I. Introduction
As the “first national effort to ensure access [to health insurance] to the nonelderly population,” Reference Jacobs1 the Affordable Care Act (ACA) may well be “the largest change in social welfare policy since the Great Society and perhaps the New Deal.” Reference Jacobs2 Among its aims are insuring a large share of the uninsured, Reference Obama3 cutting insurance disparities along the lines of health status, 4 age, 5 and race/ethnicity, 6,7 and reducing households’ exposure to the financial vulnerabilities that illness entails. 8,Reference Himmelstein, Warren, Thorne and Woolhandler9 Thus, there is much to motivate research into the ACA’s potential for “durability” Reference Pierson10 —meaning both its avoidance of outright retrenchment, 11 and fidelity to its policy aims over time. Reference Hacker12
While some features of the ACA’s “design” Reference Campbell13 may dispose it to reap “positive feedback processes,” Reference Pierson14 as part II notes, other features may work against this prospect. Further, a policy’s design is not the only determinant of its trajectory, Reference Schneider and Ingram15,Reference Patashnik and Zelizer16 and it is hardly certain the ACA will generate such feedbacks. Reference Jacobs and Mettler17,Reference Sage18,19 As the ACA is implemented, it is surrounded by informal tools of political opportunity and challenge. 20 How its beneficiaries are portrayed is one such tool.
Past research on American social policy indicates that portrayals of a policy’s beneficiaries may relate to the responses the policy generates among those beneficiaries, the mass public, and political elites—actors all critical in policy implementation and durability. 21 At the heart of much of this work is Schneider and Ingram’s concept of the “social construction of target populations,” meaning the “characterizations or popular images of the persons or groups whose behavior and well-being are affected by public policy.” 22 Portrayals’ dynamics are complex. Policies may enjoy political stability when portrayals help underscore beneficiaries’ breadth, Reference Skocpol and Skocpol23,Reference Skocpol24 and “[a]rguments or images that spotlight social groups may activate stereotypes and prejudices” that “then become the dominant guideposts for the evaluation of public policy.” Reference Nelson and Kinder25 Simultaneously, policies curry strength and guard beneficiary interests when they encourage beneficiaries to see themselves as “politically meaningful” 26 groups, Reference Mettler27,28,29 and may lack political endurance when this is not the case. 30,31,Reference Soss, Fording and Schram32 Beneficiary mobilization is “not an automatic process,” 33 and “[l]egislative achievements remain…prone to being dismantled” Reference Mettler34 when intended beneficiaries have “barely offered more than tepid support.” 35 Such dynamics may matter greatly to the ACA as a law forged amid partisan strife 36 and repeatedly subject to Supreme Court scrutiny. Yet, no study to date has systematically described and analyzed ACA beneficiary portrayals. This paper does so. It first seeks descriptive answers to three questions about portrayals that the literature connects to policy durability: (1) Do portrayals depict ACA beneficiaries as economically heterogeneous? (2) Do portrayals focus attention on groups that have acquired new “political relevance” 37 due to the ACA? (3) What themes that have served as messages about beneficiary “deservingness” in past American social policy are most frequent in ACA beneficiary portrayals? It then assesses how the portrayal patterns uncovered in answering these questions may work for and against ACA durability, finding reasons for confidence and caution.
Specifically, this paper reports on portrayals of two ACA “target populations” before and during the first four months of the ACA’s first open enrollment period: those who are (or would be) newly eligible for Medicaid pending state expansion, and separately those eligible for the ACA’s insurance subsidies. A focus on these groups is logical since two major ways that the ACA aims to cover the uninsured are by offering (1) Medicaid to people up to 133 percent (“effectively 138 percent” 38 ) of the federal poverty level (FPL) who were not previously eligible for the program, and (2) subsidies to buy insurance to the uninsured at 100–400 percent FPL. Reference Jacobs39 While not the only means by which the ACA addresses uninsurance, these two mechanisms’ importance is underscored by their discussion among academics, 40 research institutes, Reference Price and Saltzman41,Reference Dorn, Holahan, Carroll and McGrath42,Reference Shartzer, Kenney, Long, Hempstead and Wissoker43 and courts, Reference Gostin and Garcia44,45 by the striking cross-state (and cross-time) variation in Medicaid expansion and exchange facilitation arrangements (see Table 1), 46,47,48,49 and by their inter-dependence. 50
Note: Medicaid decision data in this table are from http://kff.org/health-reform/state-indicator/state-decisions-for-creating-health-insurance-exchanges-and-expanding-medicaid/ and are as of November 2, 2015. This KFF webpage also provides data on exchange arrangements, but exchange data in this table are from page 56 of the report at http://www.ncsl.org/portals/1/documents/health/health_insurance_exchanges_state_profiles.pdf, and are as of October 20, 2015. While assembling the newspaper text data for this article, the author referred to Medicaid expansion decision data from June 2014 from http://kaiserfamilyfoundation.files.wordpress.com/2014/03/current-status-of-the-medicaid-expansion-decisions-healthreform1.png, and exchange arrangement decision data from May 2014 that were available on page 56 of the report previously found at http://www.ncsl.org/Portals/1/Documents/Health/Health_Insurance_Exchanges_State_Profiles.pdf.
This paper also reports on portrayals of two groups informally crafted by the ACA in this period: those gaining health insurance (insurance-gainers) due to the ACA, and those losing it (insurance-losers). The latter emerged as a category during HealthCare.gov’s rollout, as well illustrated by a document entitled “‘Because of Obamacare…I Lost My Insurance”’ that circulated among ACA opponents in Congress in November 2013. Reference Lipton and Stolberg51 For brevity, this paper refers to the newly Medicaid-eligible, subsidy-eligible, and insurance-gainers collectively as ACA “beneficiaries,” in the sense used by others. 52
The portrayals reported come from an original dataset of newspaper article text applicable at the state level from August 1, 2013 through January 31, 2014, gathered retroactively on February 3, 2014. (Citations for the newspaper articles used to build this paper’s data are not included in the bibliography but are available by request). The ACA’s first open-enrollment period officially ran October 1, 2013 to March 31, 2014, with a brief Special Enrollment Period thereafter. 53 The data thus begin two months before, and run four months into, this first open enrollment period. For this reason and others that part IV notes, the timeframe studied is a critical one in the ACA’s implementation.
To preview the results, the data suggest that portrayals underplay beneficiaries’ economic heterogeneity, pay little attention to young adults—a key group the ACA makes politically relevant—and emphasize themes of workforce participation, economic self-sufficiency, and insider status, giving little attention to health status, age, gender, and race/ethnicity. These three descriptive findings—assessed through the lens of existing literature—suggest reasons for both expectancy and caution regarding the ACA’s durability. Favoring durability is the finding that beneficiaries are depicted in terms associated with deservingness in past American social policy—particularly being cast as workers and insiders. Yet, there are three broad reasons for caution. First, ACA insurance-losers are also portrayed as deserving. Second, it is unclear how the portrayal patterns found may impact the durability of the ACA’s efforts to cut insurance disparities by age, health status, and especially race/ethnicity. Third, portrayals’ strong casting of beneficiaries as workers, and limited attention to beneficiaries’ economic heterogeneity and to young adults, may do little to help the ACA cultivate beneficiaries’ political engagement.
II. Background: motivations and foundational literature
A key part of the ACA’s design that may support durability is that it is in many ways what Skocpol terms a “[c]ross-[c]lass [s]ocial [p]olic[y].” 54 Skocpol and others 55,Reference Jacobs and Skocpol56,57 note that the ACA is a “[r]edistributive [r]eform” Reference Skocpol58 in granting “subsides to millions of working people of modest means.” 59 It also includes features focused on cutting disparities. 60,61 Simultaneously, subsidies go to middle-income earners. 62,63 President Obama has appealed to the mass public for “‘help in spreading the word”’ on how the ACA “‘can make a difference in your lives and the lives of your families,”’ 64 and the ACA by some estimates may benefit the “vast majority of Americans.” 65 Cross-class policies tend to enjoy notable spans of political success. 66,Reference Katz67 They are administered in non-stigmatizing ways, 68,69 foster political participation by beneficiaries of all income levels, 70 and arrange at least latent coalitions of low- and middle-income earners. Reference Weir, Orloff, Skocpol, Weir, Orloff and Skocpol71,Reference Skocpol and Skocpol72 Scholars argue that the latter’s stake as beneficiaries bolsters Social Security, 73,Reference Skocpol and Skocpol74 Medicare, Reference Oberlander75 and Medicaid. Reference Olson76 Neckerman, Aponte, and Wilson argue that programs “available to working- and middle-class segments of society as well as to the poor, are more likely to attract political support, and therefore more generous and stable funding.” Reference Neckerman, Aponte, Wilson, Weir, Orloff and Skocpol77 Greenstein argues that policies are politically stronger when—like the ACA in some respects—they “do not separate those modestly above the poverty line from those well below it” but rather “combine these two groups.” Reference Greenstein, Jencks and Peterson78
Yet, another part of the ACA’s design may work against beneficiary mobilization and mass support: many of its benefits are what Mettler calls “submerged.” 79 Unlike Social Security, whose “stakes are high and clear,” 80 submerged benefits “leave much of the public, even beneficiaries themselves, unaware of government’s role, incognizant of…what is at stake… and unengaged and unlikely to take action.” 81 Individuals’ “awareness of government activity” is key in fostering positive policy feedbacks; 82 but, “unlike visible policies that…attract group loyalty, policies of the submerged state are…too hidden…to generate such affiliations.” 83 Mettler notes that if a policy “neglects to reveal to citizens what government will do or has done on their behalf, it may….prove unsustainable, as opponents dismantle it or undermine implementation.” 84 Mettler 85 and Patashnik and Zelizer 86 explicitly worry that these concerns apply to the ACA.
Given these cross-cutting considerations, influences on the ACA’s trajectory other than its design may be pivotal. Political context matters to policy durability. 87 An informal but potent influence on a policy’s course may reside in how beneficiaries are discussed and portrayed. 88,Reference Winter89,90 Certainly, non-portrayal factors also matter, including political institutions, Reference Weir, Orloff, Skocpol, Weir, Orloff and Skocpol91,92,93 coalitions, Reference Weir, Orloff, Skocpol, Weir, Orloff and Skocpol94,Reference Finegold, Weir, Orloff and Skocpol95,Reference Myles, Weir, Orloff and Skocpol96,97 “voluntary groups,” 98 regional economies, Reference Quadagno, Weir, Orloff and Skocpol99,100 and others articulated by Pierson, 101 Greenstein, 102 and Patashnik and Zelizer. 103,Reference Patashnik and Zelizer104 Yet, as discussed below, portrayals relate to a policy’s reception among intended beneficiaries, the mass public, and elites. And critically, portrayals may impact beneficiaries’ participation in political institutions and coalitions, 105,Reference Ingram, Schneider, Schneider and Ingram106,Reference Soss107 thus setting—like prior policies do 108 —the terms on which these other influences on a policy’s course operate. For all of these reasons, ACA beneficiary portrayals deserve study.
Portrayals also merit attention because three factors make the ACA vulnerable to the politics of target population constructions. First, the fact that the ACA is not universal, and does redistribute, makes it susceptible to a point made by Nelson and Kinder and echoed by Iyengar: Reference Iyengar109 “[g]roup-centrism is pervasive” in American politics. 110 “Many policies are…criticized on those grounds in public debate,” 111 potentially influencing mass opinion on the policy. 112 And, this criticism of policy can entail criticism of beneficiaries that discourages their program-specific and broader political participation. 113
Second, scholars suggest that beneficiary portrayals can play a role in bringing about an eventual, and potentially bipartisan, unravelling of policies embraced by only one party. For instance, Soss, Fording, and Schram argue that “[f]rom the 1960s on, conservatives brandished the troubled lives of the poor as evidence of liberal [policy] failure and as a wedge issue,” 114 and that parts of the 1996 Personal Responsibility and Work Opportunity Reconciliation Act responded to these portrayals, 115 replacing Aid to Families with Dependent Children with Temporary Assistance for Needy Families. There are likely examples with the left’s and right’s roles reversed in other policy areas. The ACA has faced strong Republican challenge from inception, 116,117,118 though the law also is not beloved by all Democrats. 119 Skocpol and others argue that “no one…should think…the battle is over” 120 simply because the ACA became law. 121,122
Third, as explained below, benefit take-up may be sensitive to portrayals, and take-up is critical to the ACA’s implementation. The possibility that “customers would not come” was a main concern of an executive branch official involved in implementing the ACA federal exchange. Reference Stolberg and Shear123 Low rates of Medicaid and subsidy take-up may especially hurt poorer states’ economies, 124 as these benefits are key routes by which the ACA stands to put money into states as others send it to the federal level. 125,126,Reference Dubay, Holahan, Long and Lawton127,128 Thus, intended enrollees not taking up these benefits is arguably functionally akin to states leaving “money on the table.” Reference Nicholson-Crotty129
A closer look at existing research unpacks how beneficiary portrayals may relate to a policy’s reception by beneficiaries, the public, and elites; how portrayals may bear on people’s thoughts about a policy; and why media portrayals are particularly important in these dynamics.
Routes by which social constructions shape politics
While it does not establish that portrayals are a causal “first mover,” research including but not limited to Schneider and Ingram’s finds portrayals linked to several phenomena that are important to a policy’s durability. These phenomena include take-up of the policy’s benefits, the policy’s support in the mass public, the policy’s treatment by political elites, and political participation by the policy’s beneficiaries.
Portrayals may encourage or discourage take-up in two ways. First, alongside a policy’s design and administration, beneficiary portrayals can signal whether a policy does or does not carry stigma. 130 Stigma can lead those eligible for benefits to shun them. 131,Reference Miller132,Reference Newman133 Citing Piven and Cloward, Neubeck and Cazenave in fact argue that public criticism of welfare recipients is aimed at eligible non-enrollees, who are thereby “discouraged from applying.” Reference Neubeck and Cazenave134 Second and simultaneously, beneficiary portrayals may be a piece of “political communication” that helps to “reveal what is at stake” where benefits are “submerged.” 135 Beneficiary descriptions may help underscore self-interest in a policy. Reference Jacoby136 This informational role may be critical to take-up and broader beneficiary support, as a policy can collapse when people who are its intended beneficiaries do not believe themselves to be so. 137,138
Portrayals may relate to a policy’s popularity in the mass public, 139,Reference Gilens140 which forms opinions about policies partly by considering whom they benefit. Reference Chong, Mutz, Sniderman and Brody141,Reference Gilens142,Reference Rodriguez, Laugesen and Watts143 “[S]ocietal support for…[a] program and its recipients” 144 gives elected officials “incentive to pay attention to” a program’s beneficiaries, 145 and can “set limits on” 146 the scope of retrenchment proposals. 147
Beneficiary portrayals may also relate to a program’s popularity with lawmakers and thus alterations in its design and funding. 148 While a “causal link between social constructions and policy designs is not inevitable,” Reference Nicholson-Crotty, Meier, Schneider and Ingram149 Rose and Baumgartner find that “[t]he portrayal of the poor as either deserving or lazy drives public policy,” specifically its “relative generosity… toward the poor.” Reference Rose and Baumgartner150 In the past, temporary press portrayals of seniors as “‘greedy geezers”’ coincided with policymakers reassessing public spending on this typically favorably viewed group. 151
Finally, portrayals can bear on a policy’s durability by joining other factors in signaling beneficiaries about their political status. 152,153,154 While again not proving causality, research supports Ingram and Schneider’s hypothesis of a positive correlation between favorable portrayals and political participation. 155,156 Beneficiaries of programs with favorably discussed target groups participate in politics at high rates, both in relation to the program and generally. 157,158 For instance, seniors “defend their programs, warning lawmakers through their participation not to tamper with Social Security and Medicare.” 159 And, “because seniors are a politically dominant group, their preferences on other issues also matter. Policy effects spill over.” 160 Recipients of programs whose beneficiaries are criticized do not, believing, as Soss and others 161 note, that policymakers “do not understand, care about, or respond to ‘people like them.”’ 162 Participatory differences may owe partly to administrators’ treatment of beneficiaries, 163,164 which in turn may owe to administrators’ several beliefs about beneficiaries. 165 These dynamics well reflect Ingram and Schneider’s argument that “social constructions of target groups…stimulate and advance the typifications, or cognitive models, carried along by institutions,” 166 having “enormous influence upon citizenship roles, group mobilization, and civic participation.” 167 To reiterate an earlier point then, portrayals may impact what Campbell calls “political inequality,” 168 and thus the terms on which multiple other influences on a policy’s path operate.
Evidence that social constructions can operate on thoughts about policy
Much of the preceding research on how social constructions matter in politics assumes, implicitly or explicitly, that social constructions operate on people’s thoughts in policy relevant ways. The “framing effects” literature offers empirical support for this assumption. Druckman and Chong distinguish “frames in communication” from “frames in thought.” Reference Druckman169,Reference Chong and Druckman170,Reference Chong and Druckman171 Frames in thought concern “what an individual is thinking” while frames in communication are “what a speaker says (e.g., the aspects of an issue emphasized in elite discourse).” 172 Scholars use “framing” in both senses and explain their intersection. Nelson, Oxley, and Clawson’s definition of framing as “the process by which a communication source constructs and defines a social or political issue for its audience,” Reference Nelson, Oxley and Clawson173 and definitions given by others, 174,Reference Druckman175 well highlight how “frames in communication” may impact on “frames in thought.” “If people can think about an issue…in multiple ways, they are susceptible to framing effects.” Reference Binder, Childers and Johnson176
Communication frames indeed matter in politics because they appear to impact frames in thought at least some of the time. Communication frames can “activate existing beliefs and cognitions.” 177 For instance, Nelson and Kinder as noted find that “[a]rguments or images that spotlight social groups may activate stereotypes and prejudices,” 178 an effect involving “emphasis frames” 179,180 that is also found by others. Reference Ben-Porath and Shaker181,Reference Palmer182,Reference Palmer183,Reference Mendelberg184 Such effects can be sufficiently strong that, as Nelson and Kinder say, “[g]roup sentiments…become the dominant guideposts for the evaluation of public policy,” 185 a point Jacoby also suggests. 186 While “not inevitable,” 187 elite—and arguably media—commun- ication frames can encourage this outcome. 188,Reference Ingram, Schneider, Schneider and Ingram189 Jacoby notes that elites may undertake framing efforts with political goals in mind. 190 Framing effects differ across people and contexts, 191,Reference Druckman192,Reference Chong and Druckman193,194,195,196,197,198 but effects such as stereotype activation can happen even when listeners are politically sophisticated or disagree with the frame. 199
Communication frames may also shape a policy’s meaning to beneficiaries. For instance, Soss finds that “[t]o many clients, news stories on welfare suggest that the degraded position they occupy in the program carries over to the rest of the polity. The stigmatizing discourse on welfare creates a bridge between their status as clients and…as citizens.” 200 This article does not claim to uncover frames or framing effects of the sort reviewed here, or of other sorts. 201,Reference Tversky, Kahneman, Kahneman and Tversky202 It aims simply to describe and analyze portrayals. But this literature suggests that if portrayals are seeds for communication frames, they could much influence the politics around the ACA.
The relevance of social constructions from the mass media
Schneider and Ingram identify the media as a key “carrier” of social constructions, 203,Reference Ingram and Schneider204 and the media have perhaps a dominant role in shaping and disseminating claims about policy beneficiaries. 205,Reference Ono and Sloop206 But, the focus here on portrayals of beneficiaries in the media requires a defense from two possible objections. First, a large literature finds the media exerting “minimal effects” on public attitudes. Reference Iyengar, Peters and Kinder207,208 Second, social constructions have other sources, including policy itself, 209,210,211 interactions of “policy, discourse, and the courts,” Reference DiAlto, Schneider and Ingram212 and political elites. 213
In response to the first objection, much research rejects minimal effects. Druckman suggests that studies of media communication have “cycled from maximal effects to minimal effects…to…indirect effects (i.e., agenda setting, priming, and framing).” 214 Zaller argues that media effects are tough to detect statistically precisely because “mass communication…exercises… power on an essentially continuous basis.” Reference Zaller, Mutz, Sniderman and Brody215 Cook contends that, in the U.S., news media “directly influence political elites: helping to…shape the context of one legislator asking another for support.” Reference Cook216 Cook’s arguments potentially qualify Jacoby’s indication that “frames typically originate with political leaders; the mass media serve as the ‘conduits.”’ 217 Cook posits that media “news presents and interprets…[governmental] actions by means of agreed-upon production values.” 218 And, Cook’s assertion that the media are an institution with “shared processes and predictable products across news organizations” 219 tempers the concern that the “fragmented media environment” Reference Bennett and Iyengar220 of today “foreshadow[s] a return to…minimal effects.” 221
In response to the second objection, constructions in other venues certainly matter. Yet, media frames may be more powerful than frames issued directly or only by, for instance, political elites. Iyengar, Peters, and Kinder, crediting Walter Lippmann, note that “media provide compelling descriptions of a public world that people cannot directly experience.” 222 Others note that news is the “primary source of information that people have as distant events unfold,” 223 and that media attention is “a key determinant of what makes it onto the public agenda.” Reference Armstrong, Carpenter and Hojnacki224
These claims all suggest that the media are capable—perhaps uniquely capable—of creating what Chong calls a “common frame of reference”—“an interpretation of an issue…popularized through discussion.” 225 Iyengar argues that “mass media news presentations loom as powerful vehicles for political framing effects.” 226 Nelson, Oxley, and Clawson make a similar point. 227 Media portrayals may self-reinforce over time. 228 DiAlto proposes that it is “discourse, perhaps most powerfully [supplied] by the mass media” that offers “rationale” for “[c]onstructions of deservedness and entitlement” in public policy. 229 DiAlto, in fact, argues that “[s]ocial constructions of group identity” can be “generated and transmitted by the media in its capacity as a moral entrepreneur.” 230 These messages reach the mass public and intended policy beneficiaries themselves. 231 For all of these reasons, media portrayals of ACA beneficiaries are the focus here.
III. Descriptive questions
A vast range of social constructions merit study and could shape an analysis of target population portrayals. The analyses here do not start from hypotheses about the content of ACA beneficiary portrayals. Rather, the goal is to first objectively describe those portrayals, with an eye toward answering the three questions stated in the introduction, and then assess the possible pros and cons of the answers uncovered for durability. Existing literature explains how these three questions are useful in understanding portrayals’ possible bearing on a policy’s strength, and offers guidance for detecting the answers to these questions in textual portrayal data.
1. Are ACA beneficiaries portrayed as economically heterogeneous?
As part II notes, a large set of scholarship argues that policies known to carry “cross-class” benefits enjoy broader mass support, 232,Reference Wilson, Jencks and Peterson233,234,235,236,237,238 and broader beneficiary political participation, 239 than those appearing to benefit only poorer Americans. (And policies seen as narrowly benefitting the wealthy may also be unpopular. 240 ) References to the range or mix of income levels to which a program gives benefits signal that a policy’s beneficiaries are economically heterogeneous. 241 Portrayals advancing the “political isolation of the poor…from the working and middle classes” would do the opposite. 242
2. Do portrayals of beneficiaries highlight groups to which the ACA gives new political relevance?
Another question in the literature, and one highly relevant to the ACA, 243 is whether a policy and the politics around it encourage beneficiaries to “identify themselves as [its] valued recipients.” 244 Policies can “stimulat[e] brand new social identities and political capacities,” 245 and gain political protection in the process, as documented in Campbell’s study of how Social Security made seniors “[o]nce the age group least likely to participate in politics…the most active.” 246 “Without a government policy…there [wa]s no politically meaningful senior ‘group.”’ 247 But “[o]nce governmental benefits [we]re conferred on the basis of age…the group ha[d] political relevance and [wa]s ripe for mobilization by policy entrepreneurs, interest groups, and political parties.” 248 Similar potential exists in the ACA in several ways. 249,250,251,252 To take one example, young adults may remain on parental insurance (if existent) up to age 26 under the ACA, Reference Sommers, Buchmueller, Decker, Carey and Kronick253 and are coveted enrollees in the insurance options the ACA organizes. 254,255 While engaging this group is not—as part VIII discusses—the only way the ACA may “make citizens,” 256 tracing mention of young adults is a start at gauging whether beneficiary portrayals are helping to foster newly “[p]oliticized social identities.” 257
3. What themes that have served as messages about beneficiary “deservingness” in past social policy are most frequent in ACA beneficiary portrayals?
A question scholars have scrutinized for virtually all policies is whether beneficiaries are cast as “deserving” or “undeserving.” Reference Schneider and Ingram258,259,260,261 Divisions between these categories “run like fault lines through the entire history of American social provision.” 262 Policies whose beneficiaries are understood as deserving tend to be popular with the mass public, 263 and those beneficiaries tend to exhibit “no moral qualms about defending the program.” 264 Policies whose beneficiaries are constructed as undeserving tend to be unpopular with the mass public 265 and beneficiaries themselves. 266 Before this question can be broached for the ACA, however, it is necessary to answer a more preliminary one: what themes that have served as messages about beneficiary “deservingness” in the past are seen in ACA beneficiary portrayals?
Past research indicates that messages about deservingness may take the form of portrayals that associate beneficiaries with “social groups” 267 or “subgroups,” 268 use “[p]ositive” or “[n]egative” constructions 269 or stereotypes of those groups to deem them (un)deserving, and operate on mass, elite, and beneficiary attitudes through framing mechanisms. 270 Citing Gordon, Reference Gordon271 Soss, Fording, and Schram observe that “[e]valuations of deservingness [historically] fell along many dimensions…often rooted in differences of gender, race, ethnicity, and religion.” 272 Alleged behaviors are another metric in evaluating deservingness. Reference Kim273 Past research indeed highlights several themes by which portrayals may send messages about deservingness.
One is through messages about whether beneficiaries engage in work and efforts toward self-sufficiency. Work strongly, perhaps centrally, 274 distinguishes the deserving in American social policy. Reference Piven and Cloward275,276,277,278,Reference Skocpol and Skocpol279,Reference Ikenberry, Skocpol and Skocpol280,281 Thus, “citizens and taxpayers” are considered deserving, 282 as are the “working poor.” 283,284,285 Schneider and Ingram’s “[a]dvantaged” category consists of those who are favorably constructed and includes “business, science, the military, [and] the middle class.” 286 Veterans are usually seen as deserving, Reference Amenta, Skocpol and Skocpol287,288,289,290,Reference Jensen, Schneider and Ingram291 as are those pursuing education. 292,293 While “‘the rich”’ and “‘Wall Street bankers”’ are often viewed unfavorably, 294 customers or “‘clients”’ 295,296,297 in the economy are constructed favorably. Especially in neoliberalism, the “competent and self-reliant market actor—working, investing, choosing, and assessing returns—is…synonymous with the good citizen.” 298 Those unable to “look out for their own interests” Reference Schriner, Schneider and Ingram299 or achieve “economic self-reliance” 300 are cast as the opposite. Indeed, Americans across the income distribution often see welfare recipients as undeserving, 301,302,Reference Quadagno303,304 along with the non-working “nonelderly, nondisabled poor,” 305 criminals, 306 and those with “‘vicious habits”’ 307 —such as alcohol or drug use 308 —believed to self-inflict dependency. 309
Whether beneficiaries are ‘‘insiders” or ‘‘outsiders” has also served as a signal of deservingness, with “ingroups” being considered deserving. 310 (Soss, Fording, and Schram in fact suggest that the “line between community members and ‘outsiders”’ historically formed a “moral distinction” alongside deservingness, drawn between people. 311 ) Certain words or phrases can convey assertions about whether beneficiaries are “insiders.” Winter notes that use of the “first person” and phrases like “our elderly” by elites discussing a policy signals that beneficiaries are “ingroups,” 312 as do comments associating the policy with “‘everyone,”’ the “national good,” and referencing “‘Americans…pull[ing] together for the common good.”’ 313 Ono and Sloop make similar observations about words such as “Californians” in newspapers in some circumstances. 314 While this article studies media remarks, Winter’s notes on the language of elected officials, and Ono and Sloop’s insights, are instructive in explaining one way to track references to “insider” status in the portrayal data.
Race is a uniquely strong cue in American politics, Reference Carmines and Stimson315,316 and one that may be invoked obliquely. Reference Mendelberg317,Reference Mendelberg318,319 Schneider and Ingram observe that racial and ethnic minorities have frequently been negatively constructed 320 as compared to Americans of European origin. 321 Other scholarship gives examples of these constructions, 322,323,324,325 and research finds beliefs about beneficiary race or ethnicity often twined with beliefs about whether benefits are deserved—a pattern that scholars have interpreted as evidence of “symbolic racism,” Reference Rabinowitz, Sears, Sidanius and Krosnick326 “racial resentment,” Reference DeSante327 and “welfare racism.” 328 Winter finds favorability to Social Security as an “earned” benefit linked not so much to its universalism but its association with “whiteness.” 329 Gilens and others present evidence that opposition to welfare is rooted in an interaction of negative racial stereotypes with beliefs that African Americans are beneficiaries. 330,331,332 Soss, Fording, and Schram report that welfare is more punitive where many beneficiaries are racial minorities. 333 Asian Americans, 334 Latinos, Reference Ana335 and immigrants Reference Hochschild, Chattopadhyay, Gay and Jones-Correa336,337,Reference Schneider, Ingram, Schneider and Ingram338 have often been defined as undeserving in being defined as “foreigners” 339 or “outsiders.” Soss, Fording, and Schram’s “Racial Classification Model” 340 posits that “race can operate below the level of conscious reflection” 341 as a “mental structure” 342 in all individuals’ beliefs and decisions. 343 In researching race and policy, it is important to study “how minorities are portrayed,” 344 and the many “implicit” forms racial references can take. 345,346,347,348 Such analysis is, however, beyond the methodology of the present article. As a start at preliminarily assessing whether race/ethnicity is salient in ACA portrayals, this article tracks the frequency of explicit references. (See the Appendix for a detailed methodological explanation.)
Portrayals of beneficiary gender have also carried implications about deservingness in U.S. social policy. Public assistance beneficiaries may be seen more sympathetically when female. 349,350 The United States once “came close to forging a maternalist welfare state” dedicated to “help[ing] adult American women as mothers or as potential mothers,” 351 and mothers tend to be positively constructed. 352 In contrast, “able-bodied” men on public assistance are especially considered to be the “‘unworthy’ poor.” 353 That said, women’s somewhat more favorable treatment in social policy is historically more typical for white than non-white women, 354,355,356,357,358 middle and upper income than poor women, 359 and married than unmarried mothers. 360,361,362 Thus, it is relevant to track women’s prevalence, and references to motherhood and families, in the data.
Messages about deservingness have also been carried in portrayals of vulnerability, especially rooted in age and health. Children Reference Skocpol and Skocpol363,364,365,366 and elderly people are treated as deserving, 367,368 as are the disabled, 369 with some caveats. 370,Reference Piatak371 Families are viewed favorably, 372 but single-parent households less so. 373,374,375
Table 2 summarizes the groups and behaviors used in past constructions of deservingness or lack thereof as suggested by the aforesaid literature, roughly identifying how groups, or groups qua behaviors, have been used as foils against each other in politics according to that literature. It is similar to Schneider and Ingram’s table of the positively and negatively constructed and includes groups (e.g. “The Rich,” “dependents,” Wall Street/“big” business) that they define, 376 but unlike their table ignores power. It is also similar to Kim’s table of traits and behaviors used as, essentially, signals of (un)deservingness, and attributed to people and groups in politics and media in the past. 377
Table 2 has caveats. First, constructions of deservingness change over time. 378,379 Second, there are historical exceptions to several groups’ placement, including immigrants, Reference Newton, Schneider and Ingram380 African Americans and Whites, 381,382 Asian Americans, 383 veterans, 384 and seniors. 385 Third, race/ethnicity references can overlap with insider/outsider references, 386,387 and are also “enmeshed” 388 with ideas about work. 389,390,391 And as noted, women’s and mothers’ perceived deservingness may vary by race, income, and marital status. Fourth, “[t]he ACA is disrupting long-standing patterns of American politics” 392 and so could alter the table.
IV. Data
This paper aligns with past research on portrayals in studying news, 393 newspapers, 394 and newspaper text. 395,396 Druckman finds that “television news and newspapers…do not drastically differ in terms of content” and that “newspapers, and not television news, play a significant…role in informing the electorate.” Reference Druckman397 Others concur. Reference Chiasson398 Schneider and Ingram identify text as a source of portrayal data, 399 and Oberlander also indicates that the “vocabulary” used in describing a policy’s beneficiaries is a key influence on how they are politically understood. 400
Newspaper articles discussing those eligible for Medicaid and/or subsidies under the ACA were collected through LexisNexis Academic, retroactively on February 3, 2014. Articles identified as relevant to a state include those in newspapers based in that state, and those that mention that state printed in out-of-state papers, according to LexisNexis. The articles should thus reflect not only what residents may have read from state-based outlets, but what they (or elites or journalists) may have read about the state in other outlets. Complete search procedures are available on request. The search returned 8019 articles. The average number per state is 160.4 ( $\text{SD}=155$ ). California had the most (897), Delaware and Nebraska the fewest (18 each).
As noted, the articles run August 1, 2013 through January 31, 2014, starting two months before the first ACA open-enrollment period officially began and running through its first four months. This timing alone makes the period studied significant. At this time, many Americans first interacted with a major ACA policy output—insurance exchanges. Important pieces of the ACA that give it cross-class reach also took effect in this period. In these months, the ACA touched people with incomes well above the federal poverty line, with the initiation of subsidies on January 1, 2014, 401 and touched those just above and far below the poverty line with the Medicaid expansion also intended for January 2014. 402 This conveyance of “resources” likely helped the ACA begin to be “woven into the fabric of people’s lives” in a way that it was not in its initial years. 403 Also in these months, the ACA became squarely applicable to working-age Americans, beyond the young and elderly as in earlier years. 404
The months studied are also prime for research on beneficiary portrayals because in these months, news stories about people signing up for insurance under the ACA were salient insofar as HealthCare.gov was salient. New York Times articles from the last quarter of 2013—not drawn from the articles coded to build the text data for this article, any overlap being by chance—remarked on the “political crisis caused by…[the website’s] disastrous debut,” Reference Pear405 noting that President Obama “had to stand in the Rose Garden to apologize for a broken Web site.” Reference Johnson and Reed406 The website’s problems prompted several, visible, executive branch actions from October to December 2013. Reference Goldstein407,408,Reference Shear and Pear409 The timeframe studied here coincides with and extends just beyond these events. This salience means that the portrayals studied here are ones many citizens likely encountered and possibly “received.” Reference Zaller410
V. Methods
The Appendix provides a full description of the methods used to analyze the articles. In brief, the analysis included three phases. First, the author and graduate assistants manually coded select sentences in each state’s article batch for descriptions of each of the four groups: the newly Medicaid-eligible, the subsidy-eligible, insurance-gainers, and insurance-losers. For the first and third groups, coding excluded descriptions of people eligible for Medicaid prior to the ACA, joining it by what is known as the “woodwork effect.” Reference Blumenthal and Squires411 For all groups, references to national-level information were coded, but final coded material should otherwise describe only residents of the state at hand, not of other states. Consequently, when it appears in the data, a term like “Californians” should come from a California article and thus signal an “insider” portrayal in the sense discussed in part III. Second, I harvested the words thus coded for each of the four groups, placing them in four documents (“bags of words” Reference Grimmer and Stewart412,Reference Lucas, Nielsen, Roberts, Stewart, Storer and Tingley413 ) for each state. I then assembled four “corpus[es],” 414 one consisting of the 50 documents (one per state) describing the newly Medicaid-eligible, a second the 50 describing the subsidy-eligible, a third the 50 describing insurance-gainers, and a fourth the 50 describing insurance-losers. I ran each corpus through basic automated textual processing in R, making the unconventional choice not to reduce words to their roots and not to remove terms like “the,” numbers, and punctuation 415,416 in the interest of preserving information relevant to portrayals. I then generated four “document-term matri[ces]” (“DTMs”), 417,418 one consisting of the terms describing the newly Medicaid-eligible, one the terms describing the subsidy-eligible, one the terms describing insurance-gainers, and one the terms describing insurance-losers. A DTM reports each unique term in a corpus and its frequency by document. 419 Third, I manually assigned each term a “tag.” Tags mainly stem from the literature reviewed in part III. For instance, “his” and male names such as “jonathan” were tagged Male. The term “our” was tagged Strong Insider given Winter’s discussion of “our elderly.” 420 A “dictionary” 421 lists the terms receiving each tag. Dictionary 1 (see online Appendix 1) contains 40 tags, which appear in the left-most column of Table 3. I created five alternative dictionaries (described in online Appendix 2) since terms can be differently tagged based on analyst interest. Results reported in detail are those from using Dictionary 1. Part VI mentions two other dictionaries (3 and 5), described in the Appendix.
Note: Where no terms in the DTM received the tag, “no terms” appears; 0.000 is non-zero.
To check if results would systematically differ using a database other than LexisNexis, an assistant gathered articles for August 1, 2013 through January 31, 2014 from NewsBank for ten states. Articles were analyzed, as above, for portrayals of the subsidy- and newly Medicaid-eligible. As part VI reports, results differ little from those the LexisNexis articles yield.
VI. Results
Before answering the three questions set forth in the introduction and part III and assessing their implications, I report factual results for each DTM. Results are reported for the 50 states aggregated together. Since some articles appeared in the article batches of more than one state, the aggregate results up-weight portrayals that were more widespread. Although part IV makes clear that data were gathered at the state level, I do not assess cross-state portrayal variation. The ten-state NewsBank check is adequate only to tell us whether articles obtained through LexisNexis versus NewsBank would generate different results at the aggregate level. The NewsBank results suggest the answer is no; but, it is still possible that articles found through LexisNexis versus NewsBank carry systematically different portrayals at the state level. Whether this is the case requires study beyond this paper. By reporting results for the aggregate level, I report findings that the NewsBank check suggests would replicate reasonably well if articles were gathered through a database other than LexisNexis.
The newly Medicaid-eligible
The DTM for the newly Medicaid-eligible contains 1954 unique terms. Note that because punctuation was not removed before creating DTMs, terms that are the same but for punctuation variants count as unique; for example “younger” and “younger,” are two unique terms. The DTM contains 15,406 terms total (the sum of the number of times that each unique term appears). Using Dictionary 1, I tagged 4917 of these 15,406 terms and left 10,489 (68 percent) that were generic or ambiguous untagged. (A high proportion of terms is untagged across all dictionaries, and for all DTMs, since I did not drop numbers and words like “the” before generating the DTMs. The terms Dictionary 1 left untagged appear in online Appendix 1). The first column of Table 3 lists the proportion of terms falling under each tag for the newly Medicaid-eligible. Of the 4917 terms tagged, 941 (19 percent) were tagged Workers. (This figure derives from 66 unique terms tagged Workers, many of which appear in the DTM multiple times, together yielding 941 instances of the Worker tag.) In addition, 18 percent were tagged Poor/Very Poor, and 15 percent were tagged Strong Insiders. The remaining tags appeared less often, as seen in Table 3. For simplicity, I round percentages in reporting results within this article.
The results are similar when using the other dictionaries. Using Dictionary 3, the share tagged Workers falls to 16 percent and that tagged General Low Income rises to 11 percent, but Workers is still the most frequent tag. Only with Dictionary 5 is Workers not the most frequent tag; there, Poor/Very Poor is the most frequent (18 percent) followed by Strong Insiders (15 percent), followed by Workers (13 percent). Across all dictionaries, some ordering of Workers, Poor/Very Poor, and Strong Insiders are the three most frequent tags.
That said, the Poor/Very Poor tag’s frequency here, and in other results, may owe in part to two factors that analyzing the terms with different dictionaries cannot address. First, it may owe to the prevalence of simple, factual descriptions of the newly Medicaid-eligible as being at or below 133 or 138 percent of the federal poverty line. In Dictionary 1, 861 total terms (from 20 unique terms) were tagged Poor/Very Poor. The term “poverty” and its punctuation variants account for 483 of the 861 total terms, and the term “poverty-level” for one of these terms, equating to a non-trivial 56 percent. Yet, the remaining 377 total terms that received this tag come from the unique terms “homeless” “impoverished” “indigent” “neediest” “needy” “poor” “poorer” and “poorest” (or their punctuation variants), meaning at least 43 percent of this tag does not simply refer to the FPL. In particular, “poor” and its punctuation variants account for 287 of the 861 total Poor/Very Poor terms, and “poorest” an additional 60. A second possibility that using multiple dictionaries cannot address is that the Poor/Very Poor tag’s frequency stems in part from coders being unable to separate the newly Medicaid-eligible from the traditionally Medicaid-eligible and accidentally coding the latter in the text. If this is the case however, the mistake is likely indicative of how the newly Medicaid-eligible are perceived. (Note that the assistants involved in this coding had completed multiple semesters of masters-level public administration coursework and should be no less informed on the distinction than other newspaper readers.)
The subsidy-eligible
The DTM for the subsidy-eligible contains 2092 unique terms and 19,706 terms total. The second column of Table 3 lists the proportion of terms in each tag using Dictionary 1. I here tagged 5562 terms and left 14,144 (72 percent) untagged. The most frequently used tag is Workers (24 percent), followed distantly by Families (11 percent), Poor/Very Poor (10 percent), Customers/Clients (9 percent), and Strong Insiders (8 percent). Here, the term “poverty” and its variants drive the Poor/Very poor tag (over 91 percent of terms). Instances of the word “poverty” that occur due to explicit mentions of people with incomes falling between 100 and 400 percent of the federal poverty level would portray the subsidy eligible as cross-class. But, this would appear to be the case for at most 60 percent of the instances of “poverty” since the term “400” and its variants appear only 297 times in the DTM, while poverty and its variants, plus three instances of “poverty-level” together appear 492 times. Workers remains the most frequent tag when using the other dictionaries, and for five dictionaries, some ordering of Workers, Families, and Poor/Very Poor makes up the top three tags. The exception is that in Dictionary 3, the tag Cross Class is the second-most frequent (just under 15 percent), thus also supporting the possibility that there are references to the cross-class nature of this group; with this dictionary, Workers is still the most frequent tag, and Families the third most frequent.
NewsBank check for the newly Medicaid-eligible and subsidy-eligible
As noted, analyses of portrayals of the subsidy- and the newly Medicaid-eligible were also performed using articles located through NewsBank for ten states. I coded the DTMs obtained from this work using Dictionary 1, albeit that a small number of terms had to be assigned a tag here for the first time by virtue of not appearing in the LexisNexis articles. (Dictionary 1 in online Appendix 1 does not include these new terms; they are available by request.)
In the resulting Medicaid DTM, there are 747 unique terms and 4641 terms total, 66.5 percent of which were left untagged. For the 1556 terms tagged, top tags were Strong Insiders (20 percent), followed by Workers (19 percent) and Poor/Very Poor (18 percent). The top three tags are thus the same as in the Dictionary 1 LexisNexis results, although their ordering differs.
In the subsidy DTM from this work, there are 733 unique terms and 5287 terms total, 71 percent of which were left untagged. For the 1512 terms tagged, the top tags are Workers (25 percent), Families (13 percent), and Poor/Very Poor (12 percent). These results too are very similar to the Dictionary 1 LexisNexis results. Full NewsBank results are available on request.
Insurance-losers
The DTM for insurance-losers consists of 366 unique terms and 1354 terms total, 66 percent of which were untagged. The third column of Table 3 lists the proportion of terms in each tag using Dictionary 1. For the 456 terms tagged, Strong Insiders is most frequent (29 percent), followed by Workers (14 percent) and Customers/Clients (8 percent). Strong Insiders is the most frequent tag using any dictionary (29 to 30 percent of tagged terms in each case).
Insurance-gainers
The DTM for insurance-gainers consists of 1447 unique terms and 10,455 terms total, 48 percent of which were left untagged. The fourth column of Table 3 lists the share of terms in each tag using Dictionary 1. For the 5440 terms tagged, the tag Uninsured/Underinsured dominates by a wide margin (44 percent), followed distantly by Strong Insiders (16 percent), Weak Insiders (6 percent), and Workers (5 percent). Uninsured/Underinsured is the most frequent tag using any dictionary (42 to 44 percent in each case). In Dictionary 1, the term “uninsured” and its punctuation variants account for 98 percent of the 2387 terms with this tag.
VII. Discussion: answers to the three descriptive questions
We can now answer the descriptive questions about portrayals outlined above, and then discuss their implications in part VIII. To aid the discussion, Table 4 recaps the top three tags (using Dictionary 1) in portrayals of the newly Medicaid-eligible, subsidy-eligible, insurance-gainers, and insurance-losers. Figure 1 illustrates their proportions as a share of tagged terms.
1. Are ACA beneficiaries portrayed as economically heterogeneous?
Terms signaling income heterogeneity among ACA beneficiaries were tagged Cross Class. (See online Appendix 1 for details for Dictionary 1.) This tag is absent from Table 4. Under any dictionary, this tag accounts for less than 2 percent of tagged terms describing the newly Medicaid-eligible, and less than 1 percent of tagged terms describing insurance-gainers (and insurance-losers). It accounts for 15 percent of terms in the subsidy DTM when using Dictionary 3 but virtually the same share as in Dictionary 1 (2.4 percent) using the other dictionaries.
By definition, the newly Medicaid-eligible are those 138 percent FPL or below, so it is logical that Cross Class terms are infrequent in portrayals of this group. But the infrequence of cross-class terms in portrayals of the subsidy-eligible—at least absent strong assumptions about numbers—may signal an under-representation of the de jure cross-class nature (100–400 percent FPL) of this group in media portrayals. The infrequence of Cross Class terms in portrayals of insurance-gainers may also understate the prevalence of middle income earners in this group. Government data on the incomes of those receiving ACA benefits do not yet appear to exist, but estimates suggest that, among previously uninsured adults gaining insurance after the ACA, over 40 percent have family incomes ranging 139 percent to 399 percent FPL, and over 10 percent have family incomes at 400 percent FPL or more. Reference Shartzer, Long and Zuckerman422 Such figures reinforce arguments by Skocpol and Jacobs and others that ACA beneficiaries are economically diverse. 423 Yet especially for insurance-gainers, portrayals do not appear to underscore this economic heterogeneity, and so likely failed to help address indications that “many low to middle income Americans remained unaware of the law’s key features and were skeptical that it will actually help them” as of 2013. 424 Thus, portrayals may fail to help bestow on the ACA the political strength many find around cross-class policies.
An important caveat is the possibility that cross-class portrayals abound but are missed by the methods here. This would happen if cross-class markers largely surface in numbers rather than words, as the dictionaries (albeit #3) leave many numbers untagged since they are difficult to interpret without context. (And even Dictionary 3 leaves numbers lacking “$” signs largely untagged.) Fully detecting cross-class portrayals may require different methods.
2. Do portrayals of beneficiaries highlight groups to which the ACA gives new political relevance?
As noted in part III, the ACA gives new political relevance to being a young adult under age 26. The U.S. Department of Health and Human Services (HHS) reports that 28 percent of those who selected an insurance plan on ACA exchanges in the first open enrollment period were aged 18 to 34; 425 (age 18 to 26 data appear unavailable). Young adults were thus indeed a non-trivial share of exchange-based enrollees. Yet, references to young adults make up less than 2 percent of tagged terms in all four DTMs (albeit 2.2 percent of the subsidy DTM and 2.6 percent of the insurance-gainer DTM using Dictionary 3). Their infrequent mention suggests that ACA beneficiary portrayals from these months are unlikely to advance a perception—among young adults themselves, the mass public, or political elites—that young adults have what Campbell would call an “identity as a program clientele.” 426
The methods could miss some age references strictly carried in numbers. It could also be that portrayals of young adults were higher in 2010, when eligibility to remain on parental insurance took effect. 427 But even if this is so, the fact that attention to young adults apparently did not persist into 2013–2014 may be a finding in support of Jacobs’ warning that the ACA “may fall short of the mobilizing impacts documented by scholars of policy feedback.” 428
3. What themes that have served as messages about beneficiary “deservingness” in past social policy are most frequent in ACA beneficiary portrayals?
Table 4 suggests that messages about workforce participation, economic self-sufficiency, and insider status, are the key themes or routes through which portrayals may be signaling beneficiary (un)deservingness in the case of the ACA. As detailed above, the Workers tag is the most frequent tag in descriptions of the newly Medicaid-eligible and the subsidy-eligible, and the second most frequent in descriptions of ACA insurance-losers. The Poor/Very Poor tag is one of the three most frequent in portrayals of both the newly Medicaid-eligible and the subsidy-eligible, and the Customers/Clients tag is one of the three most frequent in portrayals of ACA insurance-losers. The Strong Insiders tag is among the three most frequent in portrayals of the newly Medicaid-eligible, ACA insurance-gainers, and ACA insurance-losers.
Other signals about deservingness discussed in part III—such as messages about health, age, gender, and race/ethnicity—appear relatively infrequent in portrayals of ACA beneficiaries, as seen in Table 3. Regarding health, the Bad Health tag applies to less than 4 percent of terms in each DTM, and the Good Health/Able Bodied tag to less than 1 percent of terms in each DTM.
Age-related tags are absent from Table 4. Beyond Young Adults, the Near Elderly tag makes up less than 1 percent of tagged terms in each DTM when using Dictionary 1, even though this group may particularly stand to benefit from ACA regulations. 429,430 Adults is the most frequent age tag in portrayals of the newly Medicaid-eligible (7.4 percent of tagged terms) and of insurance-gainers (3.2 percent) using that dictionary. And for the subsidy-eligible, Adults and Young Adults appear rarely and with near equal frequency (respectively 1.4 and 1.9 percent of tagged terms).
References to gender are also infrequent. Within the references that exist, across all DTMs, portrayals are somewhat more focused on women than men (see Table 3 for details). Women’s slightly greater frequency in portrayals appears commensurate with women’s actual prevalence as ACA beneficiaries. At least of those who selected an insurance plan through ACA marketplaces during the first open enrollment period, an estimated 54 percent were female. 431
Explicit references to race also appear infrequent. As seen in Table 3, across all four DTMs, both White and non-White references are less than 2 percent of tagged terms (and are absent in descriptions of insurance-losers). While potentially related to salience, 432,433 it is not possible to assess whether portrayals of race/ethnicity are proportionate. Explicit mentions of race/ethnicity appear most in descriptions of insurance-gainers, who are portrayed as more often non-White (1.6 percent of tagged terms) than White (0.2 percent of tagged terms). In California, which as noted accounts for many of the articles and thus plays a large role in the data, a minority (35 percent) of marketplace enrollees were non-Hispanic White. 434 Nationally, HHS reports race/ethnicity information for people who selected insurance on federally-facilitated marketplaces as of May 1, 2014. 435 In those data, of the 69 percent who reported a race, 63 percent identified as White. 436
There are also methodological caveats to assessing the frequency of references to race/ethnicity. The methods may undercount explicit references since none of the dictionaries break out terms tagged as Surnames (see the Appendix) by national origin. 437,Reference Enos438 Second, as noted, the White and non-White tags will miss implicit race references—“words that have racial associations but are not racial nouns or adjectives.” 439 Third, as part III notes, scholars find messages about race/ethnicity interlaced with messages about insiders/outsiders and messages about work. As Table 4 underscores, the Workers tag and Strong Insiders tag are among the most frequent in portrayals.
VIII. Implications for durability
Are the patterns these questions have uncovered favorable to the ACA’s durability, as defined at the outset of the paper? This section offers two broad answers for consideration. On the one hand, portrayals appear conducive to durability in that they depict beneficiaries in terms associated with deservingness in past U.S. social policy. On the other hand, there are three reasons for caution. First, portrayals also cast insurance-losers as deserving. Second, it is unclear if the portrayals found will aid, or allow “drift” 440 away from, the ACA’s goals of cutting insurance disparities. Research is needed on the implications of the (non)-role of race/ethnicity, along with age and health, in portrayals, and the prominent role of the insider theme. Third, the frequent portrayal of beneficiaries as Workers, coupled with the inattention to young adults and to beneficiary economic heterogeneity, may do little to foster beneficiary political engagement.
How portrayals may bolster durability: beneficiaries as deserving
The likely query following from the third question taken up in part VII is whether portrayals depict ACA beneficiaries as deserving. As part III explained, such a portrayal is associated with favorability toward the policy in question among beneficiaries, the mass public, and elites. We can give a preliminary answer by examining Table 4 in light of Table 2. Three points suggest that ACA beneficiaries (the newly Medicaid-eligible, the subsidy-eligible, and insurance-gainers) are portrayed as deserving.
First, as noted, Workers is the tag that most often appears in portrayals of the subsidy- and newly Medicaid-eligible. In the subsidy DTM, it is the most frequent tag by over 13 points. As part III notes, workforce participation is a hallmark of deservingness in U.S. social policy.
Second, as Table 4 underscores, the second most frequent tag in descriptions of the subsidy-eligible is Families. As noted, families are often considered deserving, and the Families and Workers portrayals may interact to support durability, as “supplements for working families with low incomes” have seen expansion even when politics otherwise favored retrenchment. 441
Third, as Table 4 recaps, Strong Insiders is the third most frequently used tag in descriptions of the newly Medicaid-eligible, and the Strong and Weak Insiders tags are the second and third most frequent tags for insurance-gainers. As noted above, claims that beneficiaries are insiders have often been associated with claims that beneficiaries are deserving.
It is useful to present further information about which terms “drive” the Strong Insiders tag. For instance, in all dictionaries, the term “state’s” (possessive) is tagged Strong Insider. Readers may wonder whether the tag’s frequency owes to uses of “state’s” that may reference say, a “state’s” government or institutions, rather than people. This does not appear to be the case. Using Dictionary 1, in the subsidy DTM, the term accounts for only three of the 438 instances of the Strong Insiders tag; the most frequent terms were “americans” (201 instances), followed by “taxpayer” (22 instances), “californians” (18 instances), “citizens” (13 instances), and “virginians” (12 instances). In the Medicaid DTM, it accounts for 31 of the 721 instances of the Strong Insider tag (4 percent); ahead of it were “americans” (130 instances), “virginians” (44 instances), and “ohioans” (33 instances). Closely following it were “utahans” (28 instances), “citizens” (26 instances), “pennsylvanians” (24 instances), “americans.” (21 instances), “texans” (20 instances), and “mainers” (19 instances). In the insurance-gainers DTM, it accounts for 24 of 890 instances of the Strong Insiders tag (under 3 percent); frequent terms are “americans” (443 instances), “floridians” (35 instances), “americans.” (26 instances), and “nation’s” (24 instances). The term does not appear in the insurance-losers DTM. Thus, newspapers appear to describe ACA beneficiaries with words of the sort that past scholars have identified as signaling “insider” status, as discussed in part III.
The two other tags most often seen in portrayals as recapped in Table 4—Poor/Very Poor and Uninsured/Underinsured—also likely cast ACA beneficiaries as deserving when closely assessed. As noted, past research finds the poor—at least the working poor—on the deserving side of Table 2. To further assess the Poor/Very Poor tag in the context of the ACA, recall that a portrayal’s impact depends partly on how it aligns with existing views of a group or characteristic. 442 To that end, it is interesting to note that traditional Medicaid recipients have historically been seen with sympathy. Reference Cook and Barrett443 And, an April 2005 survey that asked national adults if they thought “a main reason why people have health insurance through the Medicaid program” is that “they are poor and can’t afford to purchase health insurance on their own,” found 87 percent saying “yes.” 444 Together, these considerations suggest that the public thinks of traditional Medicaid recipients as poor but deserving. Thus, portrayals of the newly Medicaid-eligible as Poor/Very Poor are also likely consistent with a view of this group as deserving.
Uninsured/Underinsured—the dominant tag in portrayals of insurance-gainers—also likely connotes deservingness. As noted, this tag comes almost entirely from mentions of the “uninsured.” Surveys shed light on views of the uninsured. In five closed-ended questions between 1993 and 2001 that allowed multiple responses and asked Americans to describe the uninsured, the “Poor” and “Poor people” were chosen most often (by 41 to 48 percent of respondents), followed by “Unemployed” or “Unemployed people” (35 to 37 percent), while only 10 to 16 percent chose “Working” or “Working families” in all five surveys, and only 6 to 8 percent selected “People like yourself” or “Like yourself” in the four giving this option. 445,446,447,448,449 Similar questions permitting open-ended responses also find an emphasis on “Unemployed people” and “Poor people” or “Poor people/low income people.” 450,451,452 Again, beliefs that the uninsured are poor or low-income suggest they are seen as deserving. It is more difficult to predict the upshot of beliefs that the uninsured are unemployed, especially since the Workers tag characterizes only 5 percent of terms describing insurance-gainers. As part III notes, work is a cornerstone of deservingness in social policy; but, the public does not always take unemployment as signaling an unwillingness to work, particularly during a recession. 453 Further, one of those surveys finds the uninsured associated with the unemployed and “Working families/Employed” at similar rates, 454 and Schneider and Ingram suggest the unemployed are often seen as deserving. 455 The dominant depiction of insurance-gainers as uninsured thus appears unlikely to work against a portrayal of this group as deserving, particularly in light of their simultaneous portrayal as Insiders.
There is arguably an example of what Ingram and Schneider call “degenerative politics” 456 in discussions of beneficiaries as “smokers,” and “drinkers.” Reference Cousins457,Reference Long458 But, these discussions appear to dissipate and are a very small data share (Substance Abusers in Table 3).
Thus, portrayals of ACA beneficiaries (the subsidy-eligible, newly Medicaid-eligible, and insurance-gainers) appear to emphasize themes tied to deservingness in past U.S. social policy. A depiction of beneficiaries as deserving may aid in benefit take-up, foster favorability to the ACA in the mass public, 459,460 nurture beneficiaries’ “external” political efficacy 461 and political participation, 462 and thereby help to insulate the ACA from “‘programmatic retrenchment.”’ 463
Three reasons for caution
Yet, as outlined above, three considerations give reason for caution in concluding that portrayals in all respects advance the ACA’s policy durability, as defined at the article’s outset.
Insurance-losers as deserving
A caveat to the finding that ACA beneficiaries are portrayed as deserving is that ACA insurance-losers are also strongly portrayed as deserving, and in ways that could be sharpened into bright contrasts with insurance-gainers. As seen in Table 3 and recapped in Table 4 and Figure 1, the dominant tag in portrayals of insurance-losers is Strong Insiders. And, it is seen far more often for this group (29 percent of tagged terms) than it is for insurance-gainers (16 percent of tagged terms). The second most frequent tag in portrayals of insurance-losers is, as noted, Workers (14 percent of tagged terms), compared to this tag applying to only 5 percent of tagged terms describing insurance-gainers. The third most frequent tag in portrayals of insurance-losers is, as noted, Customers/Clients, another group that, as part III discusses, has been considered deserving in the past in American politics. These portrayals all serve to cast insurance-losers as highly deserving according to the literature, and could conceivably serve to turn insurance-gainers’ dominant portrayal as the Uninsured into a signal of undeservingness in the future—particularly if the association the public makes between the uninsured and the unemployed were to tighten, and perceptions of the unemployed to turn negative. It will be important to trace whether the categories of insurance-gainers versus insurance-losers persist, and to continue to track how each is portrayed.
Portrayals and the durable pursuit of disparity reduction
Two aspects of the results require further study—outside this paper—to assess whether the patterns found stand to bolster or weaken the durability of the ACA’s efforts to cut insurance disparities: (1) the implications of the infrequent attention to race/ethnicity, as well as to age and health; and (2) the implications of the salient attention to insider status.
Much literature suggests that race/ethnicity’s role in portrayals could relate to the ACA’s ability to reduce race/ethnic insurance disparities. 464,465,Reference Sidney, Schneider and Ingram466,467,Reference Schram, Schneider and Ingram468 If the apparent inattention to race/ethnicity found in part VII means an absence of the sorts of negative portrayals of minorities that Gilens and Neubeck and Cazenave describe, this is favorable for racial equality in politics, 469,470 and potentially for ACA durability insofar as some past policies standing to cut racial disparities that have been linked to racial stereotypes have faced direct retrenchment 471 or attenuated efficacy. 472,473 Simultaneously, Schram argues that when race is ignored, little attention may be paid to whether a policy that aims to reduce disparities is actually doing so, and that inequalities, especially between African Americans and Whites, could thereby be “reinforce[d].” 474 Other work echoes this concern, 475,Reference Lin, Harris, Lin and Harris476 including, broadly, research on media portrayals of disease. 477 Discussing welfare, Schram advocates “tak[ing] race into account,” and directly attending to the “racial dimensions of our social and economic structure” when aiming to cut disparities. 478 A range of scholarship makes a similar argument. 479,480,481,Reference Powell482,483 This call may be relevant to the ACA, with attention to how income and race condition access to employment-based health insurance being but one example. Reference Bertrand and Mullainathan484,485,486,487,488
The political science literature is less developed around age and health, and as noted, race has a unique role in American politics. But by similar logic, the infrequent attention to age and health found in part VII has unclear implications for the ACA’s work to cut insurance disparities between the near-elderly and those who are younger, and between those in poor versus good health.
The literature suggests a three-step mechanism by which the Strong Insider theme’s salience could hinder the durability of the ACA’s disparity cutting efforts by discouraging benefit take-up among eligible immigrants. First, portraying beneficiaries as insiders implicitly highlights outsiders. 489,490 Second, undocumented immigrants are outsiders to ACA benefits. They cannot purchase insurance in exchanges, and eligible children must provide documentation to do so. 491 The Strong Insider portrayal, as noted, also describes ACA beneficiaries using words such as “californians” and “citizens”—terms that have underscored undocumented immigrants’ outsider status in the past. 492 Third, factors highlighting undocumented persons’ ineligibility for benefits can “chill” take-up by eligible immigrants and co-ethnics due to deportation fears, Reference Pedraza and Zhu493 and there is some indication of elite concern about this possibility playing out in the ACA. 494,495 In some cases, “any reminder of…immigration status may be sufficient to cue a ‘chilling effect.”’ 496 If so, the Strong Insider theme’s preeminence could work against the ACA reducing insurance disparities, especially between non-Hispanic Whites and Latinos. 497,498
Thus, for multiple reasons, further research may be needed to assess whether the portrayal patterns found here stand to support or slacken the ACA’s adherence to its disparity cutting aims. This question may especially merit study at the state level. Reference Zhu and Clark499,500 Elites indeed already appear to be monitoring the ACA’s fidelity to its disparity reducing goals. Reference Radnofsky501
Portrayals and beneficiary political engagement
The portrayals found may also fail to politically mobilize ACA beneficiaries. Part VII already noted two ways in which this is so: portrayals do little to showcase the new political relevance of being under age 26 and so do little to foster positive feedbacks among young adults; and, portrayals do little to underscore beneficiaries’ economic heterogeneity and so do little to help address Mettler’s concern that many Americans “gained little understanding of what the policy might do for them.” 502 Yet, one more aspect of the portrayals may impede positive feedbacks according to arguments by Mettler and others: the salience of the Worker theme.
While work is associated with deservingness, some scholars might argue that the Worker portrayal underscores beneficiaries’ economic role more than their political capacity. Mettler worries that political engagement around social policy is unlikely when a policy and its politics “regard people primarily as…participants in markets” when “[f]undamental to democracy, by contrast, is the idea that people are…active participants in governance.” 503 Ono and Sloop make a similar argument, 504 and Soss, Fording, and Schram’s arguments about neoliberalism as a “policy rationality” 505 tend toward a similar conclusion. 506 The Worker portrayal joins ACA features—like subsidies—that may already underscore citizens’ market role. 507 And, the portrayal may in itself be insufficient to suggest that ACA benefits are earned; not just beneficiaries’ work history, but payroll taxes, help generate this view of Social Security and Medicare. 508,509,510 If the ACA’s beneficiaries—its “consumers” 511 —are politically dormant, then the ACA may, like Medicaid, 512,Reference Slessarev, Weir, Orloff and Skocpol513,Reference Rose514 derive political strength from the “producer” side of its constituency 515 —the health care industry. 516,Reference Starr517,518 But, “divisions between health-care producers and consumers…have facilitated retrenchment in Medicare,” 519 and “[d]ivide-and-conquer strategies” 520 have similarly fostered cuts in antipoverty policies. 521 Mettler in fact alludes to this risk within submerged policies. 522 Campbell notes that “variation in program trajectories [can] aris[e] from the interaction of…design features with the political strategies of program foes.” 523 Thus, if the Worker portrayal enables rather than counters beneficiary political dormancy, its preeminence could leave the ACA more vulnerable to retrenchment than it otherwise may be.
IX. Conclusions
If the ACA achieves the goals noted in the Introduction, it may extend the American welfare state’s “scope of risk protection,” 524 and by “reduc[ing] vulnerability” even help address entrenched inequalities. 525 This article therefore takes the premise that the ACA’s durability merits scholarly interest, and—motivated by past research on social policy, welfare state retrenchment, and social constructions that suggests that a policy’s durability relates to depictions of its beneficiaries—takes the premise that ACA beneficiary portrayals merit systematic study. This article first describes those portrayals by answering three questions that the literature connects to durability: (1) Are beneficiaries portrayed as economically heterogeneous? (2) Do portrayals highlight groups to which ACA gives new political meaning? (3) What themes that have served as messages of “deservingness” in the past riddle ACA portrayals? It finds the answer to question (1) to be “no,” with the caveat that the methods may miss some cross-class portrayals. The answer to question (2) also appears to be “no,” with the caveats that young adults may have received more attention in months prior to those studied, and that the methods may miss some references to age. In response to question (3), portrayals most often highlight themes of work, economic self-sufficiency, and insider status. Health status, age, gender, and race/ethnicity appear to receive little attention.
The article then assesses how the patterns uncovered in answering these descriptive questions may work for and against durability. While “[i]t is hazardous to make predictions about how policies will evolve, especially about those with as many moving parts as the ACA,” 526 these findings—assessed through the lens of existing literature—suggest reasons for both confidence and caution about whether portrayals are likely to bolster the ACA’s strength in resisting direct retrenchment and in diligently pursuing goals such as disparity reduction. To recap part VIII, a key result favoring durability is that beneficiaries are depicted in terms associated with deservingness in past U.S. social policy, in being portrayed as workers and insiders. But, there are three potential reasons for caution. First, ACA insurance-losers are also portrayed as deserving. Second, the durability of the ACA’s disparity cutting efforts may merit watching, with an eye to the unclear impacts that the relative absence of age, health, and race/ethnicity in portrayals, and the possibly adverse impacts the Strong Insider theme’s salience in portrayals, may have on this goal. Third, the Worker theme’s salience may, despite its ties to deservingness, join limited attention to young adults and to beneficiaries’ economic heterogeneity, as a portrayal pattern that does little to help the ACA politically mobilize its beneficiaries.
This article is the first to quantitatively describe and analyze media portrayals of ACA beneficiaries. Of studies located through JSTOR and other search strategies in May 2015 (details available by request), only a handful appear likely to speak to ACA beneficiary depictions, Reference Mariner527,Reference Oliver528,Reference Sours529,Reference Hussey and Pearson-Merkowitz530,Reference Leimbigler531 and inspection makes clear that the first three do not. Hussey and Pearson-Merkowitz state that ACA “discourse…did not portray blacks as the likely beneficiaries of national health insurance or health care reform, while it did focus on illegal immigrants.” 532 Their paper points to two New York Times articles exemplifying immigrant-focused discussions, but not to systematic studies of ACA beneficiary portrayals, and the paper itself examines a different question. 533 Leimbigler’s work shares the present article’s interest in studying how social constructions relate to the ACA’s political strength, 534 discusses political engagement, 535 and in studying “markets” and “rights” frames may trace language similar to that tagged Strong Insider, Cross Class, and Customer/Client here. 536 But Leimbigler’s work studies elite framing, and differs from this article in its goals, 537 methods, 538 and outputs. 539 Barry and colleagues study media messages during ACA implementation but not beneficiary portrayals. Reference Barry540
Early beneficiary portrayals—such as those studied here—may have uniquely powerful implications, 541,542 and data of the type gathered here may be a foundation for broaching large questions falling beyond this article, such as whether the ACA is understood as “public assistance” or “social insurance,” a ubiquitous distinction. 543,Reference Nelson and Gordon544,Reference Stone, Schneider and Ingram545 As noted, the data may be a basis for studying how the ACA may alter inequalities in political participation. 546 The type of data built here may also be a start at answering Jacobs and Mettler’s call for research on the “structural framing” around the ACA, 547 meaning “institutionally-based communications of social welfare policies that…frame concrete programmatic returns to individuals.” 548
It is important to stress, however, that the research carried out here does not claim to describe framing effects around the ACA or its beneficiaries. It reports the frequency of tags devised to organize carefully coded but atomized terms; “framing effects depend more heavily on the qualities of frames than on their frequency of dissemination.” 549 This article does not (and cannot) weight ACA beneficiary portrayals by the degree to which the public, beneficiaries, or policymakers find them convincing. These are empirical questions about which we do not yet have data.
Several other methodological limitations were stated above and are not repeated here. I rather highlight three points about external validity. First, as noted, results pertain to the 50 states in the aggregate; sub-national results may differ. Second, visual images—not studied here—may bear as much or more on beneficiary constructions as do numbers and words. 550,551,552,553,554
Third, the degree to which the results generalize outside the months studied is an open question. One consideration is that the ACA’s implementation timeline may make it logical for the media to generate different portrayal patterns at different times. Another is the partisan discord in the timeframe studied. In November 2013 for instance, the “‘Because of Obamacare…I Lost My Health Insurance”’ booklet met with a White House document entitled “‘G.O.P. Obstruction/Sabotage—Affordable Care Act.”’ 555 Representative Frederick Upton (R-MI) charged President Obama with misleading Americans on being able to keep their insurance, and Representative Michael Doyle (D-PA) retorted “‘[d]on’t pretend you care about the American people’s health care here….You just want to repeal the Affordable Care Act.”’ Reference Parker and Pear556 Whether partisan discord impacted media portrayals is a question beyond this paper. So is the question of whether any such impact makes the portrayals found here unique to these months, or rather predictive of future portrayals.
Looking forward, tight public budgets may lead to a sharpening of divisions between those deemed “worthy and unworthy” 557 within a policy’s beneficiaries. 558,559 It will be important to continue to track ACA beneficiary portrayals in the coming years, using multiple methods, to update the answers to the questions broached here, and to continue to assess how the politics around this new policy are shaping its capacity to insure the uninsured, mitigate health-based financial vulnerabilities, cut inter-group disparities, and improve health.
Note
This work was supported, in part, by funds provided by the University of North Carolina at Charlotte. For research assistance, I thank Marc Botero, Brittany Bumgarner, Kim Hill, Jenny Kaemmerlen Kabool, Charlie Lamprecht, Tracy Martin, Allison McMurry Cordell, Erika (Palmer) Ruanne, JoEllen Pope, and Ashlyn Shrewsbury. For information about LexisNexis indexing, I thank Amanda Binder. A course on “Text Mining and Text Analysis with R” taught by Scott Moser in 2013 provided instructive guidance on performing automated text analysis in $\boldsymbol{R}$ . Early versions of this paper were presented at the annual meetings of the American Political Science Association (August 2014), Midwest Political Science Association (April 2014), Northeastern Political Science Association (November 2013), and Southeastern Conference for Public Administration (September 2013). For helpful discussions and comments, I thank other panel participants at these conferences, Bill Brandon, Erik Bucy, Eileen Burgin, Sally Cohen, Nicole Krassas, Ted Marmor, Carl Snook, Robert Sprinkle, Deborah Stone, John Szmer, and Miya Woolfalk. I also thank two anonymous reviewers for helpful suggestions, including but not limited to the suggestion to examine portrayals of those gaining insurance versus those losing insurance under the ACA. Errors are my own. For references citing iPOLL as the distributor, the following acknowledgement applies, as stated by the Roper Center website: ‘‘The survey results reported here were obtained from searches of the iPOLL Databank and other resources provided by the Roper Center for Public Opinion Research, University of Connecticut.” The author’s access to Roper iPOLL was obtained through UNC Charlotte. Online Appendices 1, 2 and 3 are available as supplementary material on Cambridge Journals Online. Data are available from the author.
Appendix A detailed explanation of methods
As noted in the main text, analysis proceeded in three phases. First, the following steps were performed manually to identify portrayals of the newly Medicaid-eligible and separately of the subsidy-eligible. A human coder searched for sentences containing eligib, expan, tax credit, and subsid in each state’s article set using the find function in Word, highlighting the full sentences that did contain any of these elements. The coder (often the same person) then differently highlighted words in those sentences that the coder assessed as describing those newly eligible for Medicaid under the ACA, using instructions provided by the author (available by request). As noted in the main text, this highlighting was to exclude descriptions of beneficiaries joining Medicaid due to the woodwork effect. Highlighting included descriptions of those who would be eligible if their states expanded Medicaid. The coder differently highlighted words in those sentences that the coder saw as describing the subsidy-eligible, again with author-provided guidelines. This highlighting included descriptions of people who would use the exchanges and then find out if they were subsidy-eligible. If the coder did not believe that a sentence highlighted in the first step contained descriptions of the subsidy- or newly Medicaid-eligible and thus added no highlights at the second step, or if the coder judged the article to be virtually identical to another one already in the state’s set, no words in the sentence became part of the text data. If a coder believed that a word described both the subsidy- and newly Medicaid-eligible, the coder indicated so, and those words entered the data for both groups. References to national-level information were highlighted, but care was taken—as described later in this paragraph—to ensure that final highlighted material described residents of the state at hand, not of other states. Consequently, when it appears in the data, a term like “Californians” should come from a California article and thus signal an “insider” portrayal in the sense discussed in part III. The author coded (for descriptions of the two groups) articles for ten states, one graduate assistant (A) coded articles for 19 states, and another graduate assistant (B) coded articles for 21 states. ACA exchange and Medicaid decisions were diverse within the states that each person coded at the time the coding was done, taking decisions from May and June 2014 from the Henry J. Kaiser Family Foundation and National Conference of State Legislatures (as cited in the main text and under Table 1) as the reference. (One exception however, is that when coding articles for portrayals of the newly Medicaid-eligible and the subsidy-eligible, assistant B best followed the instructions to exclude information about residents of states other than the state at hand, or to flag it for me to exclude. I therefore retroactively went through states coded by assistant A, and those coded by myself, to check for, and when necessary to “un-code,” coded material that was—from the article text—plainly about residents of other states. While it would have been preferable for graduate assistant A to make these corrections, this student was no longer on the project when this issue was detected. A full report on the material from assistant A that was “un-coded” is available on request; the substantive results for these 19 states taken together differ very little with versus without this material).
Similar steps were taken to identify portrayals of those gaining and, separately, losing insurance. The same 8019 articles were used; coders were given blank versions not containing highlights about the subsidy- or newly Medicaid-eligible. For each state, a coder found and highlighted sentences containing any of the following words or phrases: lose, losing, cannot afford, can’t afford, for the first time, become insured, will become, will gain, will get, uninsured. The coder, often the same person, then read those sentences and identified and differently highlighted words within them that in his or her assessment described those losing insurance due to the ACA. The coder identified and differently highlighted words in those sentences that in his or her assessment described those gaining insurance under the ACA, including via Medicaid—so long as the person’s eligibility for Medicaid was new due to the ACA as far as the coder could judge. Coders were again given instructions to guide these determinations, available by request. Again, if the coder did not believe that a sentence highlighted in the first step contained any such descriptions and thus did not add highlights at this stage, or if the coder judged the article to be the same as another already in the state’s set, words from the sentence did not become part of the data. If a coder believed that a word described people who were both losing and gaining insurance due to the ACA, the coder indicated so and those words entered the data for both groups. Material about people in states other than the state at hand was again to be excluded; here, these instructions appear to have been well followed in research assistants’ coding. Here, unlike in coding for those newly Medicaid-eligible, descriptions of people who would only be eligible for Medicaid if their (non-expanding) states implemented the expansion were to be excluded. Graduate assistants were instructed to either not highlight this information, or to highlight it but flag it as likely meriting exclusion. If it was so flagged, I excluded it from the data. I coded (the same) ten states for insurance-loser and -gainer portrayals. Graduate assistant B coded 19 states (different from those that this assistant had coded for information about the subsidy- and newly Medicaid-eligible). A third graduate assistant (C) coded five states; a fourth graduate assistant (D) coded 14; a fifth graduate assistant (E) coded two. Further details are available by request.
The next phase involved extracting the highlighted information and transforming it into data. For one state at a time, I manually harvested the items thus coded as describing the newly Medicaid-eligible and saved them in a document for each state, as described in the main text. I likewise harvested the words coded as describing the subsidy-eligible and insurance-losers and -gainers. As noted, the result is four documents for each state: one describes the subsidy-eligible, one the newly Medicaid-eligible, one insurance-losers, one insurance-gainers.
As noted in the main text, I then assembled four corpuses, one consisting of the 50 documents (one per state) describing the newly Medicaid-eligible, a second the 50 describing the subsidy-eligible, a third the 50 describing insurance-gainers, and a fourth the 50 describing insurance-losers. I ran each corpus through basic automated textual processing using the RTextTools and other packages in R (version 2.15.2), removing white space and converting all words to lower-case. As noted, I did not here reduce words to their roots or remove terms like “the,” numbers, and punctuation, in the interest of preserving information relevant to portrayals. For instance, I wanted to be able to separate, if it occurred, “dakota’s” from “dakotas,” since the former may describe “insiders” in the sense noted in part III, while the latter may simply reference geography. I also wanted to preserve numbers and maximum information about numbers; for instance “400%” is likely a reference to those up to 400 percent FPL, while the meaning of “400” is less clear. I also wanted to preserve instances of “he” and “she” to track gender in portrayals.
After thus minimally preparing the documents, I used automated methods in R to generate four DTMs as described in the main text, one consisting of the terms describing the newly Medicaid-eligible, one the terms describing the subsidy-eligible, one the terms describing insurance-gainers, and one the terms describing insurance-losers. I use these DTMs in the third phase of the analysis.
In that phase, each term from the DTMs was manually assigned a “tag.” Tags were developed by the author. Tags were motivated by the literature reviewed in part III, and also emerged inductively from consideration of the terms. For instance, “his” was given the tag Male, as were male names such as “jonathan.” Personal pronouns such as “i’m” and “your” were given the tag Personal, although “our” was given the tag Strong Insider in the vein of Winter’s discussion of “our elderly” as cited in the main text. The author decided which terms received which tags; graduate assistants were not involved in this process.
To sort out which terms belong to which tags, and how often each tag appears, I built “dictionaries,” again in the vein of past work on textual analysis as cited in the main text. Dictionary 1, presented in online Appendix 1, contains 40 tags. Dictionary 1 leaves words of a high level of ambiguity untagged, alongside numbers with no clear meaning and generic words such as “people.” It tags city and state names simply as Geography. It tags terms like “citizens,” “taxypayers,” “hoosiers,” “yorkers,” and “country’s” (which, like Winter’s “our,” is possessive) as Strong Insider. It tags terms like “residents” and “nationwide” as Weak Insider to accommodate the sense that such terms are not so generic as “people,” and yet not so embracing as “hoosiers.” It codes only explicit probable references to a race or ethnicity other than non-Hispanic White—such as “asian,” “black,” “hispanic,” “indian,” and “latino”—as Non White, and tags all surnames simply as Surname regardless of the ethnicity they may suggest. It tags the “working-poor” and terms like “low wage” as Workers. It tags terms like “mother” and “husband” simply as Female and Male.
As noted, I also created five alternative dictionaries to address the fact that many terms can be differently tagged depending on the analyst’s interests or willingness to make assumptions. Online Appendix 2 describes these dictionaries in brief. The two of most interest for purposes of the results are Dictionaries 3 and 5. Dictionary 3 is like Dictionary 1 but makes strong assumptions about numbers; for instance, dollar values between $1000 and $30,000 are tagged as General Low Income rather than left untagged. Values of $30,000 and above are tagged as Cross-Class. Numbers possibly suggesting ages, like “four” and “seventeen” are tagged as Children while numbers like “57” and “60” are tagged Near Elderly. Dictionary 5 is like Dictionary 1 but tags terms such as “working-poor” and “low-wage” as General Low Income rather than Workers. For brevity, only the results from Dictionary 1 are presented in full, and only Dictionary 1 appears in online Appendix 1. Key results are largely similar across dictionaries. Full results from dictionaries 2 through 6, and the dictionaries themselves, are available on request.
Data check: text sensitivity to database used to find articles
LexisNexis casts a wide net in the newspapers it archives (see http://w3.nexis.com/sources/scripts/eslClient.pl?GSDTYPE=Newspapers#N), but in a preliminary examination, the articles obtained from LexisNexis only partly overlap those obtained from NewsBank. It may also be that papers not archived in LexisNexis have smaller circulations than those that are archived (see online Appendix 3). As noted in the main text, to check whether the results would have been systematically different had I used a database other than LexisNexis, articles from August 1, 2013, through January 31, 2014, were gathered through NewsBank, using the same key terms, for ten states diverse in region and in ACA Medicaid and exchange decisions: Alabama, Alaska, Arizona, Connecticut, Delaware, Indiana, Maine, Virginia, Washington and Wisconsin. Graduate assistants B (for three states) and C (for seven states) carried out the manual procedures described above to code the resulting articles for portrayals of the subsidy- and newly Medicaid-eligible (details available by request); they were not asked to code for portrayals of insurance-losers or -gainers. Resulting words were then analyzed using the methods described above. As part VI reports, the portrayal results for these ten states as analyzed through NewsBank-based data differ very little from results for the 50 states reported from analysis of LexisNexis-based data. Thus, it does not appear that using LexisNexis to locate articles led to systematically different aggregate results than would have emerged from finding articles through NewsBank.
Two final points merit mention. First, textual analysis can be automated to a greater degree than it is here—see the articles by Grimmer and Stewart and Lucas et al. cited in the main text—but, Grimmer and Stewart note that it is not possible to eliminate human interpretation. Second, the reader may wonder whether the timing with which LexisNexis indexes articles impacts the articles found. Timing should minimally impact the articles returned, since the articles were gathered retroactively, as noted above.