lastly, model three added AIWA score among the variables from model two. All OLS assumptions were met for this final model.24 Consistent with hypothesis one, model three predicted an additional 13.6 percent of the variation in militarism-pacifism score and the R-squared change was statistically significant. After adding the AIWA score, the percent thought to have been spent on the military maintained its predictive power while liberal ideology and support for the OWS lost some predictive power, and support for the TP lost its statistical significance. For every standard deviation increase in AIWA score, there is a .466 standard deviation decrease in militarism-pacifism score. Therefore, AIWA score was the strongest predictor in the model followed by liberal political ideology.

Several models were also considered to investigate which variables best predicted AIWA score. The standardized beta coefficient for each variable is presented in Table 2. Three models are included in Table 2 and each model was found to be statistically significant.25 Model one contains the same demographic and political variables found in model one of Table 1. It explained 31.1 percent of the variance in AIWA score with six statistically significant variables: (1) collegiate grade level; (2) gender; (3) whether the participant was ever in the US military; (4) political ideology (liberal vs. conservative); (5) support for the OWS; and (6) support for the TP. First, for each standard deviation increase in grade level, there is a .115 standard deviation increase in AIWA score. Second, males scored .118 standard deviations higher on the AIWA scale compared to females. Third, participants currently serving or ever having served in the US military scored .119 standard deviations lower on the AIWA scale compared to participants that were never in the US military. Fourth, liberals scored .215 standard deviations higher on the AIWA scale compared to conservatives. Fifth, for each one standard deviation increase in support of the OWS, there is a .262 ­standard ­deviation increase in AIWA score. Sixth, for each one standard ­deviation increase in support of the TP, there is a .222 standard deviation decrease in AIWA score.

Table 2. Multivariate Linear Regression Models Predicting AIWA Score (N=308)

Variable Model 1 Model 2 Model 3
Age –.013 (.028) –.016 (.027) –.025 (.027)
Grade .115* (.225) .126* (.220) .120* (.221)
Race White –.087 (.623) –.074 (.610) –.086 (.618)
Gender Male .118* (.547) .109* (.544) .077 (.564)
Family in Military –.048 (.577) –.021 (.637) –.033 (.640)
In Military –.119* (.882) –.073 (.573) –.072 (.576)
Ideology Liberal .215** (.831) .197** (.812) .201** (.813)
Ideology Moderate .085 (.659) .077 (.643) .086 (.165)
Support OWS .262*** (.220) .254*** (.215) .245*** (.219)
Support Tea Party –.222*** (.270) –.202** (.264) –.185** (.272)
Affected by 9/11 in Daily Life   –.212*** (.099) –.215*** (.099)
Secure from Terrorism   –.013 (.234) –.021 (.235)
News Source Liberal     .051 (1.184)
News Source Moderate     –.008 (1.064)
News Source Other     .047 (.914)
Time Spent Watching News     .106* (.175)
Model Adjusted R Square .311*** .346*** .351***
Model R Square Change .039*** .013

Notes: numbers in table are standardized beta coefficients and (standard errors)

***significant at p<.001, **significant at p<.01, *significant at p<.05

Model two added two variables (“how secure respondent felt from terrorism” and “how affected respondent felt by 9/11”) to the original variables found in model one. Model two explained an additional 3.9 percent of the variance in AIWA score and the R-squared change was statistically significant. Of the six statistically significant variables in model one, four variables (gender, liberal ideology, support of OWS, and support of TP) lost some of their predictive power, grade level gained some predictive power, and “being in the military” lost its statistical significance in model two. Of the two added variables, only “how much 9/11 had affected respondent’s daily life” was found to be a statistically significant predictor of AIWA. For each standard deviation increase in how affected by 9/11 a participant reported, there is a .212 standard deviation decrease in AIWA score.

Finally, model three included the news sources’ political orientation and time spent watching news variables in addition to the variables in model two. All OLS assumptions were met for this final model.26 Model three explained an additional 1.3 percent of the variation in AIWA score, but the R-squared change was not statistically significant. Of the variables statistically significant in model two, three variables lost some predicting power (grade level, support OWS, and support TP), two variables gained some predictive power (liberal ideology and 9/11 affecting participant’s daily life), and gender lost its statistical significance. Inconsistent with hypothesis three, none of the news source political orientation variables were statistically significant. The amount of time spent watching news pertaining to foreign policy issues was a statistically significant predictor of AIWA score. For each standard deviation increase in the amount of time spent watching news pertaining to foreign policy issues, there is a .106 standard deviation increase in AIWA score.

Discussion

The major focus of this study was to examine the impact of the media on awareness level of military foreign policy (AMFP) and AMFP’s impact on support for war (as measured by the Cohrs et al. (2002) militarism-pacifism scale). Five separate hypotheses were tested. Hypothesis one was the cornerstone of the current study, investigating whether more knowledge pertaining to military foreign policy issues (AMFP) would affect one’s support for war (as measured on the militarism-pacifism score). Partial support for this hypothesis was found. AMFP was divided into two major components: (1) the Afghanistan and Iraq Wars awareness (AIWA) scale measuring one’s knowledge of facts pertaining to the two wars; and (2) five questions testing the respondent’s knowledge on facts pertaining to the scale of the United States military and the influence of the US abroad. Component one, the AIWA scale, was strongly correlated with support for war and was found to be the strongest predictor of one’s decision to support war. The likelihood of supporting war decreased if the participant knew more about the two wars. This finding is consistent with the information updating model (Althaus and Coe 2011) that predicts that when an individual receives new information their beliefs and actions may change upon receiving the new information. It also suggests that even when immersed in a culture of war (Klein 2012), knowledge may be able to counteract a strongly militarized socialization process. For the second component of AMFP, only the percent of the discretionary budget the respondent thought was spent on military annually was weakly and negatively correlated with support for war.

Hypothesis two was partially supported. Hypothesis two predicted that individuals utilizing conservative news sources would be more likely to support war than individuals accessing liberal news sources. Bivariate analysis revealed that conservative news viewers were more likely to support war compared to all other news viewers, whereas liberal news viewers were the least likely to support war. After controlling for other variables, the political orientation of news sources failed to predict one’s decision to support war.

Hypothesis three was also partially supported. Hypothesis three predicted that individuals utilizing conservative news sources would have a lower AMFP compared to individuals utilizing liberal news sources. Bivariate analyses revealed that conservative news viewers scored lower on the AIWA scale than all other news viewers and liberal news viewers scored the highest. Once controlling for other variables, however, the impact of political orientation of news source disappeared. The second component of AMFP (awareness of the vastness of the US military) was not tested as a dependent variable in hypothesis three or five for several reasons. First, the items consisting of the second component of AMFP (the measures of US military vastness) were not inter-correlated as anticipated. Second, the descriptive statistics of AMFP revealed that the sample was highly uninformed or misinformed.

Media variables’ impact on AMFP were also explored. Type of news medium utilized was inconsequential in affecting support for war and AMFP. The amount of time participants spent watching news pertaining to foreign policy issues was not correlated with the likelihood of supporting war, but was weakly and positively correlated with AIWA. Time spent watching news remained a significant predictor of AIWA score even after controlling for other variables. The other component of AMFP did not correlate as expected with time spent watching news.27

Hypothesis four stated that Republicans will be more likely to support war compared to Democrats, and it was also partially supported. Based on bivariate analyses, Republicans were more likely to support war compared to all other political party preferences and Democrats were more likely to oppose war compared to all other political party preferences. Political party was excluded from the multivariate models because it did not prove to be a significant predictor of support for war after controlling for other variables. Furthermore, political ideology proved to be a better predictor of support for war28. This finding is inconsistent with Boussios and Cole’s (2010) finding that political party was the most important predictor of one’s support for war—even to a greater degree than political ideology. Political ideology was moderately correlated with support for war. The more liberal a respondent reported being, the more likely he/she was to oppose war. Political ideology was also the second strongest predictor of one’s decision to support war after controlling for other variables. Political predispositions appear to play a major role in supporting or opposing war.

Hypothesis five stated that Republicans will have a lower AMFP compared to Democrats. It was partially supported. In the bivariate analyses, Republicans scored lower on the AIWA compared to all other political party preferences and Democrats scored higher on the AIWA compared to all other political party preferences except the “other” group. Political party was excluded from the multivariate models (as it was for hypothesis four) because it did not prove to be a significant predictor of support for war after controlling for other variables. Also as before, political ideology demonstrated to be a better predictor of AMFP (at least the AIWA score). Political ideology was moderately correlated with AIWA score. The more liberal a respondent was, the more aware they were of Afghanistan and Iraq war facts. Political ideology was the third strongest predictor of one’s AIWA score after controlling for other variables. Given that political ideology was a stronger predictor of support for war than AIWA, having more knowledge about war may be important in successfully challenging one’s preconceived notions.

Several other un-hypothesized findings are notable. First, individuals with family or a significant other in the US military as well as those previously in the US military were found to be less aware of war facts than individuals with no social affiliation with the military. Moreover, individuals who have themselves served or currently are serving in the US military are also less aware of war facts compared to individuals never having served in the military. Two potential explanations arise from these findings. First, the US military may purposely withhold information or misinform its personnel. A second more plausible explanation is that US military members seek out only information that reaffirms beliefs congruent with a suitable mental state to perform their duty and disregard contradicting information. In other words, as a psychological defense mechanism, individuals who are actively or have been actively participating in war must rationalize to themselves that their participation was just and moral. This finding and the latter explanation is in line with Kowalewski’s (1994) findings.

Second, being a self-labeled supporter or one who opposes either the OWS or the TP is related to the knowledge one has of war facts and their likelihood to support or oppose war. Support for OWS was correlated with more war knowledge and a lower likelihood to support war, whereas support for the TP was correlated with the opposite outcomes.29 Support for OWS or the TP seemingly acted as a polarized political ideology variable where extreme liberals sided with OWS and extreme conservatives with the TP, resulting in very different outcomes of war fact knowledge. In this sense, group membership, especially when it is extremely polarizing, appears to heavily influence what information is obtained and believed.

Third, participants self-rated on a scale (ranging from 1 to 10) how affected their daily lives were by 9/11. Correlative analyses revealed that the more affected a participant was, the less aware he/she was of war facts and the higher likelihood of supporting war. The 9/11 effect on daily life was the second strongest predictor of war fact knowledge when controlling for other variables. The 9/11 effect was explained by other variables when predicting support for war. The 9/11 effect was a self-report measure and not necessarily of the participant’s reality. Using this measure, the 9/11 effect may be measuring a component of dangerous world beliefs (DWB) measured by previous researchers (see Duckitt 2001, 2006; Duckitt et al. 2002).30 People adhering to DWB fear the world as a dangerous place full of malevolence. In the case of the 9/11 effect, these individuals who reported being highly affected may view the post-9/11 world as more dangerous than before. The 9/11 effect aligns well with Klein’s (2012) culture of war. Klein describes the importance of socialized emotions in creating a culture of war, and one of those central emotions is fear, often stemming from our enemies. Future researchers should investigate the role that fear and collective enemies have on influencing knowledge of war and thereby support for war.

A non-random university sample was used in the current state and therefore limits its generalizability. Previous research has shown a divergence between the general public’s and students’ rationale for opposing war (Schuman 2003). Student populations were documented as opposing war on moral grounds, whereas the general public opposed war on pragmatic grounds. The AIWA scale asked many questions that pertained to morality. Therefore, a high AIWA score may be more predictive of opposition to war among student populations compared to the general public. Future research may be interested in adding pragmatic items to the AIWA scale to investigate their impact on support of war. Despite this limitation, the current study has produced a reliable scale for measuring war fact knowledge of the Afghanistan and Iraq Wars that can be utilized or expanded in a national, random sample.

Conclusion

Researchers have spent many years studying the factors influencing decisions to support war, and this study has identified a factor neglected by many of these scholars: knowledge of war. The major finding of this study is that awareness of war facts affects one’s decision to support or oppose war, and that knowing the facts increases the likelihood of opposing war whereas not knowing the facts results in a greater likelihood of supporting war. In fact, war knowledge was the biggest predictor of one’s decision to support war among many of the variables considered most important by social scientists. Certain characteristics were related to a lower level of war fact awareness: supporting the TP, opposing the OWS, conservative political ideology, being highly affected by 9/11, and time spent watching news pertaining to foreign military policy. Do these characteristics lead someone to be unaware or is the unawareness just another characteristic of a particular type of individual? The latter explanation is probably most explicative. Some individuals may benefit from not knowing, or being misinformed. Although this study investigated only war, these individuals may benefit not only war, but also from other actions in which they are uninformed or misinformed. Without question, some individuals profit from war, others need a buffer against cognitive dissonance (such as those in the military), others may have morals that necessitate the affirmation of unfounded convictions, others seek relief and protection from their dangerous world beliefs, and certainly several other scenarios could be at work.

Ignoring reality is not a new phenomenon; but, given its impact on public support for contemporary wars, it is in need of further investigation. The current study serves as a small piece of evidence that individuals may ignore reality when it comes to the decision to support war. This embryonic theoretical framework for explaining how certain individuals become misinformed and make significant decisions without realizing the consequences should be tested in further research.

The public heavily influences whether the United States wages war—largely through public opinion polls. Certainly, the United States would seem unlikely to enter a war with extremely low approval ratings. Therefore, the public ultimately holds a significant amount of power. Yet, as this study shows, many members of the public lack the knowledge to make informed decisions about war. Furthermore, those individuals with insufficient knowledge about war are more likely to support war than those with a more adequate knowledge base. The implications are quite clear. In order to make more prudent decisions about war, the public must be better informed.

Yet, a bigger question remains: how do you inform the public? The findings of this study suggest that certain types of people are un- or misinformed because they do not receive the proper information, but more troubling, it may also suggest that there are people who receive such information and ignore rather than accept it. Although it is difficult to know if these people were ever exposed to truthful information, Dunwoody et al. (2014, 264) seem to be quite pessimistic given that predispositions are integral to holding inaccurate beliefs:

If support for war is ultimately based on preexisting preferences, then reducing support for war must be done by engaging these preferences during their formation. Families and schools both need to emphasize the values of peace, equality, and tolerance to ultimately reduce adult preferences that support war. This is a politically sensitive topic, but the need can be seen in the public schools today. For example, Veterans Day celebrations in public schools emphasize the positive aspects of war, such as soldiers as heroes and protectors of liberty, without also emphasizing the negative aspects of war, such as civilian casualties, mental and physical trauma, and the huge opportunity costs to society. The glorification of violence in the media (movies, TV, and games) is yet another way that young minds are taught about the values of war. These systemic causes ultimately need to be addressed if we hope to reduce the likelihood of war in the future.

Dunwoody et al. were on the right track. The culture of war in the United States describe by Klein (2012) needs to be challenged when possible in the most important social institutions responsible for socialization such as in school, the family, politics, the media, sports, and the economy. The major finding of the study suggests that knowledge of war subsumes the importance of predispositions on supporting war, thus providing hopeful evidence that these predispositions are reversible.

With the major implication of this study suggesting a more informed public could lead to a more peaceful world, future researchers should help to figure out how this can be made possible. The United States seems to be constantly at war, but future researchers should seek to discover if these decisions are made prudently—and if not, why not? The concept of AMFP is novel and provides multiple avenues of future research that should be further investigated.

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Appendix A

Survey Instrument

Hello, I am (name) from the (university name) Sociology and Criminal Justice Department, and I am requesting your participation in the following online survey. This study explores people’s attitudes towards war as well as gauges the knowledge people have of the United States’ military especially pertaining to foreign policy. Your participation is entirely voluntary, and you can choose not to participate in the study at all, or you can skip any question that you do not feel comfortable with. The survey is anonymous so we will not be able to identify you or connect you to your responses. However, please remember that if you are working on a non-secure computer (e.g., a workplace computer that may be subject to monitoring by your employer), others may view your responses. We do hope you will help by answering the following questions as truthfully and completely as you can. If you wish to proceed please hit “Next” to continue to the next page to begin the survey.

First, the survey will begin with a set of statements about the wars in Afghanistan and Iraq. Please state whether you strongly disagree, disagree, are neutral towards, agree, or strongly agree with these statements. Answer neutral if you are unsure.

1. The US targeted urban areas with high rates of civilians in its initial bombing campaign of Afghanistan. (Herold 2002)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

2. The US had confirmed evidence linking Afghanistan to the 9/11 terrorist attacks prior to the US invasion of Afghanistan. (Pincus 2002)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

3. The US invasion of Afghanistan was a violation of international law. (Glennon 2002; Kelly 2002; Quigley 2003)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

4. According to international polls, the US invasion of Iraq was widely supported. (Chomsky 2003, 131–136)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

5. Since entering war with Iraq, the US has found Iraqi weapons of mass destruction. (Kull et al. 2003)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

6. The US has found clear evidence in Iraq that Saddam Hussein was working closely with the al Qaeda terrorist organization. (Kull et al. 2003)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

7. Iraq has used chemical/biological weapons in the ongoing war in Iraq. (Kull et al. 2003)

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

Next, there are four questions about the US military requiring that you type in a numerical value followed by a fifth question which is multiple choice. Please answer to the best of your ability without searching for answers.

8. Considering there are about 195 countries in the world besides the United States, what percent of those countries has United States military troops in them? (write-in) (United States Department of Defense 2009a)

9. According to the US Department of Defense, how many United States military bases are there in other countries outside the US? (write-in) (United States Department of Defense 2009b)

10. For Fiscal Year 2010, what percent of the US discretionary budget was spent on defense? (write-in) (United States Government Printing Office 2011)

11. Given that the United Kingdom spends approximately $57 billion annually, how much do you think the United States spends on its military annually? (write-in) (Stockholm International Peace Research Institute 2011)

12. Which country spends the most on its military annually? (Stockholm International Peace Research Institute 2011)

1. United States

2. United Kingdom

3. China

4. Russia

For the next 10 questions please answer whether you strongly disagree, disagree, are neutral towards, agree, or strongly agree with the statements concerning war.

13. People on this planet can live without arms and war.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

14. Our country should spend much less money on armament.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

15. One should seriously consider also using military in inner-political conflicts.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

16. War is a means of solving international conflicts one cannot do without.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

17. War is a crime against life and thus morally abject.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

18. Under certain circumstances, war can be necessary to protect justice.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

19. Due to humanity’s nature, war is unfortunately inevitable.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

20. War is never justified.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

21. The threat of military force is often the best possibility to keep aggressive states in check.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

22. Only he who has military power at his disposal can negotiate successfully in international conflicts.

1. Strongly Disagree

2. Disagree

3. Neutral

4. Agree

5. Strongly Agree

The following is a set of demographic questions which will conclude the survey.

23. What is your race?

1. Asian

2. Hispanic

3. African American

4. Other

24. What is your gender?

1. Female

2. Male

3. Other

25. Which political party do you prefer?

1. Independent

2. Democrat

3. Republican

4. No preferance

26. What is your political ideology?

1. Very Liberal

2. Liberal

3. Moderate

4. Conservative

5. Very Conservative

27. How strongly do you support the Tea Party?

1. Strongly oppose

2. Moderately oppose

3. Neutral

4. Moderately support

5. Strongly support

28. How strongly do you support the Occupy Wall Street Movement?

1. Strongly oppose

2. Moderately oppose

3. Neutral

4. Moderately support

5. Strongly support

29. What is your age?

(write-in)

30. What is your current grade level?

1. Freshman

2. Sophomore

3. Junior

4. Senior

5. Graduate student

6. Other

31. Which of the following best represents your major?

1. Fine Arts

2. Social Sciences

3. Humanities

4. Business/Public Administration

5. Education

6. Engineering/Technology

7. Health Sciences

8. Physical Sciences

9. Other

32. Have you ever been in the US military (Including at the present time)?

1. No

2. Yes

33. Has anyone in your immediate family or your significant other ever been in the US military (Including at the present time)?

1. No

2. Yes

34. From which medium do you get the majority of your news?

1. Television

2. Radio

3. Print

4. Internet

5. Other

35. From which news source do you get the majority of your news?

1. Daily Show/Colbert Report

2. Major newspaper websites

3. NewsHour with Jim Lehrer

4. O’Reilly Factor

5. National Public Radio

6. Rush Limbaugh’s radio show

7. News magazines

8. TV news websites

9. Daily newspaper

10. CNN

11. News from Google, Yahoo, etc.

12. Network evening news

13. Online news discussion blogs

14. Local TV news

15. Fox News Channel

16. Network morning shows

17. Other

36. How much time do you spend a week watching/listening/reading the news regarding US foreign policy issues?

1. None

2. Less than an hour

3. 1 to 2 hours

4. Between 2 and 3 hours

5. 3 to 4 hours

6. More than 4 hours

37. As a United States resident, how secure do you feel from terrorist attacks?

1. Very insecure

2. Moderately insecure

3. Neutral

4. Moderately secure

5. Very secure

38. On a scale of 1 to 10, 10 being the most affected and 1 being not affected at all, how much has 9/11 affected your daily life? (1-10)

Thank you for your participation.

Appendix B

Descriptive Statistics for Participants

Variable (N) Percent
Gender (337)
Male 193 57.3
Female 144 42.7
Race (343)
Caucasian 270 78.7
African American 28 8.2
Hispanic 15 4.4
Asian 11 3.2
Other 19 5.5
Grade Level (344)  
Freshman 28 8.1
Sophomore 44 12.8
Junior 71 20.6
Senior 101 29.4
Graduate Student 90 26.2
Not in School 10 2.9
Political Party (342)  
Independent 95 27.8
Democrat 73 21.3
Republican 81 23.7
Other 23 6.7
No Preference 70 20.5
Political Ideology (344)  
Very Liberal 27 7.8
Liberal 65 18.9
Moderate 155 45.1
Conservative 76 22.1
Very Conservative 21 6.1
Had Family in Military (345)  
Yes 274 79.4
No 71 20.6
Has Been in Military (345)  
Yes 159 46.1
No 186 53.9
News Medium Used (345)  
Television 69 20.0
Radio 21 6.1
Print 26 7.5
Internet 219 63.5
Other 10 2.9
Time Spent Watching News (343)  
None 13 3.8
Less than 1 hour 65 19.0
1 to 2 hours 98 28.6
Between 2 and 3 hours 62 18.1
3 to 4 hours 50 14.6
More than 4 hours 55 16.0
Specific News Sources (345)  
Liberal 41 11.9
Moderate 56 16.2
Conservative 31 9.0
Other 217 62.9
Major (345)  
Fine Arts 14 4.1
Social Sciences 69 20.0
Humanities 23 6.7
Business/Public Admin. 38 11.0
Education 45 13.0
Engineering/Technology 69 20.0
Health Sciences 37 10.7
Physical Sciences 26 7.5
Other 24 7.0
Spends Most on Military (343)  
United States 263 76.7
United Kingdom 3 0.9
China 64 18.7
Russia 13 3.8

Appendix C

Descriptive Statistics for Continuous Variables

Variable N M SD Range
Age 338 31.11 11.50 18–69
MP Score 329 33.28 7.91 10–50
AIWA Score 337 21.65 5.16 7–35
Percent Military Spending 331 40.82 21.97 0–100
Percent US Troops 337 43.20 27.90 0–100
Number of US Bases 332 211.82 271.92 0–1,000
US Military Spending 334 329.50 272.11 2–1,000
Support OWS 343 2.83 1.25 1–5
Support TP 343 2.56 1.18 1–5
9/11 Affected Life 345 5.57 2.63 1–10
Security from Terrorism 344 3.58 1.09 1–5

1. See also Baum and Groeling (2009); Soroka and Wlezien (2009); and Zaller (1992).

2. Some examples of this include the Espionage Act and the Sedition Act (see Gan 2005), the Office of Strategic Information (GlobalSecurity.org 2002), and increased refusals of Freedom of Information Act requests (Public Citizen 2004; see also Garson 2005).

3. The study focused on American casualties because if the number of Iraqi casualties is included the number drastically increases resulting in even larger underestimations (Roberts et al. 2006).

4. For instance, “What party currently controls the House of Representatives?” or “What company does Steve Jobs run?”

5. Sixty-five percent answered at least nine of twenty-three items incorrectly in 2007; 72 percent answered at least one of three incorrectly in 2008; and 86 percent answered at least one of four incorrectly in 2010.

6. In diplomatic relations prior to the Iraqi invasion of Kuwait, the US State Department did not clearly state they would intervene if Iraq invaded Kuwait. Instead, the US gave “equivocal statements” (see Sciolino and Gordon 1990).

7. Various other studies investigating “support for war” have used student samples (Parker et al. 2009; Crowson et al. 2006; Putney and Middleton 1962; Droba 1931. The most popular methodology was poll analysis, but this is not a viable approach given the research questions; AMFP or anything similar has not been included on war support opinion polls.

8. The study was approved by the University International Review Board (IRB approval #11-035).

9. A militarism-pacifism scale was used as the measure for support for war, diverging with much of the literature, for two reasons. First, the current study is interested in a measure for “general support for war.” It is assumed that militaristic people are more likely to support war generally. This assumption has been evinced in studies such as Cohrs and Moschner (2002). Second, the militarism-pacifism scale provided for much more variability and nuance than the likely alternative of a “yes/no” question about a specific war, often times asked as a mistake question (see Mueller 1971).

10. Originally, it was a ten item scale with five possible responses for each: (1) “not true,” (2) “a little true,” (3) “middling true,” (4) “quite true,” and (5) “very true.” The original as well as the more recent study were both conducted in German and therefore may not translate nicely verbatim. Instead of using their 5-point response, the current study altered the 5-point response options to (1) “strongly disagree,” (2) “disagree,” (3) “neutral,” (4) “agree,” and (5) “strongly agree.” The new wording is very common in similar scales and should not disrupt the reliability significantly.

11. A recent study used this scale and recorded a .77 (N=131) Cronbach’s alpha (Jackson and Sparr 2005).

12. See Bardes and Oldendick (1978), Putney and Middleton (1962), and Dombrose and Levinson (1950).

13. All seven items were pretested in an undergraduate Introduction to Sociology course. After 129 respondents answered the seven items, a class discussion was held about the validity of the instrument. Students confirmed that they would “agree” and not “strongly agree” when they were uncertain of the truth. There was no student who spoke out and stated that they were confused. In addition, some students reported that they answered “neutral” if they did not know the correct response instead of guessing.

14. The list of news sources replicated that of Pew Research Center’s (2007) study about political awareness and media news source. Participants were given a list of 17 news sources and asked to identify where they get the majority of their news. Two choices were not chosen by even one participant (“NewsHour with Jim Lehrer” and “Rush Limbaugh’s radio show”) and therefore were discarded. The remaining new sources were grouped by their political orientation into the categories of “liberal,” “moderate,” “conservative,” and “other.” “Liberal” consisted of “Daily Show/Colbert Report” and “National Public Radio.” “Moderate” consisted of “CNN.” “Conservative” consisted of “O’Reilly Factor” and “Fox News Channel.” The remaining categories were grouped into the “other” category.

15. The latter question was meant to filter out those individuals using the news for information not germane to US foreign policy issues such as sports, entertainment, stocks, etc.

16. Various studies have explored the effects of different demographics on support for war (Droba 1931; Mueller 1973; Lunch and Sperlich 1979; Kauffman 1989; Page and Shapiro 1992; Erikson and Tedin 1995; Allsop et al. 1996; Boussios and Cole 2010; Brooks and Valentino 2011).

17. To assess military involvement both: “Have you ever been in the US military?” and “Has anyone in your immediate family or your significant other ever been in the US military?” were asked.

18. These items included, “As a United States resident, how secure do you feel from terrorist attacks?” and “On a scale of 1 to 10, 10 being the most affected and 1 being not affected at all, how much has 9/11 affected your daily life?”

19. Items were re-coded in the same direction and the ten items were added to obtain scale scores ranging between 10 and 50.

20. Due to excessive skewness, the variables “US military spending” and “number of US bases” found in Appendix C were truncated at 1,000 (any response higher than 1,000 was recoded as 1,000).

21. When given four choices on which country spends the most on its military annually, 76.7 percent correctly chose the United States, but when asked to state, in billions of dollars, the amount of money the United States spends on its military annually, the sample answered less than half ($330 billion) of the real sum ($698 billion) (Stockholm International Peace Research Institute 2011). The sample as an aggregate thought that 40.8 percent of the discretionary budget went to defense spending when in reality 54.6 percent was used for defense spending in fiscal year 2010 (United States Government Printing Office 2011). The sample actually fared the best on this item and there was still nearly a 14 percent difference between respondents’ estimates and reality. For the remaining items, the sample believed that 43.2 percent of the countries in the world had US troops present in them, while in fact a Department of Defense document has that number at around 70 percent (United States Department of Defense 2009a). Lastly, the sample stated that there were about 212 United States military bases in foreign countries. A Department of Defense document reveals that the sample mean was a drastic underestimate and it puts the number at 716 bases (United States Department of Defense 2009b).

22. Various models were conducted until finalizing the three models found in Table 1.

23. Political party was excluded from the models because it was not found to be statisticajlly significant, and political ideology was a much better predictor.

24. Both a Shapiro-Wilke test for normality of the residuals and a White’s test were not statistically significant (p>.05). All variation inflation factors (VIF) were under three and tolerance levels were all over .40.

25. Similar to the models in Table 1, the news medium variable and political party were excluded because they did not contribute any statistically significant change to the models.

26. Both a Shapiro-Wilke test for normality of the residuals and a White’s test were not statistically significant (p>.05). All variation inflation factors (VIF) were under three except “news source other” variable which had a VIF of 3.45. Tolerance levels were all over .40.

27. In fact, two of the items were correlated in the opposite direction than expected. Possibly, the media provides more accurate information pertaining to Afghanistan and Iraq than information pertaining to the vastness of the US military.

28. The pertinence of political ideology over political party deserves explanation. After observing the descriptive statistics, one should notice that political ideology was nearly a perfect distribution whereas political party had large numbers of respondents reporting no political preference, Independent party, or some other political party preference. With a minority of participants preferring either the Democratic or Republican party, political ideology became the crucial variable. The current study’s sample consisted of a majority of young individuals enrolled in a four-year university. It is possible that this new generation of citizens are becoming frustrated with mainstream politics and seeking alternatives (e.g., Independent party, Green party, Socialist party, or no preference at all). One study that supports this explanation has shown an increase in the public’s disapproval rating of the US Congress (Pew Research Center 2009).

29. All four of these correlations were relatively moderate in strength and very similar. In addition, support of OWS was the strongest predictor of one’s awareness of war facts and support of TP was the fourth strongest predictor. Although support for TP was not a significant predictor for likelihood of support for war, support for OWS was the fourth strongest predictor when controlling for other variables.

30. Right-wing authoritarianism (RWA; see Altemeyer 1996) has been theorized as originating from DWB (Duckitt 2001, 2006; Duckitt et al. 2002), and RWA has been linked to greater support for war (Crowson et al. 2006; Crowson, 2009) consistent with the current study. The current study’s findings provide some evidence that DWB may in fact indirectly affect support for war through war fact knowledge because the 9/11 effect was the second strongest predictor of war fact knowledge. Future researchers should seek to clarify these effects.