Democracy under Fire: Voter Confusion and Influences in Colorado's Anti-Affirmative Action...

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Harvard Educational Review Vol. 83 No. 3 Fall 2013Copyright © by the President and Fellows of Harvard College

Democracy under Fire: Voter Confusion and Influences in Colorado’s Anti–Affirmative Action Initiative

AMY N. FARLEYMATTHEW N. GAERTNERMICHELE S. MOSESUniversity of Colorado Boulder

In this article, Amy N. Farley, Matthew N. Gaertner, and Michele S. Moses examine the use of ballot initiatives as a particularly attractive form of direct democracy for opponents of affirmative action in higher education. Building on previous scholar-ship, the authors question whether anti–affirmative ballot initiatives validly reflect voters’ attitudes toward affirmative action. The authors examine the case of Colo-rado’s Amendment 46, an anti–affirmative action ballot initiative. They investigate the language of the initiative itself, as well as voters’ perceptions of and confusion around its intent, and the factors that influenced voting behavior. They employ item response theory to estimate voters’ attitudes toward affirmative action. The authors then describe the prevalence of voter confusion around the initiative’s intent. Finally, employing a binary logistic regression model, they analyze survey data to determine which factors influenced voting behavior. They find that the initiative’s language was successful at confusing voters who intended to support affirmative action. Fol-lowing the U.S. Supreme Court’s recent decision in Fisher v. University of Texas and in anticipation of its decision in Schuette v. Coalition to Defend Affirmative Action, the authors call for greater scrutiny with regard to the use of initiatives to craft education policies that have a disproportionately negative impact on members of disadvantaged populations.

Since 1996, six states—California, Washington, Michigan, Nebraska, Arizona, and Oklahoma—have considered ballot initiatives seeking to ban affirmative

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Democracy under Firefarley, gaertner, and moses

action in public education and public contracting and employment. In each state, the initiative passed easily, with margins of victory ranging from 9.1 to 19 percent (see table 1). In each of these states, anti–affirmative action ballot ini-tiatives have consistently passed by wide margins of greater than 100,000 votes.

In 2008, a seventh state, Colorado, considered the anti–affirmative action initiative Amendment 46, otherwise known as the Colorado Civil Rights Ini-tiative. Though preelection polls anticipated a result similar to previous state-level affirmative action initiatives, Colorado voters defeated this initiative by fewer than 40,000 votes (Legislative Council of the Colorado General Assem-bly, 2008). This result raises several questions: Why did Colorado voters in 2008 vote differently than predicted? Why did the Colorado election results differ from elections in other states that had previously considered this issue? How did voter attitudes toward affirmative action actually affect the outcome of the vote? And how might the language of Amendment 46 have confounded a relationship between voters’ intentions and their actual votes?

Prior to the 2008 Colorado election, reports of voter fraud and deception surrounding Amendment 46 garnered significant attention in the national media. Moses and Farley (2011) recount the story of a seventy-eight-year-old African American woman who felt deceived when she inadvertently signed a petition for the pending ballot initiative. That story was first printed in the New York Times (Frosch, 2008) and gained traction on the national stage and from opponents during the Colorado campaign. In response to these claims, Vincent Carroll (2008), then a staff writer for the Rocky Mountain News, argued

TABLE 1 Affirmative action bans in six states

State and initiative Year Margin of

victory

Margin of victory no.

of votes

California Civil Rights Initiative(Proposition 209)

1996 9.1% 879,729

Washington Affirmative Action Ban(Initiative 200)

1998 16.4% 310,480

Michigan Civil Rights Amendment(Proposal 2)

2006 15.8% 585,319

Nebraska Civil Rights Initiative (Initiatitive 424)

2008 13.0% 106,365

Arizona Civil Rights Amendment(Proposition 107)

2010 19.0% 304,373

Oklahoma Affirmative Action Ban(State Question 759)

2012 18.4% 231,691

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Harvard Educational Review

that it is “a sad state of affairs when people must fight a ballot initiative by admitting they were bamboozled by simple English.” We agree with one of Carroll’s points: it is a sad state of affairs when voters are bamboozled, partic-ularly by ballot initiatives enacted through citizen-initiated direct democratic avenues.

The string of anti–affirmative action initiatives exemplifies the expanded use of ballot initiatives and other forms of direct democracy (Ellis, 2002; Ini-tiative and Referendum Institute, 2013; Kapsch & Steinberger, 1998). Figure 1 shows the frequency of citizen-initiated state ballot initiatives since the 1960s. This resurgence compels us to look closer at the focus and impact of citizen-initiated state ballot initiatives.

Although there is currently no definitive research on the use of ballot initia-tives in U.S. education, or its impact on our schools and students, we do know that the use of ballot initiatives to craft education policy has grown (Moses, 2010). The National Council for State Legislatures (NCSL, n.d.) hosts a ballot measure database that tracks historical initiative data across the United States. A simple search for citizen-initiated state ballot measures addressing K–12 and higher education results in 232 separate measures, beginning in 1910; this number likely underestimates the number of initiatives affecting educa-tion policies, however, because some tax and civil rights initiatives (other cat-egories in the NCSL database) also have large implications for schools. In the 2012 general election, voters in five states considered tax initiatives that would directly affect educational funding; voters in Washington State voted to permit the creation of charter schools (Initiative and Referendum Insti-

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FIGURE 1 Total ballot initiatives, by decade, 1960–2010

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tute, 2012). Previously, citizens have voted on a wide range of education issues, both general issues and ones that directly affect minority groups. For example, citizen-initiated ballot initiatives have targeted bilingual education for Eng-lish language learners (ELLs)1 and access to school materials and curriculum regarding the LGBTQ community.2

Given the increasing prominence of the ballot initiative process, and our belief in the importance of public education policies attentive to equity and justice, we think it is critical that researchers evaluate the consequences of ballot initiatives on education policy making. In particular, we are concerned with the use of the initiative process to legislate policies that negatively affect the nation’s most traditionally disadvantaged populations. We believe that the consequences of this citizen-initiated legislation raise questions about the appropriateness of ballot initiatives as a policy-making tool for public education in general and higher education in particular.

Further, by specifically focusing here on Colorado’s anti–affirmative action initiative, we provide additional evidence through which to consider Moses and Farley’s (2011) argument that ballot initiative reform is crucial to ensur-ing that the educational policies enacted by direct democracy do not com-promise fairness and justice or have a disproportionately negative impact on minority groups. In this case, the passage of Colorado’s Amendment 46 would have had significant implications for higher education. This concern for jus-tice leads us to examine voter perceptions of Amendment 46 during the elec-tion to determine whether this amendment functioned in a fair and highly transparent manner.

Opponents of anti–affirmative action initiatives claim that the language of these “civil rights initiatives”—including their name—is confusing, particu-larly for those who intend to support affirmative action (Colorado Unity, 2007; Frosch, 2008; Michigan Civil Rights Commission, 2006; Stoddard, 2008). Sup-porters of anti–affirmative action initiatives argue that the Amendment 46 language relies on traditional phrasing often associated with the civil rights movement (see Goodland, 2008). The Colorado Civil Rights Initiatives lan-guage reads: “The state shall not discriminate against, or grant preferential treatment to, any individual or group on the basis of race, sex, color, ethnicity, or national origin in the operation of public employment, public education, or public contracting” (Legislative Council of the Colorado General Assem-bly, 2008). This is nearly identical to the language used in the six other states that have approved such measures [(Ariz. const. art. II, § 36; Calif. const. art. I, § 31; Mich. const. art. I, § 26; Neb. const. art. I, § 26; Okla. const. art. II, § 36; RCW 49.60.400 (1998)(Washington statute)]. It is also similar to the lan-guage of Title VI of the Civil Rights Act of 1964, which states that “no person in the United States shall, on the ground of race, color, or national origin, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance.”

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Although the Colorado General Assembly’s addition of the phrase “prefer-ential treatment” in the initiative’s language clearly distinguishes it from the Civil Rights Act, it is unclear how the typical voter understands this phrase separately and apart from—or in conjunction with—the rest of the initiative’s text. We argue that sociopolitical contexts shape how voters interpret the con-cept of discrimination and could contribute to how they understand the initia-tive text and, more broadly, the intent of Amendment 46. Thus, our research focuses on understanding the extent to which the outcome of Colorado’s Amendment 46 was a genuine reflection of voters’ attitudes toward affirmative action and equal opportunity.

To address this central question, we explore the relationship between vot-ers’ attitudes toward affirmative action and their voting behaviors, the impact of demographic characteristics on voters’ attitudes toward affirmative action and their voting behaviors, and the extent to which this initiative’s potentially confusing language influenced the outcome of the vote. Our analyses not only suggest that confusion was rampant in the 2008 Colorado Amendment 46 vote but that it was much more prevalent among voters who intended to sup-port affirmative action. These findings call into question the transparency and functionality of the Amendment 46 vote. We also argue that they provide evi-dence of the use of ballot initiatives to limit minority rights, even as it pertains to a public good like education. While we believe that any ballot initiative that disproportionately affects minority groups is troubling, we argue that policies that affect education are particularly critical to the maintenance and creation of justice and our democracy. For this reason, researchers, practitioners, and policy makers should be cautious of policy-making tools—especially those that seem to function in insidious or misleading ways—that do not attend to the principals of equality and do not ensure the equal educational opportunity of all students.

Colorado Context and Background

Colorado’s Amendment 46 is a compelling case study because its subject, affir-mative action, engenders rigorous debate and strongly held opinions through-out society and among the voting public, particularly on whether it is an appropriate means for securing minority rights. The rigor of debate and soci-etal interest make affirmative action particularly attractive to the political pro-cess. This distinguishes affirmative action voter initiatives in many ways from other civil rights efforts. Conversely, it also raises unique questions about the appropriateness of the political process for amending minority rights.

This policy paradox has major foundational implications for public educa-tion above and beyond other fields of governmental influence. As Secretary of Education Arne Duncan remarked, education is “the civil rights issue of our generation. It is the only path out of poverty, the only road to a more equal, just, and fair society” (Duncan, 2009). If Secretary Duncan is correct, then it is

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especially important to consider how policy decisions of all sorts affect minor-ity students’ access to quality education.

The subject of legislating affirmative action is far from settled. In the next October term, the U.S. Supreme Court will hear Schuette v. Coalition to Defend Affirmative Action, a case concerned with the impact of such state ballot initia-tives on minority populations. The Court will consider whether states violate the Equal Protection Clause of the Fourteenth Amendment when they pass ballot initiatives that eliminate race- and gender-conscious affirmative action. Our research has significant implications for this case given our emphasis on how such initiatives may be understood by voters.

The anti–affirmative action “civil rights initiatives” have relied largely on citizen-initiated legislation; in this way, affirmative action opponents have used direct democracy as a means to restrict and eliminate policies largely enacted by a representative government to protect minority rights. As the success of these initiatives indicates, modern education policies and reform efforts can be characterized largely as a departure from the priorities set forth by the influential Brown v. Board of Education decision, with an increased focus on achievement and other outcomes instead of the Court’s historic emphasis on equity. The success of these initiatives provides just one example of how poli-cies designed to benefit disadvantaged populations, particularly low-income communities of color, have been increasingly targeted and eliminated. Given this claim, and the existing inequalities outlined above, the assertion that ballot initiatives may, in fact, exacerbate this departure from equity-minded reform is cause for concern and necessitates exploration. As such, it is espe-cially important to consider the effects of education ballot initiatives, particu-larly on historically marginalized communities, including students of color, women, low-income students, ELLs, and LGBT students.

Historical Perspectives

Direct Democracy, Ballot Initiatives, and Civil Rights Any discussion of direct democracy must first explicate the differences between direct democracy and representative government. In the Federalist Papers, James Madison (1787) distinguished between a pure democracy, in which all citizens assemble and administer the government themselves, and a representative government, like the federal republic that is the United States. Madison explained that in a representative government, decision-making authority is delegated to a small number of elected representatives; this del-egation functions

to refine and enlarge the public views, by passing them through the medium of a chosen body of citizens, whose wisdom may best discern the true interest of their country, and whose patriotism and love of justice will be least likely to sacrifice it to temporary or partial considerations. Under such a regulation, it may well hap-

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pen that the public voice, pronounced by the representatives of the people, will be more consonant to the public good than if pronounced by the people them-selves, convened for the purpose (para. 16).

Madison argued that one danger of pure democracy is the infringement of individual rights by the will of some faction of society. Alternately, representa-tive government can protect the rights of individuals and preserve the com-mon good.

Unlike representative government, direct democracy puts legislative power in the hands of ordinary citizens. The two main tools of direct democracy are the referendum and the ballot initiative (Smith & Tolbert, 2004). Referenda are the procedures through which a governing body passes an issue of public pol-icy to the citizens for a vote; the issues do not originate with the voters but are merely decided by them. Ballot initiatives, however, come from citizens and allow voters to directly propose and vote on public policy and law, often in cir-cumvention of the legislature. There are two types of ballot initiatives: consti-tutional amendments, which amend the fundamental law of the state (the state constitution), and statutory measures, which amend laws issued by legislatures, or statutes (Donovan & Bowler, 1998). Ballot initiatives are therefore the only purely citizen-initiated form of legislation and, as a consequence, represent the largest departure from the kind of traditional representative democracy urged by our founding fathers.

With the exception of a limited system in Switzerland, the initiative process is uniquely American (Patterson, 1998). However, it is a recent addition to U.S. politics that emerged in the American West with the early-twentieth-century progressive movement (Kapsch & Steinberger, 1998). Twenty-four states cur-rently allow some sort of citizen-initiated direct legislation through the ballot process: 18 currently allow constitutional amendments,3 and 21 allow statu-tory initiatives4 (Bowler & Donovan, 2000; Bowler, Donovan, & Tolbert, 1998; Broder, 2000; Ellis, 2002; Gamble, 1997; Initiative and Referendum Institute, n.d.; Matsusaka, 2004; Nicholson, 2005; Sabato, Ernst & Larson, 2001; Smith & Tolbert, 2004). These states are largely concentrated in the West. Of the states west of the Mississippi River, only 6 do not permit some form of initiative or popular referendum. Of the states east of the Mississippi, only 8 do (Magleby, 1995). Furthermore, the states with the most prolific initiative process are all in the West: Oregon has had 363 ballot initiatives, California 352, and Colo-rado 218 (Initiative and Referendum Institute, 2013).

Since the first initiative ballot amendment appeared in Oregon in 1904, the initiative process has had a substantial impact on state and local politics. In total, 984 of the 2,421 state-level initiatives put before voters have been approved (Initiative and Referendum Institute, 2013). Successful initiatives have amended state constitutions and enacted statutory requirements regard-ing a wide array of policy issues, from tax law to civil rights, education to housing policies. Despite the increasing use of ballot initiatives in the United

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States, the value of direct democracy has been debated by political scientists and the media.

There are three primary critiques of the initiative process. First, it is regarded as being vulnerable to corruption, which, in recent years, has been exacer-bated by the growth of a specialized ballot initiative industry, which includes for-profit signature gatherers and highly influential political analysts (Garrett, 1998; Magleby, 1995; Smith & Tolbert, 2004). The second criticism is that bal-lot initiatives are disproportionately utilized by citizens privileged with money, power, and access to other influential people (Goldsmith, 2005; McCuan, Bowler, Donovan, & Fernandez, 1998). The overrepresentation of the privi-leged in the political arena of the ballot initiative—and the resultant prioriti-zation of the issues they deem important—is likely to perpetuate inequalities. Some scholars argue, however, that an even more egregious miscarriage of justice occurs in the systematic and intentional abuse of minorities in the U.S. ballot initiative system (Magleby, 1995; Gamble, 1997; Goldsmith; 2005). The third criticism is that ballot initiatives disproportionately affect minor-ity groups and do not provide these groups the same protections that they might expect from a representative government (Gamble, 1997; Goldsmith, 2005; Magleby, 1995; Moses, 2010; Nicholson, 2005). In this way, direct democ-racy inappropriately facilitates “tyranny of the majority” (de Tocqueville, 1835; Guinier, 1994) where “in a racially divided society, majority rule may be per-ceived as majority tyranny” (Guinier, 1994, p. 3). In keeping with Madison’s (1787) caution, ballot initiatives may allow both small and large factions to compromise the collective good by legislating tyrannical interests. The use of initiatives focusing on English-only instruction and the denial of “special rights” to gays and lesbians serve as two particularly poignant examples. We believe it is questionable that either of these issues would have received the same traction and been awarded the same national significance were they not forced into the political dialogue because of their presence on the ballot in several states.

Nevertheless, research regarding tyranny of the majority in the ballot initia-tive process is mixed. In an examination of state and local ballots from across the United States, Gamble (1997) found “strong evidence that the majority has indeed used its direct legislative powers to deprive political minorities of their civil rights” (p. 256). Gamble’s analysis reveals that initiatives that nega-tively target minority rights pass more than twice as often as those that do not. In an extension of Gamble’s study, Haider-Markel, Querze, and Linda-man (2007) found evidence of disparate impacts of ballot initiatives on LGBT communities: in 143 initiatives examined, spanning twenty-five years, 71 per-cent diminished gay rights.

Not all scholars agree about the prevalence of tyranny of the majority in the American ballot initiative system. Hajnal, Gerber, and Louch (2002) analyzed voter outcomes in the ballot initiative process in California to determine the presence of systematic differences among various racial and ethnic groups.

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They found that minority groups were no less likely to be on the winning side of the initiatives and argue that this finding provides compelling counterevi-dence to arguments that there is inherent racial bias in the initiative system and that “analyses that focus strictly on one or a few minority-targeted initia-tives overstate the detrimental effects of direct democracy” (p. 174). Hajnal et al. point to the fact that explicitly antiminority measures are rare and usually fail at the ballot box when present. However, the presence of initiatives that target minority groups—even if rare—may serve as an existence proof of the vulnerability of the initiative system to abuses of justice that could allow for the increased institutionalization of racism, sexism, homophobia, and other oppressive ideologies.

Some research even suggests that initiatives targeting minority rights—whether they pass or fail—have a lasting impact on the psyche of the voting public. Wenzel, Donovan, and Bowler (1998) claim that merely by shifting public discourse to address certain issues, “direct democracy might operate to the detriment of the toleration of political outgroups” (p. 245). Research has shown increased hostility and decreased tolerance immediately following elec-tions with ballot initiatives targeting minorities. Wenzel and colleagues, for example, show an increase in hate crimes when antigay initiatives appear on the ballot, which suggests that the deleterious effects of ballot initiatives tar-geting minority groups may extend beyond the direct outcomes on Election Day. This calls for research that examines those effects more systematically.

Affirmative Action and Higher EducationFew debates in American policy are as charged and divisive as race-based affir-mative action. Although race-based affirmative action policies are rooted in the civil rights movement, they spark fierce moral disagreement about equal opportunity, discrimination, and the legacy of racism. The legality of affir-mative action policies in higher education has been contested repeatedly in court (Fisher v. University of Texas, 2013; Gratz v. Bollinger, 2003; Grutter v. Bollinger, 2003; Regents of the University of California v. Bakke, 1978). In the higher education context, rulings have generally found that the value of selecting a diverse student body justifies the use of race as one factor in admis-sion decisions (Regents of the University of California v. Bakke, 1978; Grutter v. Bollinger, 2003; Fisher v. University of Texas, 2013). However, these court rulings have not quieted protests or attempts to prohibit affirmative action policies, particularly at the state level.

The roots of affirmative action are generally traced to President John F. Kennedy’s 1961 executive order establishing the Committee on Equal Employ-ment Opportunity. This executive order required that federally funded proj-ects take “affirmative action” to ensure hiring and employment practices free of racial bias (Exec. Order, 1961). The ensuing push for equal opportunity was strengthened following the passage of the 1964 Civil Rights Act. One year later, affirmative action was the centerpiece of a speech offered by President

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Lyndon Johnson (1966). In June 1965, addressing graduates of Howard Uni-versity, Johnson argued: “You do not take a person who, for years, has been hobbled by chains and liberate him, bring him up to the starting line of a race and then say, ‘you are free to compete with all the others,’ and justly believe that you have been completely fair.” He claimed that the next stage in the battle for civil rights would be the pursuit of “not just equality as a right and a theory but equality as a fact and equality as a result.”

Universities and colleges in the United States took this as a call to recruit and admit minority students. Bob Laird (2005), former dean of admissions at the University of California, Berkeley, notes that in the 1970s there was an “overwhelming sense of urgency felt by some colleges and universities to sharply increase the numbers of African American, Latino, and Native Ameri-can students they enrolled” (p. 52). Soon after, opponents of race-conscious admissions policies began to challenge the legality of affirmative action.

In Regents of the University of California v. Bakke (1978), Justice Lewis Powell, in his controlling concurrence, found the use of rigid race-based quotas to be unconstitutional. Powell wrote that universities could take race into account in admissions decisions as long as minority status was weighed holistically among a host of other factors. The compelling interest in this regard, Powell argued, was the educational benefit realized by a diverse student body. In the 2003 Grutter v. Bollinger decision, Justice Sandra Day O’Connor suggested that “25 years from now, the use of racial preferences will no longer be necessary to further the interest approved today” (Grutter, 2003, p. 31). In response to the court’s claim that affirmative action would soon be rendered “unnecessary,” Carter (2009) argues against the notion that the United States is “postracial”: “a postracial nation is not one that remains segregated . . . [and] we now have to ask whether the powerful impact of both accumulated and contemporane-ous disadvantages will keep many poor racial and ethnic minorities wedged at the bottom of the U.S. opportunity structure” (p. 291). Although Carter argues that systems of oppression and inequality necessitate equal opportu-nity programs on the basis of race, opponents believe that affirmative action policies actually exacerbate inequalities and unfairly discriminate on the basis of race. The Supreme Court’s June 2013 ruling in Fisher v. University of Texas did little to settle the issue. Writing for a 7–1 majority, Justice Anthony Ken-nedy acknowledged that racial diversity yields important educational benefits on college campuses, but the ruling put affirmative action on notice. Echoing Grutter, Kennedy’s opinion emphasized that when race-conscious admissions are used, “strict scrutiny” must be applied; specifically, courts “must ultimately be satisfied that no workable race-neutral alternatives would produce the edu-cational benefits of diversity” (Fisher v. University of Texas, 2013, p. 2). Fisher will be reconsidered by the U.S. Circuit Court of Appeals for the Fifth Circuit.

Following a number of unsuccessful court cases, affirmative action oppo-nents turned to voter initiatives to advance their cause. That these opponents were dissatisfied with the outcomes of court rulings does not imply that the

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courts have upheld affirmative action without placing limitations on how race can be used in admissions decisions. To the contrary. In Gratz v. Bollinger (2003), the use of “points” assigned only to minority applicants was deemed discriminatory and illegal. Despite these limits on affirmative action, Connerly (2007) argues that affirmative action of any kind is “reverse discrimination” and as such strays from “one of our nation’s basic civic values, namely a nation in which all of its citizens are of equal value in the eyes of the government” (p. 62). This “reverse discrimination” rhetoric galvanized support for anti– affirmative action initiatives. In a major blow to affirmative action equal oppor-tunity programs, these initiatives passed in every state except Colorado (Moses, Yun, & Marin, 2009). Numerous studies have shown that one consequence of outlawing race-based affirmative action is a profound reduction of minority representation on college campuses (Contreras, 2005; Horn & Flores, 2003; Saenz, 2010). Minority representation has also plummeted in graduate pro-grams following legal bans on race-conscious admissions (Cantwell, Canche, Milem, & Sutton, 2010; Garces, 2010). This is especially true for selective institutions. Even when universities implement other policies to encourage diversity—like guaranteeing admission to top students from every school in a state—enrollment of minority students continues to lag behind pre-ban lev-els (Hinrichs, 2009; Long, 2004, 2007; Long & Tienda, 2008). This research suggests that the results of the process in anti–affirmative action civil rights initiatives have had a disproportionate impact on minority populations. Thus, challenging affirmative action through the initiative process provides another example of tyranny of the majority at work.

Theoretical Framework and Underlying Beliefs

We designed our research questions and analyses through a lens heavily influ-enced by conceptions of democratic education that centrally locate the prin-ciple of equal educational opportunity (Burbules & Sherman, 1979; Gutmann, 1999; Howe, 1997). Figure 2 graphically presents the beliefs underlying our research and the two primary premises that arise from them. First, educa-tion ballot initiatives have potentially great impacts on democracy and justice. This is predicated on the idea that education is necessary for the creation and maintenance of democracy. As Gutmann (1999) asserts, “Education not only sets the stage for democratic politics, it plays a central role in it” (p. 1). She argues that, mechanistically, education instills and creates the moral character of citizens and that, in turn, this moral character combines with laws, values, and social institutions to create the fabric of our government. Democratic gov-ernment then “shapes the education of future citizens, which, in a great mea-sure, forms their moral character” (p. 49). The process is cyclical. Extending this logic, we argue that ballot initiatives can affect not only the laws and insti-tutions that are the basis of our democracy but also the future moral character of our citizens and, by extension, the future of democracy. Simply stated, edu-

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cation is indispensable for the establishment and maintenance of democracy, so education policy decisions may have profound consequences for democ-racy. Because of this, the increasing frequency of ballot initiatives targeting education has implications for our democracy.

Our second underlying premise is that the implications of ballot initiatives may be especially felt by students who are already marginalized in our demo-cratic society. We first argue that underrepresented students—particularly stu-dents of color—are at a disadvantage in our education system. The weightiness of the problems associated with, and in part responsible for, the achievement gap have prompted Ladson-Billings (2006) to advocate for its reconceptu-alization as a debt owed to marginalized students rather than as an apoliti-cal “gap” in performance. By advocating a shift in the onus of responsibility, Ladson-Billings’ reconceptualization is important for this study as well. If we begin to see education as fundamentally linked to democracy, we must then consider inequalities in schools and inequitable access to higher education as inequalities in the very fabric of democracy. Correspondingly, if education policy making is implemented through hasty, inequitable, or insidious means, the resultant policies will also have potential consequences not only for educa-tion and educational equity but also for society at large.

Given these two premises, we approach the study of ballot initiatives affect-ing education policy as a critical area of scholarship in and of itself. The con-sequences of such ballot initiatives extend well beyond the immediate effects of any given decision (Saenz, 2010). As the education-policy-by-ballot-initiative phenomenon continues to grow, it is important not only to consider the impacts and effects of said policies but also to examine how they function in practice.

FIGURE 2 Graphical representation of theoretical framework

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Methods

The central research question of this study is whether or not the Amendment 46 outcome was an accurate reflection of Colorado voters’ beliefs. To answer that, we focus on the relationship between voters’ attitudes toward affirma-tive action and their voting behavior, holding constant relevant demographic covariates, and the extent to which the amendment’s potentially confusing language influenced the outcome of the vote. We developed and administered a survey to collect demographic, voter attitude, and voting behavior data and specified statistical models to estimate influences on voting behavior.

ParticipantsVoter Consumer Research, an independent research company, administered a telephone survey in May 2009 to a stratified random sample of 507 Coloradans who reported voting in the November 4, 2008, election. Considerable time had elapsed since the November 4 vote, so it was necessary to screen potential respondents and collect data from only those who were sufficiently confident they remembered how they voted on Amendment 46. Only voters who indi-cated they were at least 70 percent confident were included in the sample, and the survey was terminated for voters who indicated that they were less than 70 percent confident of their vote.

We did not have access to demographic and socioeconomic characteristics of likely voters in Colorado but were able to collect much of this informa-tion for registered voters. Participants were randomly sampled from the popu-lation of all registered voters, stratified across eighteen regions designed to be representative of the state in terms of partisanship, urbanicity, and physi-cal proximity. The median age for respondents was 52, with a range of 18 to 92 years old, and the median family income was $65,500. Data regarding the 2008 voting population from the U.S. Census Bureau (2010) does not provide state disaggregated socioeconomic information, making it difficult to gauge the representativeness of our sample’s income compared to the voting population of Colorado. The median family income in Colorado in 2008 was $55,212, which was lower than our sample. But because income is positively associated with voting rates—in 2008, only 51.8 percent of citizens with family incomes under $20,000 voted, compared to 75.4 percent of citizens with fam-ily incomes between $75,000 and $99,999—it is highly likely that the median income among registered voters, particularly those who actually voted, would be closer to that of our sample.

Exploratory analyses also suggest that demographic characteristics of vot-ers in our sample are generally consistent with the population of registered voters in Colorado (see table 2). While data on education levels for registered Colorado voters are unavailable, 55.8 percent of our sample reported hav-ing a college education, compared with 33.5 percent of Coloradans at large. Probability of voting is also related to education levels, with 78.9 percent of

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college-educated citizens casting a ballot nationally in 2008, compared to only 57.8 percent of non-college-educated citizens (U.S. Census Bureau, 2010). As a result, our sample was largely English speaking, slightly older than the gen-eral population, possibly more affluent, and likely more educated than Colo-rado’s general population. One percent of respondents selected a language other than English as the primary language spoken at home.

MeasuresThe full survey included questions on voting behaviors, influences of various campaign activities and public media, demographic information, and atti-tudes toward affirmative action. (For the full text of the survey, see Moses et al., 2010.)

Voting Behaviors. Respondents were asked to report how they voted on Amend-ment 46 and whether or not they voted no “straight down the ballot.” Follow-ing the election, proponents of Amendment 46 indicated that the initiative may have failed in Colorado because of ballot fatigue: there were fourteen

TABLE 2 Sample representativeness of voting population

Voter categoryColorado 2008

voting population Sample

Sex

Male 48.7% 48.7%

Female 51.3% 51.3%

Race

White non-Hispanic alone 84.7% 83.9%

Person of color 15.3% 16.1%

Age

18 to 24 10.0% 6.7%

25 to 44 35.0% 23.6%

45 to 64 39.3% 48.7%

65 to 74 11.3% 14.5%

75+ 6.4% 6.5%

Presidential vote

Barack Obama 53.5% 54.0%

John McCain 44.9% 44.4%

Political party

Democrat 32.9% 33.5%

Republican 33.2% 35.1%

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amendments on the ballot in 2008, the second most in the state’s history. They argued that voters were overwhelmed by the number of amendments and sim-ply voted no on every initiative, contributing to the defeat of the amendment. Respondents’ Amendment 46 vote was the primary outcome of interest in this research, and voting no straight down the ballot represents an instance of vot-ing behavior unrelated to attitudes toward the substance of the ballot initia-tive. To assess confusion about the intent of the initiative, we asked voters to report if they believed a yes vote was in favor of affirmative action or against it. This measure of confusion represented one predictor of substantive inter-est in this study. We also asked voters to report their political party affiliation and who they voted for in the 2008 presidential election. We collected these data to assess the extent of an “Obama bump” related to Amendment 46 vot-ing behavior. If, holding constant attitudes toward affirmative action, respon-dents were more likely to vote against Amendment 46 if they also voted for Barack Obama, the causal link between voter confusion and the Amendment 46 outcome could be confounded. However, we found no evidence of such an effect. Controlling for attitudes toward affirmative action, those who voted for Obama were no more likely to vote no on Amendment 46.

Influences of Various Campaign Activities and Public Media. Two of the questions on the survey asked respondents to indicate how frequently they consulted a variety of sources to gather information about the initiative and how cer-tain campaign activities influenced their vote. Exploratory analyses suggested responses to certain prompts in these questions were correlated. Specifically, three sources were associated with independent consultation of information regarding Amendment 46 (print and broadcast news, online sources, and friends and family), while four dealt with the consultation of formal voting recommendations (unions or professional organizations, political parties, reli-gious organizations, chambers of commerce). Moreover, an additional set of seven options was related to the influence of campaign activities. To reduce the data gathered via these questions, we used principal components extrac-tion to create three standard normal composite scores: INFOIND, INFOREC, and CAMPAIGN. To better isolate the effect of potentially confusing initiative language, we used the factor scores derived from these principal components analyses as statistical controls in our models of voting behavior. We took this step to address the concern that our estimate of the effect of confusion could be confounded by voters’ interactions with information, recommendations, or campaigning surrounding Amendment 46.

Demographic Information. Socioeconomic characteristics can affect voting behavior (Rentfrow, Jost, Gosling, & Potter, 2009). To control for this effect, we gathered detailed demographic information from each respondent.

Measuring Attitudes toward Affirmative Action. Attitudes about affirmative action cannot be observed directly. Exploring these attitudes with survey

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items that directly ask if participants support affirmative action oversimpli-fies a complex question and tends to yield unstable sample-dependent results (Wright, 1994, Wright & Linacre, 1989, Wright & Panchapakesan, 1969). To address this issue, we used a Rasch (1960) model approach to survey design. This methodology employs a battery of survey items that elicit observable responses via direct questioning to estimate an unobservable trait—such as an individual’s attitudes toward affirmative action. We developed the Survey of Attitudes toward Affirmative Action (SAAA), largely informed by Wilson’s (2003, 2005) construct modeling approach to measurement, which allowed us to link voter responses on our survey items to a theoretical model of attitudes toward affirmative action. We then placed voters’ responses on a common psy-chometric scale to extricate the nuances of voters’ perceptions of affirmative action and its associated policies. We summarize our theoretical model of atti-tudes toward affirmative action in figure 3.

Development of both the theoretical model in figure 3 and the survey items relied heavily on input from national policy makers and scholarly literature regarding the affirmative action debate (Crosby & VanDeVeer, 2000; Moses, 2002; Young, 1990). To aid in survey development, we conducted ten cognitive interviews5 and a pilot study of fifty-eight individuals prior to the full survey administration. These steps helped us refine the SAAA to more precisely mea-sure the intended trait. For example, initial iterations of the SAAA included “neutral” response options for prompts requiring respondents to articulate their beliefs about affirmative action. We found that neutral answers often sig-naled respondents’ discomfort with answering questions about a controversial topic, rather than providing valid information about their attitudes toward affirmative action. As such, we removed this response option and instead asked respondents’ to indicate a level of agreement with each prompt (strongly dis-agree, disagree, agree, or strongly agree). Results from psychometric analysis demonstrate that items have a high level of internal consistency (Cronbach’s ∝ = 0.87).6

Analytic ApproachOur investigation of voter attitudes toward affirmative action and voting pat-terns on the Colorado Civil Rights Initiative utilized four analytic strands. First, using item response theory (Hambleton, Swaminathan, & Rogers, 1991), we examined the general patterns in voter attitudes and the psychometric charac-teristics of each item on the SAAA. Second, we compiled basic descriptive sta-tistics focused on the distribution of Amendment 46 votes and the prevalence of confusion surrounding the intent of the amendment. Third, we estimated binary logit models to determine which factors significantly influenced the Amendment 46 vote. Finally, we evaluated responses to our open-ended sur-vey question, which asked respondents to describe the text of Amendment 46 in their own words.

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Results

Item AnalysisWe applied the Rasch partial credit model (Masters, 1982) to estimate vot-ers’ attitudes toward affirmative action. This technique is particularly useful because it models the probability of a given item response as a function of both a respondent’s attitudes (represented by the common psychometric con-vention, θ) and the item’s “difficulty.”7 Item difficulty estimates are derived empirically, and, in a traditional testing context, an item’s difficulty estimate can be interpreted as the knowledge and skills required to answer that item correctly. Simply put, difficult items are those that very few people answer cor-rectly. Easy items are those that most people get right. Similar principles apply in a survey of attitudes, such as the SAAA. In this context, difficult items are those where very few people strongly agree and easy items are those where more people strongly agree. For example, empirical results suggest that an item asking about the relationship between gender and educational opportu-nity is quite difficult. Very strong positive attitudes toward affirmative action

FIGURE 3 Theoretical model of attitudes toward affirmative action

Level 4—Strong supporter of affirmative action

•Prioritizes equality of opportunity and egalitarian conceptions of justice

•Strongly supports the use of compensatory programs as one way to achieve those principles

•Believes diversity is a worthwhile end and a relevant qualification

Level 3—Moderate supporter of affirmative action

•Supports but does not prioritize equality of opportunity and egalitarian conceptions of justice

•Supports the use of compensatory programs to achieve diversity and ameliorate current and past injustices

•Believes diversity is a worthwhile end

Level 2—Moderate opponent of affirmative action

•Recognizes structural inequalities but prioritizes fairness and meritocracy

•Does not support the use of compensatory programs if they compromise the principles of fairness and merit

•Believes diversity is valuable if it does not compromise the principles of fairness and merit

Level 1—Strong opponent of affirmative action

•Prioritizes fairness and meritocratic conceptions of justice•Believes that a lack of formal barriers provides adequate

access for all individuals•May conceive of affirmative action as reverse racism•Believes diversity is not a valuable end

Note: For a full list of the items included in the SAAA, see Moses et al. (2010).

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are required for a respondent to strongly agree with the following statement: “An individual’s gender has a meaningful impact on their educational oppor-tunities.” Only 7 percent of respondents strongly agreed. Conversely, an item asking about the benefits of racial diversity in university settings is among the easiest on the SAAA. A respondent does not need to hold exceptionally strong positive attitudes toward affirmative action to strongly agree with the follow-ing statement: “A racially diverse student body is something universities should try to achieve.” In fact, 27 percent of respondents strongly agreed with that statement.

Estimates of item difficulty from the Rasch model are useful because they can help us assess the palatability of various statements about affirmative action. Generally, items focused on the value of diversity were relatively easy, while items focused on meritocratic ideals and perceived negative consequences of affirmative action were more difficult (see Moses et al., 2010, for additional detail). These findings may inform messaging related to future affirmative action initiatives, because items that are “easy” relative to the others represent the arguments most palatable to voters. Two caveats are important to note here. First, we did not probe cognitive interview respondents regarding the palatability of each affirmative action prompt. Second, we did not link respon-dents’ political parties or presidential votes (nor did we measure political ide-ologies) to the estimated difficulty of individual SAAA items. Although these steps represent research foci outside the scope of this paper (e.g., the rela-tionships between political ideologies and affirmative action attitudes), sub-sequent research studies may pursue these ideas in more depth to determine why certain elements of affirmative action and equal opportunity are more or less palatable.

Descriptive Statistics The first step in our analysis of the link between voters’ attitudes toward affir-mative action and voting behavior involved examination of basic descriptive statistics. Table 3 summarizes voters’ attitudes toward affirmative action (θ) as a function of voting behaviors and political party affiliation. This measure is normally distributed with a mean of 0 and a standard deviation of 1. Higher values of θ are associated with more positive attitudes toward affirmative action; lower θ values are associated with more negative attitudes.

In our sample, attitudes toward affirmative action are strongly related to political partisanship and demographic variables. Democrats had significantly more positive attitudes than Republicans, and women and people of color had more positive attitudes than men and white respondents, respectively. The relationship between affirmative action attitudes and voting behavior is not as strong as one might expect if Amendment 46 is an indicator of attitudes. How-ever, we found that the difference between those who voted in favor of elimi-nating affirmative action (a yes vote) and those who voted against eliminating affirmative action (a no vote) is less than half of the difference between Demo-

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crats and Republicans. This suggests voting behaviors may be driven by factors other than attitudes toward affirmative action.

If Amendment 46 were a valid and genuine reflection of voters’ attitudes toward affirmative action, we would expect to find a monotonic relationship between voting behaviors and θ for all respondents. This is not what we found. Many respondents with positive attitudes toward affirmative action reported casting a yes vote on Amendment 46, thereby supporting the elimination of affirmative action policies in Colorado. This raises questions about factors that moderate the relationship between attitudes toward affirmative action and vot-ing behavior on the Colorado Civil Rights Initiative.

Table 4 presents response patterns for individuals on the basis of their vot-ing behavior and their understanding of the meaning of a yes vote: 261 voters reported that when they voted, they believed a yes vote was in favor of affirma-tive action, and 46 were unsure about the amendment’s intent. Regardless of

TABLE 3 Mean θ values and standard deviations by voting behavior and political party affiliation

Political party

Voted no Voted yes Overall

Mean SD Mean SD Mean SD

Republican –0.26 0.85 –0.20 0.69 –0.25 0.72

Democrat 0.91 0.87 0.55 0.76 0.64 0.81

Independent 0.25 1.05 0.08 0.72 0.12 0.79

Total 0.35 1.03 0.09 0.80 0.14 0.86

TABLE 4 Reported voting behavior by perceived outcome of Amendment 46

Vote on Amendment 46

Perceived meaning of a yes vote

In favor of affirmative

action

Against affirmative

action Unsure Refused Total

Yes (prohibit affirmative action) 232 118 36 9 395

No (preserve affirmative action) 29 69 10 4 112

Total 261 187 46 13 507

Copyright © 2010 Michele S. Moses.

Source: Moses et al. (2010), p. 5.

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whether or not voters intended to support affirmative action, more than half of the sample was confused about the meaning of the amendment.

To account for the 52 percent of voters who misinterpreted the amend-ment, we created a variable to approximate each voter’s intended support of affirmative action. For example, we coded voters who indicated that they voted yes on Amendment 46 and that a yes vote was in favor of affirmative action as intending to support affirmative action. Whereas we coded voters who indi-cated that they voted yes and that a yes vote was against affirmative action as not intending to support affirmative action. Table 5 presents the relationship between reported voting patterns and the intent to support affirmative action. Here we see that more than two-thirds of the sample intended to support affirmative action programs on Election Day. We also found that confusion was directional, with considerably more voters voting yes when intending to preserve affirmative action than those voting no when intending to prohibit it.

Statistical Models of Voting BehaviorTo estimate the probability of a yes vote on Amendment 46, we used binary logistic regression. It is important to clarify that for the purposes of these analyses, the outcome (Yv) is an actual yes vote on Amendment 46—not an intended yes vote.

P(Yv = 1) =

In the model, Yv is a dichotomous variable that takes a value of 1 if voter v votes yes on Amendment 46, and 0 otherwise. The independent variables of substantive interest in our model are attitudes toward affirmative action (θ), confusion over the intent of the ballot initiative (CONFUSION), and the inter-action between affirmative action attitudes and confusion (θ*CONFUSION). We also included a set of control variables thought to be related to voting behavior: college education, independent consultation of information regard-ing the amendment, consultation of formal voting recommendations, and the influence of campaign activities. All independent variables are included in the vector Xv. β is the vector of parameters associated with Xv. Table 6 presents the parameter estimates associated with all independent variables included in the model.

Results suggest that confusion exerts a powerful influence on voting behav-ior. All else equal, someone who was confused about the intent of Amendment 46 was nearly 4.5 times more likely to vote yes than someone who was not confused. There is also evidence of an interaction between attitudes toward affirmative action and confusion, where the effects of confusion are magni-fied for individuals with extremely positive or negative attitudes. This relation-ship should not be too surprising; if a voter favored affirmative action and believed Amendment 46 would preserve it, she was highly likely to support

exp(βXv)

1 + exp(βXv)

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the measure. However, this interaction effect also illustrates a critical finding. Not only was confusion about the intent of Amendment 46 widespread, it was also directional. Figure 4 presents two curves: one represents voters who were confused, and one represents voters who were not. In the figure, δ represents the estimated effect of confusion on the probability of a yes vote for the typical confused voter, conditional on attitudes toward affirmative action.

TABLE 5 Reported voting behavior by intent to support affirmative action

Vote on Amendment 46

Intended support of affirmative action

In favor of Against Total

Yes (prohibit affirmative action) 232 118 350

No (preserve affirmative action) 69 29 98

Total 301 147 448



TABLE 6 Parameter estimates and odds ratios for model of voting behavior

95% confidence interval odds ratio

Independent variables βWald

χ2 Sig.Odds ratio Lower Upper

(Intercept) 0.93 8.28 0.004 2.53

θ –1.88 29.44 0.000 0.15 0.08 0.30

Confusion 1.51 20.22 0.000 4.54 2.35 8.77

θ x Confusion 2.88 35.89 0.000 17.90 6.97 46.00

College graduate –0.75 4.84 0.028 0.47 0.24 0.92

INFOINDa -0.45 6.40 0.011 0.64 0.45 0.90

INFORECa –0.17 1.02 0.313 0.85 0.61 1.17

CAMPAIGNa 0.20 1.32 0.250 1.22 0.87 1.72


Source: Moses et al. (2010), p.19.

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We emphasize here two important nuances: few voters with negative feel-ings toward affirmative action were confused by Amendment 46, and the impact of confusion was much larger for voters who felt positively toward affir-mative action. These results further support the analysis presented in table 5, where respondents’ intended support of affirmative action is contrasted with their reported voting behavior. Confusion disproportionately affected those who intended to support affirmative action. While 80 percent (118/147) of respondents who did not support affirmative action voted in accordance with their belief (i.e., yes on Amendment 46), only 23 percent (69/301) of respon-dents who supported affirmative action reported voting in accordance with their belief (i.e., no on Amendment 46).

Open-Ended Response AnalysisFor the final substantive question of the voter survey, we read the text of Amendment 46 aloud to respondents and asked them to explain what it meant. We did not ask respondents to comment on the perceived impact of Amend-ment 46 relative to race specifically; rather, we simply asked that respondents

FIGURE 4 Predicted probabilities of a yes vote on Amendment 46 given attitudes toward affirmative action and confusion over initiative language



0

0.2

0.4

0.6

0.8

1

-3 -2 -1 0 1 2 3

Pro

bab

ility

of V

oti

ng

Yes

on

46


Not confused

Confusedδ

0

50

100

150

200

250

300

350

400

1960−1969 1970−1979 1980−1989 1990−1999 2000−2010

Nu

mb

er o

f In

itia

tive

s

Total Number

Approved

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explain the initiative text in their own words. To analyze voter responses to this question, three members of the research team independently coded a set of fifty responses; in comparing the codes applied to these responses, our mea-sure of inter-rater reliability—Fleiss’ kappa (Fleiss, 1971)—was 0.83.8 Once sufficient levels of agreement were demonstrated, the remaining 457 voter responses were divided among the three raters for subsequent coding.

Alarmingly few voters accurately explained the meaning of Amendment 46 and its implications. Table 7 presents the results from the coding of open-ended responses. Consistent with the results from the other analyses, only 28.2 percent of respondents were able to clearly articulate the meaning and impact of the text. For example, one respondent noted that Amendment 46 meant “the government shouldn’t involve themselves to help make relationships.” Another expressed uncertainty more explicitly: “Well, to start with, I would have said, discriminate, but you said, ‘or grant’ . . . Can you read that again? It almost sounds like we will do nothing either way.” Just over 5 percent of respondents stated that the amendment would protect affirmative action or equal opportunity policies. One respondent was quite succinct in his inter-pretation: “I say it would protect affirmative action.” Another respondent who believed Amendment 46 would support affirmative action said the initiative would create “a more level playing field for everyone . . . black, white, Asian . . . all ethnicities as well as both genders.”

The vast majority of voters (66.3%) restated the initiative in a way that did not allow us to determine the perceived impact on affirmative action. For example, one respondent noted, “It means that it would be illegal for

TABLE 7 Results from coding of open-ended responses regarding the meaning of Amendment 46

Coded responses – Restatements of Amendment 46 TextPercent of respondents

with this code

Perceived impact of Amendment 46 on affirmative action:

Preserve affirmative action 5.5%

Prohibit affirmative action 28.2%

Unclear from response given 66.3%

Other coded responses:

Mentioned affirmative action explicitly 13.6%

Mentioned discrimination 30.2%

Mentioned preferences, preferential treatment, or similar 11.8%

Cited protection for groups not included in the initiative 14.8%



455


an employer or university to discriminate based on color or sex.” Another stated, “We should not discriminate against race or gender,” with yet another echoing, “Nobody should be discriminated against based on their color or sta-tus or anything.” In addition, our analyses suggest that although the initiative text prohibits both discrimination (e.g., explicitly barring access to education, employment, or contracting for certain races) and preferences (e.g., granting college applicants additional consideration in the admissions process based on their race), voters seem to connect more deeply with the concept of dis-crimination. In restating the initiative, 11.8 percent of voters mentioned pref-erences or preferential treatment, while 30.2 percent referenced discrimination. For example, one respondent stated, “It means that no employer should not be allowed to discriminate on an employee if the employee can perform the job.”

Finally, a large group of voters (nearly 15%) specifically cited the initia-tive’s impact on a group of citizens not included under Amendment 46. For example, voters repeatedly described the initiative as prohibiting discrimina-tion and/or legally protecting individuals on the basis of socioeconomic sta-tus, religion, age, and sexual orientation. For example, one respondent stated “that the government cannot discriminate whether a person’s race/ethnicity. When hiring they need to be fair whether they are male or female or creed, what have you, including sexual orientations.” Another explained that “busi-ness should not discriminate against anyone on race, sexual, orientation, age, color, and obesity. Looking at you they can see these things. If they are gay or lesbian they should not be discriminated against simply because of this. If they are not performing their duties that is another story. If they are doing what is expected they should not be fired.”

It is intriguing that nearly 15 percent of respondents mistakenly interpreted the Colorado Civil Rights Initiative to be relevant to other civil rights issues that constitute a significant part of the political discourse. Our study was not designed to examine why voters may conflate policy initiatives like affirmative action and marriage equality, but subsequent research efforts should examine this issue in greater depth.

Discussion and Conclusion

This article contributes to a growing body of literature that explores the trend of ballot initiatives that affect education policy. The initiative process has grown in frequency and influence in recent years. Ballot initiatives have become a means for citizens to enact legislation and amend state constitutions without the legislature. Although state ballot initiatives have received signifi-cant attention in the past decade from political scientists, they have yet to be examined adequately in the context of education.

Our analysis of the Colorado Civil Rights Initiative is relevant to the affirma-tive action debate. First, we developed a reliable instrument—the SAAA—that

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may be used in future research to gauge groups’ attitudes toward affirmative action. We are not aware of any other survey tool that serves this purpose. Repeated administration of SAAA items in the future will help further estab-lish its validity for making inferences about voters’ views on affirmative action. We believe valid measurement of voters’ attitudes is critical for research on an issue that continues to court controversy and litigation. It will be difficult to determine whether ballot initiative results fairly reflect voters’ attitudes with-out rigorous measurement of those attitudes; the SAAA takes an important first step in this direction.

More importantly, our analyses show that both attitudes toward equal oppor-tunity and amendment language had a profound impact on Amendment 46 outcomes. Further, the significant interaction between voter attitudes and the amendment language suggests that, holding attitudes about affirmative action and demographic covariates constant, those who misunderstood the intent of Amendment 46 were considerably more likely to vote yes. We also find that voters with more positive attitudes about affirmative action were more likely to report being confused.

Our results provide empirical evidence to support anecdotal claims of voter confusion. Opponents of state anti–affirmative action “civil rights initiatives” frequently contend that supporters deliberately use misleading language to confuse voters (Frosch, 2008). Those in favor of affirmative action policies point to the similarity of ballot language to the Civil Rights Act as one example of misleading language (Colorado Unity, 2007; Michigan Civil Rights Com-mission, 2006). They argue that it is intentionally designed to make voters believe they are voting in favor of traditional antidiscrimination legislation. In response, some proponents claim that voters are not confused about the initia-tive, and others argue that confusion affects voters on both sides of the cam-paign and does not disproportionately affect supporters of affirmative action.

Our findings suggest that confusion was widespread, that it disproportion-ately affected affirmative action supporters, and that it nearly resulted in a different outcome on Election Day. Our results also suggest that Coloradans intended to support affirmative action. Thus, we believe that if Colorado’s Civil Rights Initiative had been a clearly worded referendum on attitudes toward affirmative action, it would have failed by a wide margin. Had a much larger percentage of Coloradans voted no on Amendment 46, it is possible that enthusiasm for like-minded initiatives in other states would diminish.

Only if voters know what they are voting for and understand the likely effects can the results of ballot initiative elections accurately reflect the will of the people. This may suggest the need for increased voter education and more substantive coverage by the media to draw attention to the true mean-ing of initiatives (Moses & Saenz, 2008). Better yet, it can be seen as a call for clarity in the election process, particularly when the stakes are this high. As voter referenda on affirmative action move toward the forefront of public debate with the pending Supreme Court case Schuette v. Coalition to Defend Affir-

457


mative Action, it is even more important to gain clarity about the initiatives in question.

At a minimum, our findings suggest the need for clarity in ballot initiative text. However, they also caution against the use of ballot initiatives to make decisions that disproportionately affect vulnerable populations. We argue that high school–age students of color seeking admission to universities fall within this category. Furthermore, our findings highlight the potential dilemma that occurs when education policy—something that is critical to the future of our democracy—is determined by political processes that are not transparent and do not accurately reflect the opinions of the voters. These results do not, how-ever, address whether ballot initiatives are appropriate when they do reflect societal opinion but also disproportionately affect minority groups. We none-theless urge voters and policy makers to consider the implications of educa-tion ballot initiatives—and any potential prohibition of affirmative action—on democracy, equal educational opportunity, and justice.

If education is to serve democratic purposes, policy decisions must be made with special attention to equality and justice and consider the needs of all students. Our research provides evidence that ballot initiatives may not be functioning appropriately for educational policy decisions because there is a discrepancy between voters’ intentions and behavior. Studies like ours are important if we seek to shine a light on the benefits and consequences of direct democracy as an education policy-making tool and should be consid-ered as we explore the implications of ballot initiatives and their effects for underrepresented students.

Notes1. As recently as 2008, a citizen-initiated ballot initiative in Oregon would have prohibited

teaching in any language other than English for a period greater than two years (Ore-gon Secretary of State, n.d.). Although that initiative was unsuccessful, similar measures have passed in Arizona (Proposition 203), California (Proposition 227), Massachusetts (Question 2), and Colorado (Amendment 31) (Ballotpedia, n.d.a.).

2. In 1994, by a margin of just over 3,000 votes, Idaho voters defeated Proposition 1, an initiative that stated that “elementary and secondary school educators shall not discuss homosexuality as acceptable behavior; . . . and limiting to adults access to library mate-rials which address homosexuality” (Idaho State Policies Regarding Homosexuality, n.d.). Similar initiatives have appeared in Oregon (Measure 9) and Colorado (Amend-ment 2), in addition to a handful of state citizen-initiated measures that generally pro-hibit the inclusion of sexual orientation in antidiscrimination laws (Ballotpedia, n.d.b.).

3. Arizona, Arkansas, California, Colorado, Florida, Illinois, Massachusetts, Michigan, Mis-sissippi, Missouri, Montana, Nebraska, Nevada, North Dakota, Ohio, Oklahoma, Ore-gon, and South Dakota.

4. Alaska, Arizona, Arkansas, California, Colorado, Idaho, Maine, Massachusetts, Michi-gan, Missouri, Montana, Nebraska, Nevada, North Dakota, Ohio, Oklahoma, Oregon, South Dakota, Utah, Washington, and Wyoming.

5. Cognitive interview subjects were selected purposefully so that our pool of interview-ees was diverse. Because our sample was small, confidentiality concerns limit the level

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of descriptive information we can report. Nevertheless, participants included both whites and minorities and also spanned a range of political ideologies, education back-grounds, and ages. We asked these voters to “think aloud” while responding to our survey items; their feedback allowed us to reword problematic items in advance of dis-tributing surveys.

6. There are no hard-and-fast rules for determining minimally acceptable values of coef-ficient alpha, but Ebel and Frisbie (1991) note that most published standardized tests yield scores with reliabilities in the 0.85–0.95 range. They also suggest reliability coeffi-cients of at least 0.85 are required if decisions are made about individual respondents; but if claims are made only about groups of respondents (as is the case with our analy-sis), the generally accepted minimum reliability is closer to 0.65. By either standard, the SAAA’s reliability estimates are acceptable.

7. Under the RPCM, each item has multiple parameters representing difficulty associated with moving from one response category to the next (e.g., Disagree to Agree). For ease of presentation, when referring to a single measure of an item’s difficulty, we are refer-ring to the trait level required to move from a Disagree to an Agree response to that item.

8. Fleiss’ kappa is often used to calculate agreement for more than two raters and can be interpreted as the percent of total agreement beyond what would be expected by chance. Although Fleiss’ kappa does not have a measure of significance, convention states that anything between 0.80 and 1.00 can be considered nearly perfect (Landis & Koch, 1977).

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