Evidence from Japanese-American Internment During WWII∗

Home , Internment, Judgment Without Trial

e Political Consequences of Ethnically Targeted Incarceration: Evidence from Japanese-American Internment During WWII∗

Mayya Komisarchik† Maya Sen‡ Yamil R. Velez§

May 28, 2021

Abstract What are the downstream political consequences of state activity explicitly targeting an ethnic minority group? is question is well studied in the comparative context, but less is known about the eects of explicitly racist state activity in liberal democracies such as the United States. We investigate this question by looking at an important event in American history—the internment of people of Japanese ancestry during World War II. We nd that Japanese Americans who were interned or had family who were interned are signicantly less politically engaged and that these paerns of disengagement increase with internment length. Using an identication strategy leveraging quasi-random camp assignment, we also nd that camp experience maers: those who went to camps that witnessed intragroup violence or demonstrations experienced sharper declines, suggesting that group fragmentation is an important mechanism of disengagement. Taken together, our ndings contribute to a growing literature documenting the demobilizing eects of ethnically targeted detention and expand our understanding of these forces within the U.S.

∗We are grateful to Daniel de Kadt, Michael Hankinson, Alexander Hertel-Fernandez, Boris Heersink, Katherine Krimmel, Mahew Lacombe, Sarah Merchant, and Michael Miller for helpful feedback. Additional thanks to seminar participants at Rutgers, Boston University, Cornell, the University of Virginia, Duke, UC-Berkeley, UC-Merced, the University of Pennsylvania, and Stanford GSB. Special thanks to Danny Shoag for conversations on an earlier iteration. Comments and suggestions welcome. †Department of Political Science, University of Rochester. ‡John F. Kennedy School of Government, Harvard University. §Department of Political Science, Columbia University. 1 Introduction

Growing immigrant populations in liberal democracies have spurred a rise in policies targeting immigrants and ethnic minorities. ese include indenite detention, the corralling of unau- thorized immigrants into holding facilities, and the reinforcement of border barriers that create hostile conditions for migrants. Such policies raise questions about the impact of such detention on the individuals detained and about the universal scope of democratic principles. e U.S. government’s internment of people of Japanese descent is a key case that frames the dierence between democratic principles and practice. In June of 1942, approximately 120,000 people of Japanese descent were sent to internment camps throughout the American interior. By the time the camps were shut down at the end of World War II, hundreds of thousands of people had been displaced and their lives severely disrupted. is included not just adults, but also children—many of whom spent formative years living in internment. Despite the signicance of this event and growing use of detention centers in the U.S. and elsewhere, we still know lile about the political consequences of such large-scale ethnic targeting within liberal democracies. Some studies in comparative politics have examined forced migration and the internment of ethnic minorities in autocracies, concluding that these tend to iname inter-ethnic conict and reduce minorities’ trust toward the state (e.g., Lupu and Peisakhin, 2017; Zhukov and Talibova, 2018). In addition, a growing American politics literature has examined the crippling impact of incarceration on aected populations (e.g., Lerman and Weaver, 2014). is literature—focused on penal institutions as opposed to military ones—has found that incarceration depresses the political engagement not just of those incarcerated but also that of their extended families (White, 2019). However, whether and how a large-scale, ethnically targeted detention policy could aect subsequent political aitudes in liberal democracies is less clear. e context of Japanese internment provides an important instance to address the question. First, the internment of Japanese Americans during WWII was a large-scale government activity, puing it on par with ethnically driven state activity in a comparative context. Second, the historical record is rich, and we have substantial documentation on internment and its consequences.

1 In this regard, an important literature on Japanese-American political engagement posits that the group’s history of internment might be a reason why Japanese Americans are among the most politically active of Asian American groups (Wong, 2011). In addition, we have useful variation: not only was there variation in who was interned, but, conditional on initial location, families were mostly exogenously assigned to camps throughout the U.S. is enables us to gain causal traction on how internment experiences impacted subsequent engagement. We nd that internment has had negative downstream repercussions. First, we nd that being interned or having family members who were interned is associated with a lasting, large, and signicant decrease in political interest and engagement. Although not necessarily causal, we nd that this relationship cannot be explained by factors that plausibly covary with internment status (such as military service or income). Second, conditional on internment, we nd that an additional year of internment is associated with a decrease in political trust and engagement; again, this does not appear to be explained by other factors. ird, shiing to a causal analysis, we leverage that, conditional on pre-internment location, internees were quasi-randomly assigned to camps. is allows us to examine the nature of the camps themselves (following Shoag and Carollo, 2016). We nd that being assigned to a camp that experienced violence or unrest resulted in greater political disengagement. is suggests the social conditions within camps themselves were key pathways to disengagement. Surprisingly, we do not nd similar eects for exposure to militaristic environments or the cultural or political environment in camps’ surrounding areas. We explain these paerns by highlighting an important mechanism linking negative state activity to disengagement: group fragmentation. We argue that, in contrast to atomized encounters with the criminal justice system, the internment process produced political disengagement by exposing internees to divisions within their ethnic group, revealing possible barriers to collective action. ese ndings suggest that the negative eects of punitive government interactions might be transmied via intragroup dynamics. While previous studies have emphasized vertical relations between minority populations and the state as a key determinant of disengagement, our study illuminates how captivity-induced conicts within groups can lead to disengagement.

2 Our paper speaks to several research streams. First, we link disparate literatures from comparative politics with scholarship on American politics, explaining how state-sponsored racial targeting—even within a large liberal democracy—can have lasting political consequences. Sec- ond, our research shows how more adverse collective conditions produce larger eects over time, illuminating that the nature of hostile state contact is important. ird, our study provides an op- portunity to assess theories of hostile state contact using a case where the psychological linkages to the government are strong. Our ndings therefore have strong implications for governments’ current-day use of detention centers, including those conning migrants. Lastly, our results en- gage a growing literature on Japanese-American public opinion, complicating the link between the group’s high levels of political engagement and internment. is paper proceeds as follows. We rst evaluate connections between the literature on ethnic conict, the adjacent literature on the American “carceral state,” and the literature on Japanese- American political behavior, drawing on these to describe a theory of how internment might aect political engagement by eroding group cohesion. We provide context on the Japanese-American internment experience and explain our data, which include novel data on camp conditions and surroundings. We next present our main results showing that direct and family exposure to the internment predicts subsequent political disengagement and that, among those interned, the length of the internment does as well. Although not causal, these results are not explained by alternative characteristics, such as dierences in terms of military service or economic success. We next leverage quasi-random camp assignment to show that group fragmentation—in particular camp social unrest—plays a key role in furthering disengagement. Finally, we demonstrate that our design assumptions are robust to several challenges and alternative explanations. We conclude by noting how our work informs other ndings on involuntary detention policies in western democracies.

3 2 Existing Scholarship

Internment presents a unique circumstance, although it is not one without similar cases in existing literatures. Scholars have explored instances where states have controlled ethnic minorities via repression and violence during upheaval, migration, or war (Levy, 1988). Some studies reveal that repression can mobilize targeted groups (Davenport, 2005; Blaman, 2009), while others suggest demobilizing eects (Lyall, 2009). While this literature claries the potential impacts of violence and repression on targeted communities, recent work has drawn aention to regime strength and whether repression eorts are carried out by state actors. As Zhukov and Talibova (2018) note, repression scholars have traditionally focused on cases of ethnic targeting perpetrated by non-state actors or weak states. We know less about the impact of large-scale repression eorts by “strong” states on minority political participation. Focusing on the deportation of ethnic minorities during the Stalin Era, Lupu and Peisakhin (2017) and Rozenas, Schue and Zhukov (2017) nd that punitive encounters with the Soviet Union during the 20th century continue to have positive eects on group aachments and that groups experiencing violence in the past report lower levels of contemporary support for pro-Russian parties. Rozenas and Zhukov (2019) nd that places exposed to Stalin’s terror campaigns were more hostile toward the regime when under threat of retribution, suggesting several plausible mechanisms under autocracies. Looking at China, Wang (2019) nds that communities targeted by state-sponsored violence in the 1960s are less trusting and more critical of political leaders in modern times.

2.1 Ethnic Targeting in Liberal Democracies

Even within democracies, minorities have collided with punitive institutions and experienced ethnic targeting (Mann, 2005; Fouka, 2019). For example, relevant to our inquiry is the contemporary status of European Jews, who were targets of atrocities by fascist Germany but many of whom continue to live in Europe today. Although recent work has found eects of concentration camps on local non-Jewish populations (Homola, Pereira and Tavits, 2020), the literature on

4 the downstream eects of the Holocaust on Jewish political participation suggests that Jews may be more politically engaged than the general population (e.g., Schnapper, Bordes-Benayoun and Raphael, 2011). Moving to the present day, the past few decades have seen democracies detain immigrants indenitely and sidestep due process in the name of national security (Radack, 2004). Despite this, it is unclear whether the eects of ethnic targeting translate across dierent kinds of political sys- tems. On the one hand, “threat-mobilization” studies in the U.S. have shown that policies targeting ethnic groups can increase political participation (Pantoja, 2001; Bowler, Nicholson and Segura, 2006). Consistent with some of the existing literature on repression (Lupu and Peisakhin, 2017), prominent theories posit that punitive policies increase the political salience of ethnic identities, thereby strengthening the link between group aachments and voting paerns (White, 2016). ere are certainly key dierences between internment and more contemporary adversarial state interactions. Despite racial disparities in the criminal system, a minority of Blacks and Latinos experience incarceration. is complicates our ability to assess the eects of punitive policies because “policy recipients” oen dier markedly from other group members. In addition, an immigrant-based group might respond to state repression dierently than would, say, African Americans. Finally, existing studies in this literature have mostly assessed contact with punitive institutions in a binary fashion. However, as Weaver, Hacker and Wildeman (2014, 19) note, scholars have yet to “move beyond treating incarceration as a uniform treatment” and leverage “variation in the character of custodial interactions.” As we note below, the experience of Japanese Americans enables such an inquiry. Nonetheless, historians have noted a connection between the violating experience of involuntary internment and incarceration. Lyon (2012), for example, notes that “Japanese Americans were accused of being a threat to national security and were ‘incarcerated’ in camps that looked and acted like some strange hybrid of concentration camps and prisons, even though they lacked formal designation as prisons” (p. xiii). In this regard, carceral eects research has found that direct experience with racially disparate criminal justice policies can have both demobilizing and

5 disengaging eects on those populations aected (Burch, 2013). According to this perspective, contact with law enforcement serves as a political socialization experience that erodes trust in government by exposing minority groups to aggressive elements of otherwise democratic sys- tems (Lerman and Weaver, 2014; Weaver and Lerman, 2010). is facet could parallel the “stigma” that scholars of internment have observed (Kashima, 2003, ch. 10).

2.2 Scholarship on Internment and Japanese American Public Opinion

e case of Japanese-American internment during WWII makes a compelling case to study these topics. First, unlike instances in authoritarian regimes, the Japanese-American case took place in a modern, liberal democracy.1 Second, internment involved the explicit targeting of an entire ethnic group, a contrast with ostensibly race-neutral targeting (such as policing or even immigrant detention centers). Lastly, Japanese Americans remained in the U.S. following their internment, enabling us to evaluate subsequent political participation. In this regard, Japanese-American political behavior has been the subject of robust scholarly research, with scholars nding a high baseline level of political engagement (Fugita and O’Brien, 2011, ch. 9). For example, Wong (2011, p. 18-20), report that, among Asian Americans, “Japanese Americans are the likeliest group to be registered to vote and to report voting,” with registration, turnout, and engagement rates far outpacing U.S. averages (Wong (2011), Table 1.1). However, the same authors also report that “among national-origin groups…Japanese (11 percent) are the most likely to report being a victim of a hate crime” (Wong, 2011, p. 169). Several scholars have linked political engagement among Japanese Americans to internment. For example, Wong (2011) argue that Japanese Americans as a group “are characterized by relatively high socioeconomic status, as well as stark historical experiences of racial discrimination, including the internment of Japanese Americans during World War II” (p. 180). Within anthropology, Takezawa (1991) points to the movement for redress as a unifying event for many third-

1Scholars have noted subnational authoritarianism in the U.S. South, not to mention the proceeding 250 years of chael slavery. In addition, American history is replete with other examples of racial targeting, including the targeting of Native Americans, Asian immigrants, and Latino/as.

6 generation Japanese Americans; “the ethnicity of the Sansei today is constructed not merely from racial and cultural markers of pre-war days,” she notes, “but from a sense of suering of their forebears who experienced internment” (p. 41). However, scholars of internment have also detailed devastating eects stemming from internment, including not just pecuniary ones, but also psychological ones that speak to political engagement. Hayashi (2004) writes that interned Japanese Americans “were stripped of their farmland, businesses, jobs, material possessions, and wages and suered excessive losses” and also “learned to cut commercial and cultural ties to Japan” (p. 214-15). Similarly, Kashima (2003) argues that feelings of “stigma” among those interned contributed to distrust and despair. “Wartime events,” he writes, caused internees to “question their identities as Americans. ey felt that their government not only had refused to protect them from outside prejudices but had created a mechanism for withdrawing their citizenship in order to deport them from their birthplace” (p. 218). In addition, that both direct and indirect experience with internment could yield lasting eects across generations is supported by other literature. Political orientations such as partisanship and political cynicism are correlated across generations (Jennings and Niemi, 1968). Moreover, as research on pre-adult political socialization has shown, intensive exposure to salient political events can crystallize aitudes toward policies and candidates, closing aitudinal gaps between adolescents and adults (Sears and Valentino, 1997). Furthermore, in the aermath of repression, group aachments, victimhood perceptions, and feelings of threat are correlated across generations, despite a lack of direct experience with oppression among younger generations (Lupu and Peisakhin, 2017). For example, although conversations within families about internment were brief and infrequent, children still sensed the “racial implications of the internment” (Nagata and Cheng, 2003, 268). Kashima (2003) notes that “[s]ome Sansei became angry and criticized their parents’ silence, some felt frustrated and alienated from their parents, and still others became more curious about the wartime events” (p. 218). ere is similar evidence that experience with the U.S. carceral state can have eects on family members (Walker, 2014), albeit ones that are not long-lasting (White, 2019).

7 3 eory of Internment’s Impact on Engagement

Existing streams of research examining repression, incarceration, and Asian-American politics serve as useful guideposts for understanding internment’s possible eects, but its unique circumstances warrant theorizing about relevant mechanisms and scope conditions. e majority of studies examining the political eects of repression have been conducted in autocratic or post-conict seings where opportunities to address grievances through formal venues are limited, and collective action in the form of contentious politics may be seen as an eective response to an adversarial state (Davenport, 2007). ese forces mostly appear to have had a unifying effect on targeted populations, although there are important deviations suggesting that multiple political strategies (and thus, outcomes) are possible in autocracies. In contrast, internment represented something dierent with respect to group outcomes. First, as we discuss below, the presence of accountability mechanisms such as competitive elections in the U.S. could produce expectations that group-based grievances are to be channeled through formal political processes (Collier and Rohner, 2008). e presence of both formal and informal mechanisms introduces heterogeneity with respect to political strategies, as some group members might prefer a more “accommodationist” approach to dealing with punitive institutions, whereas others might consider a more radical politics that pressures the government into making concessions (Mele and Siegel, 2017). ese tensions within groups—when paired with the experience of ethnic targeting—could lead to political disengagement by eroding faith in institutions and reducing the perceived eectiveness of collective action. In sum, the political eects of internment might depart from comparable cases elsewhere because democratic institutions induce preference heterogeneity within groups over political strategies, due to the presence of both formal and informal venues for addressing grievances. is is consistent with research on immigrants showing that underlying group aachment can aect the eects of threat (Perez,´ 2015). Second, internment locations suered from a scarcity of resources. In a maer of months, families were displaced and forced to share crowded spaces with strangers for several years. is environment was not conducive to cooperation, as substandard housing conditions and limited

8 resources activated conicts within the community (Burton, 2000, Ch. 14). Further, despite the potential for mobilization due to a sense of linked fate, internment may have reduced the perceived benets of collective action by exposing some internees to a politically fractured group. Consistent with this notion, we nd that some camps experienced substantial conict between internees that devolved into violence. us, internment may have been a “political socialization experience” that not only revealed the government’s capacity for coercion and repression, but also served as an informative signal about the possibility of successful collective action. is is consistent with research on immigrats arguing that the nature of threat and individual context is highly important (e.g., Nichols and Valdez,´ 2020). Despite some similarities between incarceration and internment, the internment process involved the blunt targeting of an entire group, whereas scholars have traditionally considered the impact of the criminal justice system to be more localized (Lerman and Weaver, 2014). However, on this particular dimension, the broader scope of internment ought to have increased political engagement by cultivating a sense of linked fate. Indeed, Walker (2020) argues that individuals who come into contact with the criminal justice system can subscribe to “narratives of injustice” – or perceptions that punitive policies are unjust due to their group-targeted nature – which can oset the demobilizing eects of “carceral contact.” However, internment not only exposed Japanese-Americans to the “second face of the state;” it also created conned and contentious spaces that eroded the quality of intragroup interactions; in other words, it divided rather than united Japanese Americans as a group. Figure 1 synthesizes our proposed mechanism in simple terms and illustrates how repressive state action – such as WWII internment – might lead to depressed political engagement via fragmentization. (Importantly, repressive actions in autocracies could also similarly cause fragmentation.) Due to the conict engendered by hostile camp conditions, we expect that internment was a politically disengaging experience that created tenuous relationships between group members. In camp locations where the community was more fractured, we expect that even greater levels of political disengagement will be observed decades aer the experience. In the following

9 Figure 1: eoretical Diagram

Unies group Increased political engagement

Government repression

Fragments group Decreased political engagement sections, we describe various dimensions of the social camp environment camps that allow us to evaluate this claim.

4 Japanese-American Internment Context and Data

e U.S. entered World War II on December 8, 1941, following the aack on Pearl Harbor by Japanese forces. On February 19, 1942, President Franklin Roosevelt signed Executive Order 9066. is authorized the forcible relocation of more than 110,000 people of Japanese descent—the majority (62 percent) of whom were American citizens—into years-long internment. Public Proclamation 1, issued on March 2, 1942, created two “exclusion zones.” Military Area 1 included swaths of the American west coast deemed militarily sensitive. is encompassed coastal California, Washington, and Oregon, as well as southern Arizona (Kashima et al., 2012). e remainder of these states constituted Military Area 2. Initially, all Japanese Americans living in Area 1 were under mandatory evacuation, but all California-based people of Japanese ancestry eventually fell under the military order. People of Japanese descent living further inland in Wash- ington and Oregon, as well as those living away from the coast, were not subject to evacuation or internment.2 Figure 2 shows the eventual exclusion zone. Over 110,000—more than 86 percent—of Japanese Americans in the continental U.S. resided within the nal exclusion zone and were relocated;

2While approximately 2,000 Japanese and Japanese Americans living in Hawaii were interned in the continental U.S., the U.S. Army did not forcibly relocate the vast majority of Hawaii’s approximately 158,000 ethnically Japanese residents (Kashima, 2003). Additional information is provided in Appendix A.3.

10 Figure 2: Exclusion Zones and Internment Camps. Source: Weglyn (1976).

California alone contained around 73 percent of Japanese Americans living in the continental U.S. (Ruggles, 2019).

Internment Camp Site Selection. e U.S. Army began scouting sites in the spring of 1942. Suitable sites had to be far from military targets, large enough to house thousands, and connected to transportation and public utilities. Because of these pressures, the U.S. Army focused on sites with these features already in place. Accordingly, all but four assembly and relocation centers were located on fairgrounds, stockyards, and exposition centers (Ng, 2002). A key inquiry for us is to assess whether and how camp characteristics impacted subsequent engagement. Figure 2 shows the locations of the 10 major “War Relocation Centers,” while Table 1 summarizes several camp characteristics. As the table shows, some camps had more military-style infrastructure, including watch towers and military-use buildings.

Camp Assignment. e U.S. Army began evacuations on March 31, 1942, using a consistent procedure (Daniels, 1993). e larger military zones depicted in Figure 2 consisted of 108 Civilian Exclusion Zones encompassing approximately 1,000 people each. Exclusion Orders posted in public locations informed people with Japanese ancestry (people who were at least 1/16 Japanese)

11 Table 1: Internment Camp Characteristics

Camp State Peak Pop. Guard Towers Demonstrations Use of Force Violence Amache Colorado 7, 318 6 0 0 0 Jerome Arkansas 8, 497 7 0 0 1 Heart Mountain Wyoming 10, 767 9 1 0 0 Minidoka Idaho 9, 397 8 0 0 0 Manzanar California 10, 046 8 0 1 1 Rohwer Arkansas 8, 475 8 0 0 0 Tule Lake California 18, 789 19 1 1 0 Poston Arizona 17, 814 0 1 0 1 Gila River Arizona 13, 348 1 0 0 0 Topaz Utah 8, 130 7 0 1 0 Sources: Ishizuka 2016, Burton, et. al. 2002, Densho Encyclopedia (see http://encyclopedia.densho.org/Fort Sill (detention facility)/), New Mexico Oce of the State Historian, (see http://newmexicohistory.org/places/lordsburg-internment-pow-camp) Note: is represents a summary of the 10 major Japanese-American internment camps. Smaller detention facilities were in active operation throughout the United States during WWII and we include these in our analysis in order to preserve power and leverage additional information about internment length and location. ese 10 camps account for 2,545 of the 2,777 interned Japanese Americans in the JARP. that they were required to register and prepare to transfer. In the following days, the head of each household would report to a nearby control center, register, and receive instructions for relocation. Evacuees were given six days to travel to one of multiple assembly centers located throughout California, Oregon, and Washington. Internees spent an average of 100 days in an assembly center before being transferred to a permanent internment camp (Kashima et al., 2012). With few exceptions, evacuees were transferred from assembly centers to internment camps according to criteria unlikely to be correlated with their personal backgrounds, an assertion that we formally evaluate in Section 7.1 and is also discussed extensively in Shoag and Carollo (2016). Evacuees in assembly centers with the most dangerous conditions (e.g., no indoor plumbing) were moved to internment camps rst (Burton, 2000). U.S. Army records suggest that it made eorts to move evacuees waiting at assembly centers to the nearest internment camps with climates closest to what they had known at home (Burton, 2000). Beyond these two concerns, families were assigned—together when possible—to internment camps that were (1) suciently complete in terms of construction to house evacuees and (2) had room for them. We see direct evidence of this in the War Relocation Authority’s (WRA) records and graphically in Figure 3. For instance, Figure 3 shows that internees from Los Angeles County were primarily sent to the nearby assembly centers (le) in Manzanar, Pomona, and Santa Anita. e same internees were distributed across a variety of internment camps (right) in Arizona (Gila River, Poston), Colorado (Granada), Wyoming

12 Figure 3: Distribution of Assembly Center and Internment Camp Locations among L.A. Internees

10000 10000

7500 7500

5000 5000 Internees Internees

2500 2500

0 0 Topaz Poston Jerome Rohwer Granada None Minidoka Tulare Mayer Tule Lake Tule Gila River Manzanar Fresno Turlock Salinas Merced Pomona Portland Puyallup Tanforan Pinedale Stockton Manzanar Marysville Santa Anita Sacramento Heart Mountain

(a) Assembly Centers (b) Internment Camps

(Hearth Mountain), and Arkansas (Rowher, Jerome). us, conditional on initial pre-internment location, nal camp assignment was exogenous to family characteristics.

4.1 Data Sources and Key Variables

Our primary interest is in how internment impacted the political aitudes of those interned and their direct descendants. For this, we draw on the Japanese American Research Project (JARP), a nationally representative, multi-wave survey of 4,153 mainland Japanese Americans that was conducted between 1962 and 1968. (See Appendix A for details regarding survey modes and timing.)3 e survey excludes Hawaii-based people of Japanese descent. (As we discuss above and in Appendix Section A.3, this is not a problem for our substantive inferences as only a very small fraction of Hawaiians of Japanese ancestry were interned.) Although JARP is an older dataset and was collected approximately 20 years aer internment, we use JARP for several reasons.4 First, the JARP was conducted when many who were interned were still alive and

3e JARP was used as the primary data source in Levine and Rhodes (1981). As the authors note, however, their interest was mostly in examining the social and political incorporation of Japanese Americans, rather than the eects of internment (Levine and Rhodes, 1981, 6). 4One concern with the use of this survey is that deaths between the time of internment and the survey may not be random, and this could correlate with our outcome variables. If this were the case, JARP demographics such as age would depart from other data sources from the period of internment. However, as we show in Appendix A, the JARP is comparable to administrative data sources such as the War Relocation Authority (WRA) data.

13 politically active. (Using data collected today would be impossible; as of our writing, those interned as infants would be in their late 70s.) Second, other surveys of Asian Americans tend to be underpowered with regards to Japanese Americans. ird, JARP includes information about where respondents lived between 1932 and 1941, allowing us to leverage conditionally exogenous variation in camp assignment (following Shoag and Carollo, 2016). Lastly, JARP allows us to evaluate eects across generations because it includes three immigrant cohorts. ese are (1) Issei (1st generation Japanese immigrants), (2) Nisei (descendants of Japanese-born immigrants, or 2nd generation), (3) Sansei (3rd generation). Key features of the JARP data are summarized in Table 2. e JARP data are constrained in that camp assignment is only available for Issei, despite the fact that many Nisei and even some Sansei were interned (Table 2). In the results that follow, we link respondents in JARP using the survey’s family identier and assign subsequent generations the internment camp reported by Issei members. at is, we assume that all members of the same family were interned at the same place. is assumption is plausible, given that the U.S. Army prioritized keeping families together. It is also important to note that, in order to protect respondent privacy, the JARP recorded pre-internment locations at the state level with the exception of Cal- ifornia. California respondents have codes that place them in a cluster of metropolitan areas, but these clusters are based on city size rather than geographic location. Our main results eectively control for state, but we demonstrate their robustness by including more specic locations from additional data and controlling for more precisely recorded birthplace instead of 1940 residence in Appendix G. In addition we include a xed eect for immigration generation since JARP used dierent questionnaires for each cohort. is also makes substantive sense: cultural and political dierences as well as dierences in citizenship status (discussed below) across these cohorts could have impacted internment as well as political aitudes. In addition to JARP, we use the WRA’s records to validate our results and provide richer de- scriptions of the internment process.5 e WRA recorded detailed information about internees,

5See the Database of Japanese American Evacuees, Record Group 210, National Archives, https://www. archives.gov/research/JapaneseAmericans/wra.

14 Table 2: JARP Sample Demographic Information

Generation Observations Age Gender Married California Oregon Washington Other Interned Families Issei 1, 047 72 0.66 0.57 723 47 127 150 0.82 0.70 Nisei 2, 304 41 0.52 0.81 1, 470 101 266 467 0.76 0.86 Sansei 802 22 0.47 0.30 104 2 24 672 0.21 0.85 Total 4, 153 45 0.55 0.65 2, 297 150 417 1, 289 0.67 0.82 Notes: Age represents mean age; gender represents proportion male, and married represents proportion married. California, Oregon, Washington, and Other represent counts of Japanese Americans living in each location on the eve of the internment period. Interned represents the proportion of respondents in each generation who were interned Families represents the proportion respondents in a family where at least one member was interned including name, age, gender, addresses prior to internment, family units, education, and occupation. ese records also contained assembly center and internment camp assignment information for 109,384 Japanese Americans interned during WWII. In Appendix A, we show that the sample characteristics of the JARP are generally consistent with descriptive data from the WRA, which provides strong evidence of JARP’s representativeness; this also lessens concerns about the time lag of the JARP data. Lastly, we also use the WRA data in support for the idea that, conditional on pre-internment location, camp assignment was unrelated to personal characteristics.

Internment Status. Given that the data span three immigration cohorts, we operationalized exposure to internment in three ways: (1) Direct Exposure, respondents who were themselves interned, either solo or with family (67% of sample); (2) Family-Only Exposure, respondents who were not themselves interned but had at least one family member in the sample interned6 (18% of sample); Baseline, respondents who were not interned and did not have an interned family member in the JARP (15% of sample).7

Individual covariates. We also include gender and age, which are pre-treatment features that may aect our outcomes. (Age, for instance, likely aects political engagement independently of the internment experience.) Finally, our analysis of camp-level eects relies on controls for respondents’ place of residence on the eve of internment. Since the internment camp to which

6Each family in the JARP was assigned a family identier, which can be used to calculate how many respondents within a given family were interned. 7Internment status might be subject to underreporting. Focusing on those who were eligible for internment, 80% of our sample reported being interned, which is comparable to the estimate derived from IPUMS data.

15 people were ultimately conned was orthogonal to pre-treatment characteristics, it was largely a function of where they lived at the onset of WWII. All of our analyses of camp eects therefore control for pre-treatment area of residence. We do not control for citizenship status because it was not asked for all individuals in JARP and because it presents signicant post-treatment bias problems. For example, just 22 of the 591 citizen Issei in our sample obtained citizenship before 1941, meaning that the remainder may have been inuenced directly by their internment experiencing in deciding whether to pursue citizenship. However, we do include xed eects for cohort (Issei, Nisei, and Sansei), which accounts for much variation in citizenship. Nisei and Sansei, for example, were not asked about their citizenship status; however, all but 58 Nisei and all but 22 Sansei JARP respondents were born in the United States, making them citizens by birth.

Camp environment covariates. We gather new data on camp conditions to evaluate how dif- ferent camp conditions aected group cohesion, per our theory. First, we operationalize the level of militarism in camps by recording the numbers of watch towers per 1,000 people in each camp. Second, we draw upon multiple historical resources to identify relocation centers that experienced demonstrations, violence between internees and civilians, or the use of force by military personnel against internees (shown in Table 1). “Demonstrations” were oppositional demonstrations by some internees against personnel to protest resource shortages, working conditions, failures to pay claims when workers were injured, etc. Importantly, other groups in the camps (like the Japanese American Citizens League) preferred cooperation with Army and Wartime Civil Con- trol Administration sta to demonstrations, making this variable an expression of dissatisfaction by specic subsets of internees and a marker of disagreement within the group. “Violence” represents violence between internees or violence between internees and the surrounding civilian population. Lastly, we incorporate contextual features such as the percent white in the surrounding county (from the 1940 Census) and the percent of the county-level vote-share won by Franklin Roosevelt in 1940. We use these camp characteristics in Section 7.1.

16 Outcome Variables. Our focus is on political engagement, a topic on which we have several JARP questions.8 First, “political interest” is a four-item ordinal scale ranging from “No interest at all” (0) to a “A great deal” (3) (x¯ = 1.29; s = .83).9 Second, “political engagement” is a binary item asking respondents whether non-family members have asked them for advice regarding politics (pˆ = .17). ird, “faith in government” is a binary item asking whether respondents disagreed that “most people in government are not really interested in problems of the average man.” (pˆ = .43). Finally, preferences for dissent are measured using a trichotomous variable that captures whether respondents would have preferred a leadership strategy during the internment process that emphasized dissent (-1), accommodation (1), or neither (0) (x¯ = .61; s = .77). Substantively, preferring accommodation indicates a more politically disengaged aitude. We focus on these outcomes for several reasons. First, they are representative of the political topics (interest, participation, views of government) about which respondents were asked in the JARP. Second, we focused on questions for which question wording and the coding of responses were suciently similar across two or more generations to allow us to make these comparisons. Lastly, our use of these outcomes is consistent with other studies involving the JARP that have used these measures as indicators of engagement (Levine and Rhodes, 1981, Ch. 7).

5 Internment Status and Political Engagement

Before we delve into camp-specic eects, we investigate the possible role internment status (i.e., the relationship between direct exposure or family-only exposure to internment) played in shaping political engagement. For this, we leverage the fact that nearly 86 percent of people of Japanese descent living in the continental U.S. resided in the exclusion zone, but 14 percent did

8We do not present results on turnout and vote choice. Only Issei were asked whether they voted in specic elections and more than 42% of them in our sample are non-citizens. Also, over 40% of Sansei in the JARP data were under 21 at the time the survey was administered, making them ineligible to vote. us, the JARP limits our power to investigate this question. e directionality of an internment eect is also unclear. Internment was ordered by a Democratic president, but prominent Republicans supported internment and restrictions on Japanese immigration. 9e Issei version of this question had dierent response options, allowing for “No” or “Yes” responses. We code these responses as 0 and 1 on a 0-3 scale.

17 Internment Status and Political Engagement

Political Interest

Political Distrust

Group

Direct Exposure Family−Only Exposure Outcome

Political Advice

Leadership Approach

−0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 Coefficient Estimate

Figure 4: e relationship between internment status and political engagement. Political interest models rely on data from all three generations; political advice, leadership approach, and political distrust models are based on the Nisei and Sansei sample. 95% (narrow bar) and 84% (heavy bar) condence intervals (CIs) are shown. 84% CIs allow for visual tests of equality across coecients; 95% CIs results in Type II errors when comparing visible coecients (Bolsen and ornton, 2014). Sample sizes are reported in Appendix C. not. is variation lets us assess the relationship between whether a person or one of their family members was sent to a camp and subsequent political aitudes—a relationship that many scholars believe could have galvanized Japanese Americans (Wong, 2011). Although this analysis is not causal, we investigate alternative explanations below. Figure 4 reports results from a linear model regressing indicators of political engagement on measures of direct exposure and family-only exposure to internment with xed eects for pre- internment residential locations and generational identiers . We also control for age and gender. (e full specication is provided in Appendix Table C.) e gure shows that those who were interned are about 13% of a scale point (± 9% of a scale point) less likely to report an interest in American politics than those who were not, a statistically signicant dierence. ese paerns are similar among Japanese-Americans who themselves were not interned but who had family that were. ese individuals are about 18% of a scale point (± 9% of a scale point) less likely to express interest in politics. ese estimates correspond to a movement of approximately 3% and 4% along a three-point scale, respectively. For both distrust and political advice, estimates

18 are in the expected direction, but there is considerable uncertainty. Additionally, those who had direct exposure to internment are about 11% of a scale point (± 11% of a scale point) more likely to support a “peaceful and orderly” leadership approach during internment than one employing protest and dissent, relative to others. Among those who were not interned themselves but had family who were, this dierence is approximately 19% of a scale point (± 11% of a scale point). ese two estimates reect a 3% and 6% movement across a three-point scale, respectively. Consistent with intergenerational transmission, coecient estimates for both internment status measures are strikingly similar across outcomes. Formal tests of dierences between the two never reach conventional levels of statistical signicance (Appendix Table 7).

Alternative Explanations in Military Service, Earning Potential, and Arrival Date. ese results provide evidence that internment suppressed political interest. But could other explanations drive this nding? One possibility is that there is unexplained confounding between those of Japanese ancestry who were interned (or had family interned) and those who were not. How- ever, using data from the 1940 Census, we fail to reject the null hypothesis of no mean dierence between Japanese Americans inside and outside of the exclusion zone with respect to gender, marital status, age, education, employment rates, and occupational class (see Appendix Section E.2). We also fail to nd evidence that military service, income, or dierences in arrival date explain our paern of results (see Appendix Section H).

6 Internment Length and Political Engagement

We next evaluate the association between internment length and political engagement. is analysis is not strictly causal, especially because some internees petitioned for early release. ere were 14 conditions for early release, which included promising not to live among other Japanese Americans, conforming to American customs, and not moving to an area with hostility toward Japanese Americans (Yonemura, 2019). (is also included individuals released for military service, which we showed in Section 5 is not driving our results.) Many of those released early were

19 Table 3: Internment Length - Summary Statistics

Internment Length N Percentage of Interned Sample Less than 1 Year 313 11.50 1 - 2 Years 498 18.30 2 - 3 Years 678 24.90 3 - 4 Years 1, 064 39.10 4 - 5 Years 157 5.80 5 + Years 8 0.30 young people going east for university studies, and, according to Yonemura (2019), the vast majority of people granted indenite leave were ages 15 to 35. In the analyses below, we control for age, which accounts for some of this.10 Table 3 provides summary statistics on internment length. Roughly 12 percent of internees in our sample were released within one year, while 45 percent were detained longer than three years; this is consistent with the fact that most people stayed in camps until the camps were closed, thus providing an end-date to internment that is exogenous to personal characteristics. We would suspect, in accordance with the literature on ethnic targeting (Lupu and Peisakhin, 2017) and carceral contact in the United States (Weaver and Lerman, 2010), that longer interments would more strongly demobilize and depress civic engagement. Aer all, shorter detainments may have lile eect, but longer internments may expose internees to more intragroup conict, perhaps souring them on future engagement (Weaver and Lerman, 2010). To analyze this, we subset the data to only those with direct experience with internment. We again control for age, gender, and generational cohort. ose interned for longer periods had greater aenuation in political engagement, shown in Figure 5. (e full specication is provided in Appendix Table C.2). An additional year of being interned is associated with approximately 1.4% of a scale point decrease in political interest (± 2.6% of a scale point, so narrowly insignicant), a 4.2 pp increase in distrust (± 2.2 pp), a 3.4 pp decrease in the likelihood of being sought out for political advice (± 1.6 pp), and 4.3% of a scale point (± 3.4% of a scale point) increase in

10In Appendix C.2, we address possible non-linearities in age by including an indicator for the subgroup described in Yonemura (2019). We also subset on respondents whose families remained in internment camps aer 1945, and thus, were not eligible for early release. Our key ndings are unaected in both cases.

20 Internment Length and Political Engagement

Political Interest

Political Distrust Outcome

Political Advice

Leadership Approach

−0.05 −0.02 0.00 0.03 0.05 0.08 Coefficient Estimate

Figure 5: e relationship between internment length and political engagement. Political interest models rely on data from all three generations; political advice, leadership approach, and political distrust models are based on the Nisei and Sansei sample. 95% CIs are shown. Sample sizes are reported in Appendix C.2. supporting a “peaceful and orderly” leadership approach during the internment process. To put this into context, those who were interned for four years or more (6% of the interned sample) are approximately 4% of a scale point less likely to report an interest in American politics than those who were interned for less than one year (12% of the interned subsample). Moreover, they are approximately 17 pp more likely to express distrust in government, 14 pp less likely to be sought out for political advice, and 17% of a scale point more likely to support a “peaceful and orderly” leadership strategy. is corresponds to a movement of about 6% across the three-point scale.

7 Group Fracturing in Internment Camps

ese ndings show disengagement is associated with internment status and length. In this section, we examine the experience more closely to explain these ndings and to shed light on our theory of internment as a divisive, fractionalizing event. Additionally, as we discussed in Section 4, conditional on initial place of residence, assignment to one of the 10 major internment camps was unrelated to individual or family aributes (Shoag and Carollo, 2016). is allows us to estimate the causal eects of exposure to specic camp conditions, conditional on internment, on downstream political behavior in order to gauge possible mechanisms.

21 We expect that these conditions are important in shaping political aitudes. As suggested by the custodial citizenship literature (Weaver, Hacker and Wildeman, 2014), internees in camps that experienced more unrest, demonstrations, or backlash may have experienced greater disengagement. First-person internment accounts frequently emphasize two socially pertinent features: (1) the struggle to access basic resources and (2) unrest among internee factions. Shortages of basic necessities were widespread. Flimsy quarters meant exposure to vermin and extreme weather (Pistol, 2017). Grievances over basic needs sparked conict, driving demonstrations and strikes across several camps and inaming tensions among internee factions. At Tule Lake, agricultural workers protested authorities’ unwillingness to compensate the widow of a worker killed in a trucking accident; the camp’s project director responded by using Poston and Topaz internees as strike breakers (Burton, 2000). At Manzanar, internees led an investigation into supply shortages and founded the Mess Hall Workers Union in 1942. Tensions between this union and the pro- American Japanese-American Citizens League led to larger-scale violence on multiple occasions (Burton, 2000). ese activities broadly aected camp populations, and their eects were exacer- bated still further by the way life in camps interfered with traditional family networks. For many, home life was replaced by life in a barracks, and meals were increasingly taken with members of an internee’s work detail rather than her family. Scholars of internment have hypothesized that these changes may have reduced communication and increased ssures between family members (Ng, 2002). Per our theory, we expect that being imprisoned in a camp that witnessed demonstrations or violence among internees might further disengagement for several reasons. Internees who demonstrated or went on strike did so because they believed that camp authorities—the arm of the state with which they interacted most—were not commied to providing basic needs. At Manzanar, for example, internees found evidence that camp ocials were smuggling out sup- plies, causing shortages. Violent disagreements among internees would similarly have depressed political activity by straining communication and fostering resentments in the community. We explore these possibilities in Figures 6 (demonstrations) and 7 (violence). ese show the

22 results of OLS regressions of outcomes on whether the respondent was relocated to an internment camp in which a faction-driven demonstration or violent event took place. In both analyses, we include xed eects for immigration cohort, as well as controls for pre-internment location, age, and gender. (JARP includes case internment location only for Issei; we again assume that interned Nisei and Sansei were sent to the same camps as their Issei relatives.) As before, we assess camp- treatment eects across two groups: (1) Direct Exposure (people who were themselves interned, either solo or alongside family) or (2) Family-Only Exposure (people who were not interned, but had Issei family who were). We do not estimate eects on those who were not interned and had no family interned.

Oppositional Demonstrations. Figure 6 shows that respondents who were interned in camps where demonstrations by factions took place were 5% of a scale point (± 8% of a scale point) less likely to report being interested in politics, although this is narrowly insignicant. Among those who were not themselves interned, but had family who were, this eect is of a larger magnitude (nearly 9% of a scale point), but insignicant (± 11% of a scale point). In terms of trust in government, respondents who were interned were approximately 8 pp (± 5 pp) more likely to say that the government is not concerned with everyday people; results are similar for respondents whose families were interned. Both are signicant. Respondents interned at camps that witnessed such demonstrations were 2.4 pp (± 2 pp) less likely to have been approached for political advice, though this nding is signicant only for those who themselves were interned (and not for those who only had family interned). Lastly, the results suggest that internees sent to camps that experienced demonstrations were signicantly more likely to favor leaders who espoused peaceful transitions, perhaps because such respondents did not believe protesting would yield concessions or because they feared retribution. On this point, those directly interned are 0.08 (± 0.05) scale points (relative to the -1, 0, 1 scale) more likely to prefer leaders who backed orderly transitions. e ndings are similar in magnitude but insignicant for those who were not themselves interned but who had family who were. Overall, the results support the hypothesis that labor unrest and deprivation at camps has a

23 Effect of Witnessing Demonstrations While Interned

Political Interest

Political Distrust

Group

Direct Exposure Family−Only Exposure Outcome

Political Advice

Leadership Approach

−0.2 −0.1 0.0 0.1 Coefficient Estimate

Figure 6: Eects associated with oppositional demonstrations in a camp. 95% (narrow bar) and 84% (heavy bar) CIs are shown. Controls include age, gender, pre-internment residential location, and survey wave (Issei, Nisei, Sansei). Political interest models rely on data from all three generations; political advice, leadership approach, and political distrust models are based on the Nisei and Sansei sample. Sample sizes are reported in Appendix D. depressive eect on political engagement. We detect slightly stronger ndings for those individuals themselves interned, although formal tests assessing the dierence in eects between direct versus family-only exposure are insignicant (Appendix D). is provides suggestive evidence in favor of an inter-generational transmission of aitudes, consistent with our ndings above.

Violence. Results for the camp violence models are presented in Figure 7. Respondents who lived through violent episodes while they were interned express signicantly lower levels of interest in American politics than counterparts who did not experience violence (7.5% of a scale point, ± 6% of a scale point). However, the eect is only signicant for those who themselves were interned, either on their own or alongside family. For individuals who only experienced the eects of internment via interned family, the eect is in a similar direction but not signicant. For trust in government, internees in camps that witnessed violent episodes amongst internees themselves were 2 pp (± 7 pp) more likely to report believing that the government had lile concern for the problems faced by average people. Respondents who only had family interned were signicantly more likely to express skepticism of the government, scoring 10pp (±

24 Effect of Witnessing Violence While Interned

Political Interest

Political Distrust

Group

Direct Exposure Family−Only Exposure Outcome

Political Advice

Leadership Approach

−0.1 0.0 0.1 0.2 Coefficient Estimate

Figure 7: Eects associated with violent conditions in a camp. 95% (narrow bar) and 84% (heavy bar) CIs are shown. Controls include age, gender, pre-internment residential location, and survey wave (Issei, Nisei, Sansei). Political interest models rely on data from all three generations; political advice, leadership approach, and political distrust models are based on the Nisei and Sansei sample. Sample sizes are reported in Appendix D.

4pp) higher on distrust. ose interned in camps that experienced violence among internees also reported lower rates (2 pp) of being sought out for political advice, but the nding is not signicant for both groups. Lastly, the respondents directly interned in camps that experienced violence were 0.08 scale points (± 0.07) more likely to support leaders who did not favor protest. e eect for those were not themselves interned but who had family who were are similar in magnitude, but narrowly insignicant. Overall, these eects are slightly more modest than those we found regarding demonstrations. However, they provide suggestive evidence that violence had a negative eect on political engagement. In addition, we cannot rule out dierences in treatment eects transmied across generations (shown in Appendix D), although our ndings are mostly signicant for those who experienced internment themselves.

7.1 Robustness of the Results

Our results lend support to a demobilizing eect associated with internment, with particularly strong eects among those who were interned longer and those with direct connections to camps

25 exhibiting labor conict or violence. We also nd a corresponding, albeit slightly weaker eect among those who only had family members interned, lending evidence to the inter-generational transmission of aitudes. We note, however, some threats to this analysis, the most pressing being (1) confounding in camp assignment and (2) dierences in pre-internment locations.

Robustness to Unobserved Confounders in Camp Assignment. Following the historical record and other work on internment (e.g., Shoag and Carollo, 2016), we assume that, for individuals who were themselves interned (either solo or alongside family members), camp assignment is orthogonal to pre-internment characteristics at the individual level. However, internees may still dier on characteristics impacting political engagement, even conditional on location. We rst assess whether camp assignment is related to any pre-treatment covariates for those were personally interned. Since internment camps are discrete units, we model camp assignment as a multinomial logistic function of age, gender, and pre-internment location. Values in Table 4 correspond to z-scores, calculated by dividing coecients from the multinomial logit by their corresponding standard errors, for each covariate. In the age and gender columns, no camp is associated with a test statistic greater than 1.96 or less than -1.96. (Pre-internment location, on the other hand, is signicantly associated with camp assignment in our model, but this is what we expect given the way camp assignment was carried out.11) is analysis is consistent with Shoag and Carollo (2016)’s Table 1, which nds individual covariate balance across the camps using redress data, as well as additional analyses in Appendix Section B, which nds covariate balance using the more expansive WRA data.

11Pre-camp location is a three-digit numeric code, which we leave as a numeric variable in this model to preserve power; locations in the same region and state will be close in value and locations across states will dier considerably in value, which provides reasonable distinctions between dierent pre-camp locations.

26 Table 4: Covariate Balance Across Internment Camps

Age Gender (Male) Pre-Camp Location

Jerome -.88 1.27 -1.43 Heart Mountain .38 -.54 -2.74 Minidoka .14 .31 -1.97 Manzanar -.18 1.58 -2.73 Rohwer 1.37 .15 -4.17 Tule Lake -.49 .68 -1.07 Poston -.09 .12 -2.06 Gila River .04 -.64 -1.41 Topaz .67 -.33 2.34

Note: Reference category is Granada (Amache)

Another possible challenge is that the government reassigned or sequestered internees based on their level of resistance aer their initial camp assignment. An example of this is the WRA’s loyalty questionnaire, which was administered to men aged 17 and over beginning in 1943. Re- spondents who answered that they would not register for selective service and could not pledge unconditional loyalty to the U.S. were labeled “disloyal” and sequestered at Tule Lake. To address this, we replicate the analyses subseing to JARP respondents who were younger than 17 in 1945. e results from that analysis are consistent with the eects of internment that we report in this section. (See Appendix H for these results.)

Location Prior to Internment. Identifying the eect of camp environment assumes that every Japanese-American family living in roughly the same area was treated similarly by the WRA. Figure 8 supports this assertion. Each panel in Figure 8 displays the distribution of internees living in California, Oregon, and Washington on the eve of WWII. Panel (a) describes this information using the WRA’s records, while Panel (b) shows the same distribution using JARP data. (is is, again, only for those individuals who themselves were interned.) If the assumption that the U.S. Army prioritized proximity and speed in transfer is reasonable, then most internees from a given state should have been held in camps closest to their state of residence. is is borne out by the two gures. For example, Japanese Americans living in Oregon and

27 Figure 8: Assignment to Internment Camp by State of Residence

California Oregon Washington California Oregon Washington 400

15000 300

10000 200 Internees Internees

5000 100

0 0 Topaz Topaz Topaz Topaz Topaz Topaz Poston Poston Poston Poston Poston Poston Jerome Jerome Jerome Jerome Jerome Jerome Rohwer Rohwer Rohwer Rohwer Rohwer Rohwer Granada Granada Granada Granada Granada Granada Minidoka Minidoka Minidoka Minidoka Minidoka Minidoka Tule Lake Tule Lake Tule Lake Tule Lake Tule Lake Tule Lake Tule Gila River Gila River Gila River Gila River Gila River Gila River Manzanar Manzanar Manzanar Manzanar Manzanar Manzanar Heart Mountain Heart Mountain Heart Mountain Heart Mountain Heart Mountain Heart Mountain

(a) WRA Data (b) JARP Data

Washington were sent to the northern-most camps in California (Tule Lake), Wyoming (Heart Mountain), and Idaho (Minidoka). Californians were sent to camps located near them—Manzanar, Poston, and Gila River for people living in southern California and Tule Lake for people living in northern California. Lastly, we note strong correspondence between the two gures, providing assurance that JARP’s self-reported data accurately portray internment assignment.

7.2 Alternative Mechanisms of Demobilization

Our analyses suggest that dierences in political engagement among Japanese Americans varied not just by internment status, but also by features of the camps themselves, with exposure to unrest being an important mechanism behind demobilization. However, a potential challenge is the possibility that any camp eects are the result of another factor correlated with internment location. Here, we examine the two likeliest alternatives: (1) the severity of camp environments, and (2) the camps’ surrounding racial and political environments. We evaluate and set aside additional mechanisms—including loss of income—in the Appendix.

Severity of Camp Environments. Previous work implies that harsher internment conditions could have instilled a greater fear of the state or of repression, thereby having greater demobilizing

28 eects. We test this by (1) looking at the use of state force against internees and (2) looking at the severity of camp conditions themselves. With regards to the use of force, the prediction is not borne out, as shown in Figure 9b, which analyzes camp eects according to whether the camp experienced at least one use of force by military personnel against internees. e point estimates of this eect on political distrust, advice, interest and preferences over leadership are close to zero. Only among those with family exposure is there a single signicant nding (on political interest); all other ndings are insignicant. One reason we might observe disengagement for violence among internees (discussed in our previous section), but not for cases in which military personnel used force, is the dierence in scale. Episodes of violence among internees generally tended to precede or follow large demonstrations or involve large groups. Incidents in which guards used force against internees, in contrast, tended to be more isolated and rare. To give an example, we coded a guard at Topaz camp fatally shooting an elderly internee for standing too close to a perimeter fence as use of force (Burton, 2000). Violent confrontations between large groups of internees would have exposed more internees to unrest than isolated shootings such as this, which involved few individuals. Second, we investigate a second component of severity: the extent to which internees lived under militarized conditions. ese conditions manifested in physical space through the use of guard towers, barbed wire fencing, and barracks-style housing for internees, and served as con- stant “reminders of [internees’] lack of freedom” (Burton, 2000). We operationalize the militarization of space as the number of guard towers per one thousand internees at peak camp population. Figure 9a shows that respondents interned in more militarized camps (or with relatives who were) were 8% of a scale point (± 8% of a scale point) more likely to express interest in American politics, a nding in the opposite direction from what we would expect. is eect is, however, only signicant among respondents who were not interned but who had family members who were. Other ndings are, across the board, insignicant and with point estimates close to zero. is suggests that the disengagement paerns observed in the JARP sample are due to the internees’ collective exposure to unrest and fractionalization, rather than

29 Figure 9: Camp Eects: Militarized Conditions

Effect of Being Interned in Highly Militarized Camp Effect of Witnessing Use of Military Force While Interned

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.1 0.0 0.1 0.2 −0.1 0.0 0.1 Coefficient Estimate Coefficient Estimate (a) Militarism (b) Use of Force Note: 84% and 95% CIs are shown. Controls include age, gender, and pre-internment residential locations. Political interest models rely on data from all three generations; political advice, leadership approach, and political distrust models are based on the Nisei and Sansei sample. dierences in the severity of the camp conditions.

Surrounding Political and Racial Environment. Although camp locations were remote, exposure to local culture provides a possible alternative explanation for the results in Section 7. For example, if internees were sent to camps located in nearly exclusively white or extremely conser- vative areas, this might have led them to have lowered feelings of belonging, thereby suppressing overall political engagement. (Wong, 2011). We test for this possible alternative explanation by analyzing the eects of (1) the proportion of the internment camp’s county population that was white in 1940 and (2) the political climate, as measured by Franklin Roosevelt’s 1940 share of the two-party vote. We fail to nd any evidence that these variables consistently predict political engagement (see Appendix F).

30 8 Conclusion

Aer the aack on Pearl Harbor, thousands of people of Japanese ancestry were held for years in militarized internment camps. Our ndings suggest that this unjust internment strongly af- fected their subsequent political behavior in ways that speak not just to scholarly discussions but also to ongoing current events. First, we nd that those with direct and family experience with internment are less politically engaged and that this association strengthens with internment length. Second, we leverage that camp assignment was exogenous to individual or family characteristics conditional on pre-internment location, nding that camp conditions are associated with decreases in political engagement. In particular, those assigned to camps exhibiting intragroup conict experienced larger disengaging eects. is provides evidence for our theory that a key way in which internment was demobilizing was in weakening group ties and in undermining political cohesion. Lastly, across every measure of political engagement, we cannot nd meaningful dierences in the eect of internment among those directly interned versus those who experienced internment through a family member. is suggests a depressing eect of internment that extended across generations. Our study makes several contributions to scholarly discussions. From the perspective of the comparative politics literature, our paper highlights the potential depressive eects of punitive state interactions on political engagement in the unusual context of a liberal democracy. is is an important inquiry: to date, existing work on the topic of repression and ethnic targeting has mostly focused on weak or authoritarian states. Our ndings dovetail with those of Lupu and Peisakhin (2017) and Rozenas, Schue and Zhukov (2017), who nd that repression increases distrust toward the state. (However, in contrast to Lupu and Peisakhin (2017), we do not observe increased mobilization or political engagement in the targeted group.) Additional research could explore whether these dierences between democracies and autocratic regimes are shaped by the impact of government repression on weakening or fracturing group ties, as we posit, or by the nature of repression eorts (as suggested by, e.g., Rozenas and Zhukov, 2019). We also contribute to research in American politics examining the political consequences of

31 growth in the carceral state. Much of this literature has viewed exposure to penal institutions in a binary fashion (contact versus no contact). Although our context is dierent in scope and in populations aected, we nd that conditions within these institutions maer. Conditions that foster intragroup conict increase the likelihood of distrust and disengagement in the future. Potential avenues for future research could assess whether variation in the severity and duration of punitive encounters with the state yield worse consequences for aected groups. Moreover, a more complete accounting of mechanisms across dierent contexts could illuminate whether group fragmentation is a primary driver of disengagement and whether it is the result of the social processes described here or more material losses. Lastly, our paper contributes to a growing literature on Asian-American public opinion and political behavior. Previous work demonstrated that Japanese Americans have high rates of political participation, with scholars positing that internment may have had a galvanizing eect (Wong, 2011). Our ndings complicate this explanation, suggesting that those with rst-hand or secondary contact with internment are, if anything, less likely to be politically engaged. is leaves open several questions that are worthy of further research, including whether internment indirectly had galvanizing eects via the movement for redress in the 70s and 80s. We conclude by noting this study’s relevance beyond scholarly discourse, particularly as liberal democracies have increasingly turned to the detention of minority or immigrant groups. e psychological and material eects of these policies suggests that government must think deeply about immigrant political incorporation aer these adversarial interactions. Our study—which suggests that detentions that happen in the modern-day could suppress political engagement among these groups for generations to come—urges caution in the use of these punitive policies.

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36 Appendix

A Survey Sampling and Data Collection

e Japanese American Research Project (JARP) is a three-generation survey of Japanese Americans carried out under the direction of UCLA sociologist Gene Levine. Funded in collaboration with the Japanese American Citizens League (JACL), the Carnegie Corporation (1964), and the Behavioral Sciences Research Branch of the National Institute of Mental Health (1966), the study was designed to study the “ways in which three generations (Issei, Nisei, and Sansei) of Japanese-American families adapted to social, cultural, educational, occupational, and other institutions of American life” (Levine, 1997). Researchers drew a stratied random sample from a list of 18,000 Japanese Americans belonging to the Issei generation who had survived until 1962 and lived in the mainland U.S. at the time. e sample was stratied by county, neighborhood housing quality tier, and the population density of the Japanese-American community within each county (Levine, 1997). Levine’s team asked participating Issei respondents to provide contact information for their children (Nisei) and grandchildren (Sansei). We have no evidence that Issei refused to provide information about their relatives. Surveys were conducted via a mix of personal interviews, mail-in questionnaires, and telephone interviews between 1962 and 1968. Issei were rst interviewed between 1962 and 1966, while Nisei were interviewed over several months in 1967 and Sansei largely lled out questionnaires throughout 1967 and 1968. is approach to sampling has two implications: rst, we expect the stratied random sampling approach to yield a representative sample of surviving Issei12 - whether they were in the interned group or the non-interned group. We provide evidence for this in Section A.1. Second, this approach to sampling should provide a representative sample of other generations because inclusion in the survey should be independent of Issei’s decisions to have children. Finally, families included in the survey are matched directly since respondents identify and provide information for their own family members. is means family IDs in the JARP should identify members of linked family units much more accurately than surveys based on probabalistic merges across dierent data sets.

A.1 Is the JARP Representative? To assess whether or not respondents to the JARP survey who were interned are a representative sample of internees, we can compare internees in the JARP to the WRA records. We have to do this carefully because the information about internees recorded in the WRA data was recorded upon internment in 1941-1946. e JARP data was recorded between 1962 and 1968 depending on the survey wave, which means approximately 20 years elapsed between the JARP survey and the end of WWII. is means the same internees recorded in the WRA in 1942-1945 might look substantially dierent by the time they completed the JARP (in terms of education, occupation, etc.). Another challenge is that some variables in the JARP coded in suciently dierent ways that they cannot be easily compared (e.g., occupational categories). Still, we focus this analysis on variables that are either relatively xed or unlikely to change across the WRA and JARP.

Location Section 7.1 already provides some evidence for congruence between the WRA and JARP data; Figure 8 demonstrates that the internment camp assignments recorded for JARP respondents living in California, Oregon, or Washington on the eve of internment are representative of the same assignments for the nearly complete roster of internees recorded in the WRA data. is comparison covers the vast majority of people interned: over 98% of people in the WRA records lived in California (83.9%), Washington

12Just 6% of internees in the WRA records were over 60 years old during the internment period, with 19% of Issei - the oldest cohort of internees on average - falling into this category. Accordingly, we do not expect age-related censoring to have been a signicant concern by the time researchers began to collect data for the JARP in 1962. Similarly, records of deaths across the 10 largest internment camps show 1,879 deaths within the camps out of an interned population of approximately 120,000 (Burton, 2000).

1 (11.5%), or Oregon (3.2%) at the beginning of the internment period. is gure is almost the same for internees in the JARP data, similarly 98.7% of whom were distributed across California (79.9%), Washington (13.7%) and Oregon (5.1%).

Age Figure 10 suggests the age distribution for internees in the JARP data is relatively similar to the age distribution for interned people in the WRA records. While traditional dierence in means (test statistic -8.08) and K-S tests (p-value 2.2 x 10−16) both suggest that some dierences exist between the age distributions in the two data sources, it is important to keep in mind that WRA records did not, as a rule, record births that occurred within camps13. at dierence may help explain the relative abundance of people with birth years between 1942 and 1950 in the JARP data.

Figure 10: Age Distribution for Interned Japanese-Americans in the JARP and WRA Records

0.03

0.02

Data

JARP

Density WRA

0.01

0.00

1860 1890 1920 1950 Birth Year

Gender e JARP data for people who were interned is 55.7% male and the WRA data is 54.5% male. A traditional two-sample t-test for the proportion of male internees in the JARP and WRA data suggests that the JARP is representative on this dimension (p = 0.18). is suggests that the JARP is representative of the WRA in terms of gender balance.

Educational Attainment Distributions of educational aainment are likewise similar for Issei respondents in the JARP and the WRA data. ese distributions appear in Figure 11. We focus on Issei respondents because both data sets record respondents’ terminal level of education. Since Issei are usually the oldest respondents, they are the least likely to have goen additional education between 1942 and 1968. Education levels for JARP respondents overall tend to be higher than for internees in the WRA, but this is less pronounced for Issei because their levels of education are more likely to be xed across these two periods.

13Over 6,000 births were recorded in the 10 major internment camps (Burton, 2000)

2 Figure 11: Educational Aainment for Interned Issei in the JARP and WRA Records

0.8

0.6

Data

JARP 0.4 WRA Percentage of Issei Percentage

0.2

0.0

None Less than High School Some College Graduate High School Graduate College Graduate Work

A.2 Who Are the Non-Interned Japanese-Americans in the Data? While Section A.1 provides evidence for similarity between interned respondents in the JARP and internees listed in the WRA records, the question of whether or not JARP respondents who were not interned are a representative sample of the broader non- interned Japanese-American population remains open. Here too, direct comparisons between respondents in the JARP and the broader population are even more dicult to make without extensive data on individual Japanese Americans living outside the Exclusion Zones in 1941. Still, we can address several potential concerns using the data collected for this study.

U.S. Arrival Dates One potential concern about the JARP data is that non-internees who were surveyed might be an unrepresentative population of non-interned Japanese Americans because they arrived in the United States between 1946 and 1962- 1968. In that scenario, a portion of the non-interned respondents to the JARP might be unrepresentative because they are immigrants who le Japan during a later period and possibly for dierent reasons. is concern is not borne out in our data. e JARP survey asked Issei respondents when they rst arrived in the United States. Just two respondents had arrival dates post-dating the beginning of WWII (one in 1954 and one in 1955, respectively). By denition, Nisei are the U.S.-born children of at least one Japanese-born parent and Sansei are U.S.-born children of Japanese parents who were born outside of Japan.

Summary Statistics for Non-Internees in the JARP 1,362 respondents in the JARP survey were not held in internment camps during WWII. 447 respondents (33%) in this group were 21 years old or younger when the JARP survey was administered, which means that they were born aer the end of the internment period and could not have been interned themselves.14 Of those who were old enough to have been interned (but were not), 341 (50%) lived outside of Arizona, California, Oregon and Washington and therefore would not have been subject to relocation or internment. While the JARP did not ask respondents why they were not interned if they reported living in the Exclusion Zone but did not report being interned, respondents who were college students in states outside the Exclusion Zones or respondents who registered for military service may have avoided internment. 153 Nisei respondents and 54 Sansei with addresses in the Exclusion Zone report that either they or their spouses had served in the U.S.

14Since this group consists of the Sansei and youngest Nisei, whose surveys were administered largely throughout 1967, we use a cuto of 1967 - 1946 = 21 as a cuto for being too young to have been interned.

3 Armed Forces. Section E.2 provides additional information about the broader Japanese-American population in the U.S. on the eve of WWII.

A.3 People of Japanese Descent Living in Hawaii Our analysis excludes the large number of people of Japanese descent living in Hawaii in 1941 on substantive grounds, which we further explain in this section.15 In the late 1930s and early 1940s, approximately 158,000 people of Japanese descent (citizens and non-citizens) lived in Hawaii, accounting for around 37 percent of the territory’s population. By contrast, there were around 130,000 people of Japanese descent living in the entire mainland U.S., much fewer in terms of the absolute number and also as a share of the population. Given the large shares of Japanese and Japanese-Americans in Hawaii, large-scale evacuation and internment would be dicult. Some individuals in the military and in the government nonetheless recommended removing all Issei and their citizen children to the mainland or taking them hostage (Kashima, 2003, p. 68); however, others with deeper knowledge of the situation in Hawaii—such as Delos Emmons, head of Western Defense Command during the war—warned that removing such a large population would prove logistically intractable and leave gaping needs in terms of much needed war-time labor (Kashima, 2003, p. 75). e laer view eventually won out. Following the aack by the Japanese on Pearl Harbor on December 7, 1941, the entirety of Hawaii was placed under martial law, with control of power transferred from the civilian territorial governor the military head of the Hawaii command. (is lasted almost three years, until October of 1944.) e introduction of martial law aected all residents of Hawaii, including citizens and non-citizens, Japanese-Americans and others. However, there were some detentions and evacuations. For example, several hundred Japanese or Japanese Americans on a special FBI “custodial detention list” were quickly taken into custody. is included “businesspeople, Japanese consular ocials, Japanese language school teachers and principals, Buddhist and Shinto priests, and ‘others of no particular aliation but who by reason of their extreme nationalist sentiments would be a danger to our security as well as others who have seen Japanese military service” (Kashima, 2003, p. 68). ere was also additional wartime detention and relocation of some 1,500 Kibei residents—that is, Japanese-Americans living in Hawaii who had been educated in Japan, spoke primarily Japanese, or had other close personal or nancial interests in Japan. e result was that by far smaller numbers and shares of Hawaii’s Japanese or Japanese-American population were interned than on the mainland. Kashima (2003, pp. 86–87) summarizes:

Under this selective policy, an additional 1,217 persons eventually were shipped to WRA relocation camps from November 23, 1942 to July 1945. e largest group, numbering 1,037, arrived between November 1942 and March 14, 1943. [T]he army put all these Hawaii residents in WRA camps; most of them went to Jerome, Arkansas, or Topaz, Utah, but some ended up at Minidoka, Idaho, and Tule Lake, California. [A]dding this count of 1,217 to the 875 predominately male Issei produces a total of 2,092 persons brought to the mainland. Along with the estimated 300 persons who remained in Hawaii, the total number of Hawaii residents of Japanese ancestry were detained in permanent imprisonment facilities comes to 2,392. Compared to the prisoner population of Nikkei on the mainland, this is a very small number. e contrast in treatment between these two groups is stark and revealing.

For our purposes, the number of people interned—around 2,300 in total—represents around 2 percent of the overall Hawaiian Japanese or Japanese American population. By comparison, around 120,000 Japanese Americans—or around 85 percent—of people of Japanese descent living in the mainland were interned. In sum, there was never wholesale evacuation and internment of people of Japanese descent, like there was on the west coast of the United States. For these reasons, we set Hawaii aside in our analyses.

15For more on the dierences in the internment of Hawaii-based people of Japanese descent and those living on the mainland, see Kashima (2003, ch. 4).

4 B From Assembly Centers to Internment Camps

Over 90,000 Japanese Americans in WRA custody were transferred from assembly centers to internment camps throughout the fall of 1942. Notably, not all were transferred from assembly centers. ose forced to report to the Owens Valley (10,000) and Parker Dam (12,000) reception centers were not transferred to internment camps because Owens Valley was expanded to become the Manzanar internment camp and Parker Dam became Poston. Over 17,000 internees were taken to internment camps directly from their homes, while 5,918 were born in internment camps, and over 4,500 were transferred from Immigration and Naturalization Service (INS) facilities, prisons, and other institutions.16 By July 1, 1942, the WRA had completed construction on just three of the ten planned Japanese Internment camps: Manzanar, Poston, and Tule Lake. Manzanar had reached its population capacity by summer 1942, but the other camps began receiving groups of internees virtually as soon as each was operational (WRA, 1942). e WRA’s objective was to “relocate the evacuated people as quickly as possible in order that their removal from private life and productive work would be brief” (WRA, 1943). Internees were transported to the nearest accessible camps by train as soon as they were open. e WRA also prioritized keeping families and communities together (WRA, 1943). To this end, the Army tried to relocate each assembly center’s whole population to a single nearby internment camp in one mass evacuation per assembly center. e WRA only deviated from this when an assembly center’s population was too large for any single internment camp to accommodate (see WRA (1943), p. 3). Since victims of internment were assigned to camps using a procedure orthogonal to their personal characteristics, we should expect to see relatively high degrees of balance along these characteristics across camps. We already show this to be the case using available pretreatment covariates in the JARP sample in Table 4, but we can take a look at a broader set of pre-treatment covariates using the WRA data. Table 5 leverages WRA records to show a high degree of balance across major camps in terms of age, gender, marital status, education levels, birth country, and agricultural occupations.

Table 5: Balance Statistics by Camp for Internees in the WRA Data

Camp Internees % Male % Married U.S. Born Age Degree Just HS Less than HS Agricultural Worker Gila River 13172 0.55 0.38 0.66 29.08 0.02 0.24 0.67 0.22 Granada 6919 0.53 0.41 0.65 29.53 0.02 0.22 0.68 0.18 Heart Mountain 10936 0.54 0.4 0.64 30.24 0.02 0.25 0.65 0.14 Jerome 8484 0.53 0.36 0.68 28.12 0.01 0.23 0.7 0.25 Manzanar 10160 0.57 0.38 0.65 29.16 0.02 0.24 0.68 0.11 Minidoka 9531 0.54 0.39 0.6 31.18 0.03 0.3 0.62 0.1 Poston 18089 0.54 0.36 0.68 28.45 0.02 0.22 0.7 0.21 Rohwer 8418 0.57 0.36 0.65 29.76 0.02 0.25 0.68 0.2 Topaz 8575 0.54 0.4 0.63 30.89 0.03 0.27 0.61 0.05 Tule Lake 15088 0.54 0.37 0.66 29.36 0.02 0.22 0.7 0.25

C Internment Status (Table)

C.1 Formal Tests of Coecient Equality C.2 Internment Length (Table and Robustness Checks) Among those granted indenite leave, 70% were aged between 15 and 35 years old (Yonemura, 2019). Respondents in this category (40-60 when the JARP study was conducted) had shorter internment lengths relative to those in adjacent age categories in

16National Japanese American Memorial Foundation. “Forced Removal and Incarceration.” https://www. njamemorial.org/internment-overview

5 Table 6: Internment Status and Political Engagement

Dependent variable: Political Interest Distrust Political Advice Leadership Approach OLS OLS OLS OLS Internment Status (Self) −.133∗∗∗ (.043) .043 (.036) −.019 (.027) .109∗ (.056) Internment Status (Family) −.181∗∗∗ (.046) .022 (.036) −.005 (.027) .190∗∗∗ (.057) Generations Issei, Nisei, Sansei Nisei, Sansei Nisei, Sansei Nisei, Sansei Generation Fixed Eects XXXX Pre-internment Locations XXXX Controls XXXX Observations 2,690 1,891 1,892 1,858 Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01

Table 7: Formal Tests of Coecient Equality (Direct Exposure = Family-Only Exposure)

Model Residual DF RSS df Sum of Sq. F-statistic p Political Interest 4061.00 1899.14 1.00 0.77 1.64 0.20 Political Distrust 3034.00 742.92 1.00 0.13 0.54 0.46 Political Advice 3035.00 417.91 1.00 0.05 0.40 0.53 Leadership Approach 2950.00 1714.86 1.00 1.78 3.06 0.08

Table 8: Internment Length and Political Engagement

Dependent variable: Political Interest Distrust Political Advice Leadership Approach OLS OLS OLS OLS (1) (2) (3) (4) Internment Length −.014 (.013) .042∗∗∗ (.011) −.034∗∗∗ (.008) .043∗∗ (.017) Generations Issei, Nisei, Sansei Nisei, Sansei Nisei, Sansei Nisei, Sansei Generation Fixed Eects XXXX Controls XXXX Observations 2,690 1,891 1,892 1,858 Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01

6 our sample. ough we control for age in our analyses, modeling age as a continuous variable does not account for these possible non-linearities. In Table 9, we show that our ndings still hold aer including an indicator for this particular subgroup.

Table 9: Internment Length (Yonemura Subgroup)

Dependent variable: Political Distrust Political Leadership Interest Advice Approach Internment Length −.041∗∗ .041∗∗∗ −.033∗∗∗ .052∗∗ (.014) (.012) (.008) (.018) Age-Based Subgroup .327∗∗∗ −.019 .011 .099 (.030) (.039) (.027) (.058) Generation Fixed Eects XXXX Controls XXXX Observations 2,690 1,891 1,892 1,858 Note: ∗p<0.05; ∗∗p<0.01; ∗∗∗p<0.001

Table 10: Internment Length (Final Internment Year ≥ 1945)

Dependent variable: Political Distrust Political Leadership Interest Advice Approach Internment Length −.009 .035∗∗ −.025∗∗ .028 (.017) (.013) (.009) (.020) Generation Fixed Eects XXXX Controls XXXX Observations 2,075 1,449 1,451 1,423 Note: Subset = Final Year ≥ 1945 ∗p<0.05; ∗∗p<0.01; ∗∗∗p<0.001

D Eects of Internment Experience (Table)

7 Table 11: Eects of Internment Experience

Dependent variable:

Interest Distrust Advice Leadership Interest Distrust Advice Leadership Interest Distrust Advice Leadership Interest Distrust Advice Leadership

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16)

Violence −.06 (.06) .10∗∗∗ (.02) −.02 (.04) .08 (.05) Demonstrations −.09 (.05).09∗∗∗ (.03) −.04 (.04) .04 (.05) Force .06 (.06) −.02 (.05) .07 (.04) .01 (.08) Militarism .12∗∗∗ (.04)−.06 (.05) .04 (.04) −.03 (.05) Interned −.01 (.06) .03 (.03) −.02 (.03) −.08∗ (.05) −.03 (.06) .02 (.04) −.03 (.04) −.10∗ (.05) −.001 (.06) .003 (.03) −.002 (.03) −.08 (.05) −.001 (.04) −.01 (.03) −.02 (.03) −.11 (.09) Gender (Male) .13∗∗∗ (.03) −.01 (.02) .08∗∗∗ (.02) −.13∗∗∗ (.02).13∗∗∗ (.03)−.01 (.02) .08∗∗∗ (.02) −.13∗∗∗ (.02).13∗∗∗ (.03)−.01 (.02) .08∗∗∗ (.02) −.13∗∗∗ (.02).13∗∗∗ (.03)−.01 (.02) .08∗∗∗ (.02) −.13∗∗∗ (.02) Age −.001 (.003)−.001 (.001)−.004∗∗ (.002).01∗∗∗ (.002)−.001 (.003)−.001 (.001)−.004∗∗ (.002).01∗∗∗ (.002)−.001 (.003)−.001 (.001)−.004∗∗ (.002).01∗∗∗ (.002)−.001 (.003)−.001 (.002)−.004∗∗∗ (.002).01∗∗∗ (.002) Violence x Interned −.01 (.07)−.08∗∗∗ (.03) −.004 (.04) −.01 (.06) Demonstrations x Interned .04 (.08) −.01 (.02) .02 (.05) .05 (.05) Force x Interned −.07 (.11) .04 (.05) −.09∗ (.05) .01 (.07) Militarism x Interned −.03 (.07) .04 (.02) −.01 (.05) .02 (.08)

Generations I, N, S N, S N, S N, S I, N, S N, S N, S N, S I, N, S N, S N, S N, S I, N, S N, S N, S N, S Generation Fixed Eects XXXXXXXXXXXXXXXX Pre-Internment Location Fixed Eects XXXXXXXXXXXXXXXX Observations 3,188 2,392 2,396 2,334 3,188 2,392 2,396 2,334 3,188 2,392 2,396 2,334 3,135 2,357 2,360 2,299 R2 .31 .01 .03 .03 .31 .01 .03 .03 .31 .01 .03 .03 .31 .01 .03 .03 8

Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01 Note: Standard errors clustered by internment camp to which respondents are assigned. E Balance Test Results

E.1 K-S Tests We conducted a series of Kolmogorov-Smirnov (KS) tests of the null hypothesis that age and occupation for internees imprisoned across dierent camps come from the same distribution. ese tests support the idea that internees are comparable across these dimensions. KS tests compare pairs of samples. ere are 45 possible pairs of the 10 major camps to which Japanese Americans were assigned during the internment period. For age, our KS test results reject the null hypothesis of a single parent distribution in two of 45 cases (internees in Topaz vs. Manzanar and Topaz vs. Jerome). is is with the dened Type I error rate of 0.05 for these tests. For employment sector, we treat the 3-digit designations for occupational sector as a continuous covariate and test the distributions of these sectors for Nisei respondents across camps. Here, we reject the null hypothesis of a single distribution at the 5% level in none of the 45 cases. Full results for these tests are presented in Tables 12 and 13. A series of t-tests for standardized dierences in proportions never reject the null hypothesis that gender balance is nearly identical across all 45 possible pairs of internment camps at the 5% level; results are reported in Table 14. All of these tests rely exclusively on respondents who were directly interned themselves.

9 Table 12: Kolmogorov-Smirnov Test Results for Table 13: Kolmogorov-Smirnov Test for Em- Age ployment Sector

Camp 1 Camp 2 p-value Camp 1 Camp 2 p-value

Rivers, AZ Poston, AZ 0.53 Rivers, AZ Poston, AZ 0.09 Amache, CO Poston, AZ 0.66 Amache, CO Poston, AZ 0.10 Denson, AR Poston, AZ 0.43 Denson, AR Poston, AZ 0.24 Manzanar, CA Poston, AZ 0.26 Manzanar, CA Poston, AZ 0.22 McGehee, AR Poston, AZ 0.66 McGehee, AR Poston, AZ 0.98 Heart Mountain, WY Poston, AZ 0.87 Heart Mountain, WY Poston, AZ 0.15 Hunt, ID Poston, AZ 0.63 Hunt, ID Poston, AZ 0.10 Newell, CA Poston, AZ 0.78 Newell, CA Poston, AZ 0.97 Topaz, UT Poston, AZ 0.08 Topaz, UT Poston, AZ 0.62 Amache, CO Rivers, AZ 0.52 Amache, CO Rivers, AZ 0.93 Denson, AR Rivers, AZ 0.77 Denson, AR Rivers, AZ 1.00 Manzanar, CA Rivers, AZ 1.00 Manzanar, CA Rivers, AZ 0.68 McGehee, AR Rivers, AZ 0.74 McGehee, AR Rivers, AZ 0.46 Heart Mountain, WY Rivers, AZ 0.64 Heart Mountain, WY Rivers, AZ 1.00 Hunt, ID Rivers, AZ 0.64 Hunt, ID Rivers, AZ 1.00 Newell, CA Rivers, AZ 0.87 Newell, CA Rivers, AZ 0.19 Topaz, UT Rivers, AZ 0.06 Topaz, UT Rivers, AZ 0.09 Denson, AR Amache, CO 0.14 Denson, AR Amache, CO 1.00 Manzanar, CA Amache, CO 0.25 Manzanar, CA Amache, CO 1.00 McGehee, AR Amache, CO 0.72 McGehee, AR Amache, CO 0.68 Heart Mountain, WY Amache, CO 1.00 Heart Mountain, WY Amache, CO 1.00 Hunt, ID Amache, CO 0.90 Hunt, ID Amache, CO 1.00 Newell, CA Amache, CO 0.53 Newell, CA Amache, CO 0.12 Topaz, UT Amache, CO 0.52 Topaz, UT Amache, CO 0.24 Manzanar, CA Denson, AR 0.81 Manzanar, CA Denson, AR 0.98 McGehee, AR Denson, AR 0.44 McGehee, AR Denson, AR 0.73 Heart Mountain, WY Denson, AR 0.17 Heart Mountain, WY Denson, AR 1.00 Hunt, ID Denson, AR 0.16 Hunt, ID Denson, AR 1.00 Newell, CA Denson, AR 0.46 Newell, CA Denson, AR 0.20 Topaz, UT Denson, AR 0.04 Topaz, UT Denson, AR 0.52 McGehee, AR Manzanar, CA 0.61 McGehee, AR Manzanar, CA 0.94 Heart Mountain, WY Manzanar, CA 0.37 Heart Mountain, WY Manzanar, CA 0.97 Hunt, ID Manzanar, CA 0.31 Hunt, ID Manzanar, CA 0.96 Newell, CA Manzanar, CA 0.44 Newell, CA Manzanar, CA 0.25 Topaz, UT Manzanar, CA 0.05 Topaz, UT Manzanar, CA 0.67 Heart Mountain, WY McGehee, AR 0.82 Heart Mountain, WY McGehee, AR 0.53 Hunt, ID McGehee, AR 0.68 Hunt, ID McGehee, AR 0.66 Newell, CA McGehee, AR 0.49 Newell, CA McGehee, AR 0.93 Topaz, UT McGehee, AR 0.22 Topaz, UT McGehee, AR 1.00 Hunt, ID Heart Mountain, WY 1.00 Hunt, ID Heart Mountain, WY 1 Newell, CA Heart Mountain, WY 0.56 Newell, CA Heart Mountain, WY 0.15 Topaz, UT Heart Mountain, WY 0.15 Topaz, UT Heart Mountain, WY 0.11 Newell, CA Hunt, ID 0.92 Newell, CA Hunt, ID 0.12 Topaz, UT Hunt, ID 0.14 Topaz, UT Hunt, ID 0.10 Topaz, UT Newell, CA 0.06 Topaz, UT Newell, CA 0.41

10 Table 14: T-Tests for Dierences in Gender Proportion by Camp

Camp 1 Camp 2 Dierence in Means Standard Error T p-value Lower Bound Upper Bound

Rivers, AZ Poston, AZ 0.03 7.11 0.004 1.00 -13.99 14.00 Amache, CO Poston, AZ 0.01 7.10 0.001 1.00 -13.97 13.97 Denson, AR Poston, AZ -0.07 5.24 -0.01 0.99 -10.37 10.35 Manzanar, CA Poston, AZ -0.06 6.83 -0.01 0.99 -13.45 13.43 McGehee, AR Poston, AZ -0.01 6.18 -0.001 1.00 -12.19 12.18 Heart Mountain, WY Poston, AZ 0.03 7.35 0.003 1.00 -14.45 14.46 Hunt, ID Poston, AZ -0.01 7.58 -0.001 1.00 -14.91 14.90 Newell, CA Poston, AZ -0.02 6.95 -0.003 1.00 -13.68 13.67 Topaz, UT Poston, AZ 0.01 6.60 0.002 1.00 -12.99 12.99 Amache, CO Rivers, AZ -0.02 6.49 -0.004 1.00 -12.76 12.76 Denson, AR Rivers, AZ -0.10 4.99 -0.02 0.98 -9.88 9.84 Manzanar, CA Rivers, AZ -0.09 6.27 -0.01 0.99 -12.36 12.33 McGehee, AR Rivers, AZ -0.04 5.77 -0.01 1.00 -11.38 11.37 Heart Mountain, WY Rivers, AZ -0.004 6.67 -0.001 1.00 -13.13 13.13 Hunt, ID Rivers, AZ -0.04 6.84 -0.01 1.00 -13.47 13.46 Newell, CA Rivers, AZ -0.05 6.37 -0.01 0.99 -12.55 12.53 Topaz, UT Rivers, AZ -0.02 6.10 -0.003 1.00 -12.01 12.00 Denson, AR Amache, CO -0.08 4.98 -0.02 0.99 -9.86 9.83 Manzanar, CA Amache, CO -0.07 6.26 -0.01 0.99 -12.33 12.31 McGehee, AR Amache, CO -0.01 5.76 -0.002 1.00 -11.35 11.35 Heart Mountain, WY Amache, CO 0.02 6.66 0.003 1.00 -13.11 13.11 Hunt, ID Amache, CO -0.01 6.83 -0.002 1.00 -13.44 13.44 Newell, CA Amache, CO -0.03 6.36 -0.004 1.00 -12.52 12.51 Topaz, UT Amache, CO 0.01 6.09 0.001 1.00 -11.99 11.99 Manzanar, CA Denson, AR 0.01 4.83 0.002 1.00 -9.55 9.55 McGehee, AR Denson, AR 0.06 4.62 0.01 0.99 -9.12 9.14 Heart Mountain, WY Denson, AR 0.10 5.07 0.02 0.99 -10.00 10.04 Hunt, ID Denson, AR 0.06 5.13 0.01 0.99 -10.14 10.16 Newell, CA Denson, AR 0.05 4.91 0.01 0.99 -9.70 9.72 Topaz, UT Denson, AR 0.08 4.80 0.02 0.99 -9.48 9.51 McGehee, AR Manzanar, CA 0.06 5.59 0.01 0.99 -11.00 11.02 Heart Mountain, WY Manzanar, CA 0.09 6.44 0.01 0.99 -12.66 12.68 Hunt, ID Manzanar, CA 0.05 6.59 0.01 0.99 -12.95 12.97 Newell, CA Manzanar, CA 0.04 6.14 0.01 0.99 -12.08 12.09 Topaz, UT Manzanar, CA 0.07 5.91 0.01 0.99 -11.62 11.65 Heart Mountain, WY McGehee, AR 0.03 5.89 0.01 1.00 -11.61 11.62 Hunt, ID McGehee, AR -0.002 6.01 -0.0004 1.00 -11.84 11.84 Newell, CA McGehee, AR -0.02 5.67 -0.003 1.00 -11.18 11.18 Topaz, UT McGehee, AR 0.02 5.49 0.004 1.00 -10.81 10.82 Hunt, ID Heart Mountain, WY -0.03 7.05 -0.005 1.00 -13.88 13.87 Newell, CA Heart Mountain, WY -0.05 6.54 -0.01 0.99 -12.88 12.87 Topaz, UT Heart Mountain, WY -0.01 6.24 -0.002 1.00 -12.30 12.29 Newell, CA Hunt, ID -0.01 6.70 -0.002 1.00 -13.18 13.18 Topaz, UT Hunt, ID 0.02 6.38 0.003 1.00 -12.56 12.57 Topaz, UT Newell, CA 0.04 5.99 0.01 1.00 -11.80 11.81

E.2 Census Analysis ough we control for gender, age, and pre-internment locations, there is the possibility that Japanese Americans who were interned still dier from Japanese Americans who were not along some important covariate. Because social scientists typically construe an individual’s level of political engagement as a function of socioeconomic status (Verba, 1995), we might be particularly worried that internees and non-internees dier along other socioeconomic covariates such as education, marital status, or specic occupation. We use data from the 1940 U.S. Census to demonstrate that this is unlikely to be the case; Japanese Americans living in-

11 and outside of the Exclusion Zone are comparable along a variety of important socioeconomic dimensions.17 Table 15 displays the results of a formal test of dierences between those residing in- and outside of the Exclusion Zone. e lowest p-value corresponding to any of these tests is 0.33, which suggests that Japanese Americans living in- and outside of the Exclusion Zone are not signicantly dierent on the basis of these observed covariates at the 95% level.

Table 15: p Values from Two-Sided Dierence-in-Means Tests on Exclusion Zone Boundary in 1940

Variable p Value Prop. Male 0.40 Prop. Married 0.33 Prop. Under 20 0.72 Prop. Completed HS 0.81 Median Yrs. Ed. 0.63 Prop. Employed 0.61 Prop. Professional 0.42 Prop. Farmers 0.79

F Assignment to Places with Particular Political or Demographic Characteristics

One alternative pathway through which internment may have aected political outcomes for internees might have involved the political or demographic characteristics of the jurisdictions that housed internment camps. In a period when wartime uncertainty and racial anti-Japanese sentiment were at an all-time high in the mass public, skeptical readers might worry that Japanese-Americans interned in particularly white areas or areas that showed broad support for Franklin Roosevelt might have experienced more hostility. In short, the climate outside of the camps might have conveyed more of the eects we report than the climate within the camps themselves. Below, we provide evidence that this was unlikely to have been the case. First, qualitative accounts suggest that Japanese- Americans interned throughout the United States had extremely limited contact with the outside world. Internees would have lile information about the surrounding people living in areas with even extremely distinct political or demographic characteristics. To rule out this possibility, we included indicators for Franklin D. Roosevelt’s 1940 share of the two party vote and for the percentage white in the county of internment hosting each internment camp. ese covariates themselves are rarely signicant. e percentage white in each county of internment is only signicantly associated with level of political distrust when we consider one type of camp experience (experiencing violence). While presidential vote share in 1940 seems to consistently and signicantly inuence political communication and views on leadership approach, these values are substantively small. More importantly, including these covariates does not change our substantive conclusions about the eects of experiencing violence or oppositional demonstrations while interned.

17ese analyses rely on the 1940 Census summary report entitled “Characteristics of the Nonwhite Population by Race.”18 is summary report provides distributions of age, gender, marital status, education, employment status, and employment type for Japanese Americans living in California, Oregon, Washington State (inside the Exclusion Zone), Colorado, New York, and Utah (outside the Exclusion Zone).

12 Table 16: Eects of Internment Experience, Controlling for Surrounding Camp Environment

Dependent variable:

Interest Distrust Advice Leadership Interest Distrust Advice Leadership Interest Distrust Advice Leadership Interest Distrust Advice Leadership

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16)

Violence −.06 (.06) .08∗∗∗ (.03) −.02 (.04) .05 (.03) Demonstrations −.07 (.06) .08∗∗∗ (.03) −.04 (.04) .02 (.04) Force .16∗ (.09) −.09∗∗ (.04) .07 (.04) −.11∗∗ (.05) Militarism .12∗∗ (.05) −.07 (.04) .04 (.03) −.03 (.03) Interned −.01 (.06) .03 (.03) −.02 (.03) −.08∗ (.05) −.03 (.05) .01 (.04) −.03 (.04) −.10∗∗ (.05) .002 (.06) .0002 (.03) −.002 (.03) −.08∗ (.05) −.004 (.04) −.01 (.03) −.02 (.03) −.11 (.09) Pct. White 1940 −.001∗∗∗ (.001) .001 (.001) −.0004 (.0003) .0003 (.001) −.001 (.001).0001 (.001) 0.0000 (.001) −.0004 (.001)−.004∗∗∗ (.001).002∗∗∗ (.001) −.0005 (.001) .002∗∗ (.001)−.002∗∗∗ (.0002) .001 (.001) −.001∗∗∗ (.0001) .0001 (.001) FDR 1940 Vote Share −.08∗ (.04) .11 (.11) .03 (.02) .22∗∗∗ (.07) −.10∗ (.06) .07 (.06) .04 (.04) .21∗∗∗ (.05) −.34∗∗∗ (.07) .25∗∗ (.10) .01 (.07) .46∗∗∗ (.11) −.17∗∗∗ (.03) .15 (.10) −.01 (.02) .25∗∗∗ (.04) Gender (Male) .14∗∗∗ (.03) −.01 (.02) .08∗∗∗ (.02) −.14∗∗∗ (.02).13∗∗∗ (.03) −.01 (.02) .07∗∗∗ (.02) −.14∗∗∗ (.02) .14∗∗∗ (.03) −.02 (.02) .08∗∗∗ (.02) −.14∗∗∗ (.02) .14∗∗∗ (.03) −.01 (.02) .08∗∗∗ (.02) −.14∗∗∗ (.02) Age −.001 (.003) −.0005 (.002)−.004∗∗ (.002).01∗∗∗ (.002)−.001 (.002)−.001 (.001)−.004∗∗ (.002).01∗∗∗ (.002) −.001 (.003) −.0004 (.002)−.004∗∗ (.002).01∗∗∗ (.002) −.001 (.003) −.001 (.002) −.004∗∗ (.002) .01∗∗∗ (.002) Violence x Interned −.01 (.07) −.08∗∗∗ (.03) −.004 (.04) −.01 (.06) Demonstrations x Interned .04 (.08) −.01 (.02) .02 (.05) .05 (.05) Force x Interned −.06 (.11) .04 (.04) −.09∗ (.05) −.004 (.07) Militarism x Interned −.02 (.07) .03 (.02) −.01 (.05) .01 (.08)

Generations I, N, S N, S N, S N, S I, N, S N, S N, S N, S I, N, S N, S N, S N, S I, N, S N, S N, S N, S Generation FE XXXXXXXXXXXXXXXX

13 Location FE XXXXXXXXXXXXXXXX Observations 3,188 2,392 2,396 2,334 3,188 2,392 2,396 2,334 3,188 2,392 2,396 2,334 3,135 2,357 2,360 2,299 R2 .31 .01 .03 .03 .31 .01 .03 .03 .32 .01 .03 .03 .32 .01 .03 .03

Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01 Note: Standard errors clustered by internment camp to which respondents are assigned. Location FE refer to pre-internment location xed eects. Figure 12: Eects of Internment Using WRA Location Data: Demonstrations and Violence

Effect of Witnessing Demonstrations While Interned Effect of Witnessing Violence While Interned

● Political Interest Political Interest ●

● Political Distrust Political Distrust ●

Group Group

Direct Exposure ● Direct Exposure Family−Only Exposure ● Family−Only Exposure Outcome Outcome

● Political Advice Political Advice ●

● Leadership Approach Leadership Approach ●

−0.1 0.0 0.1 −0.1 0.0 0.1 0.2 0.3 Coefficient Estimate Coefficient Estimate (a) Demonstrations (b) Violence

G Recording of Pre-Internment Location

One important limitation for the JARP data is the fact that pre-internment location outside of California is recorded at the state level.19 While it is plausible to assume that people living in a single city or county area would have had similar probabilities of camp assignment, it is less clear that this assumption might hold for everyone living in a given state. We used individual records in the WRA data, where specic pre-internment locations are available for each person, to simulate pre-internment locations for respondents in the JARP. We used the WRA data to calculate the empirical probabilities of living in specic, sub-state geographies conditional on living in a given state20. We produced 10,000 sets of simulated pre-internment locations for JARP respondents and re-estimated the eects of internment each time. Figures 12 through 13 display the results of these simulations. e means of each ploed distribution can be interpreted as the average eect of witnessing violence, force, strikes, or heavily militarized camp conditions across all of our simulations. We compare the coecients and standard errors21. e simulation produces very similar point estimates for the eects of various camp characteristics even under dierent assumed pre-internment locations, which provides support for plausible exogeneity of camp assignment. Another way to check the robustness of our pre-treatment location control is to use indicators for birthplace instead of indicators for state or subregion of residence in 1941. JARP records birthplaces for Nisei and Sansei respondents at the SMSA level, so people from Los Angeles are distinguished from people born in Sacramento, Bakerseld, and other cities. While conditioning on birthplace

19For California, JARP provides separate designations for people who lived in the state’s largest Metropolitan Sta- tistical Areas (“MSA”) from people who lived in “rural clusters” throughout the state. ese designations provide lile additional information relative to the statewide code because they group jurisdictions across geographic areas. San Francisco and Los Angeles, for instance, are coded using the same value because both are large MSAs 20For example, the WRA data shows 6 Japanese-American internees with pre-internment addresses in Colorado: 4 in Rocky Falls and 1 each in Greely and Fort Upton. We took a list of unique family ID numbers for JARP respondents living in Colorado. All members of each family ID were assigned to Rocky Falls with a 67% probability and to Fort Upton and Greeley with 16% probabilities, respectively. If one family ID had some members who lived in Colorado before internment and other members who lived in California before internment, the California members would be assigned to specic locations in California using the same process. 21Standard errors are the standard deviations of the distributions of simulated coecients.

14 Figure 13: Eects of Internment Using WRA Location Data: Force and Militarization

Effect of Witnessing Force While Interned Effect of Militarized Camp Environment

● ● Political Interest Political Interest ● ●

● ● Political Distrust Political Distrust ● ●

Group Group

● Direct Exposure ● Direct Exposure ● Family−Only Exposure ● Family−Only Exposure Outcome Outcome

● ● Political Advice Political Advice ● ●

● ● Leadership Approach Leadership Approach ● ●

−0.1 0.0 0.1 −0.2 −0.1 0.0 0.1 Coefficient Estimate Coefficient Estimate (a) Force (b) Militarization

requires us to make the assumption that people largely lived in the same location they were born in on the eve of internment, this assumption might be plausible in the sense that mobility was lower before and up to the 1940s than it is today. Furthermore, a considerable portion of people in the data were farmers, which connected them to the land they lived on and likely meant lower mobility relative to people who worked in dierent occupations. Figure 14 summarizes our main results using this approach. ese are very consistent with the results we present in the main dra. We can further focus on the 671 JARP respondents born in Los Angeles. is is the largest group from a single birthplace in our data. ese results are also generally consistent with our main results, if noisier as a result of the lower sample size.

15 Figure 14: Eects of Internment Controlling for Birthplace as Pre-Internment Location

Effect of Witnessing Demonstrations While Interned Effect of Witnessing Violence While Interned

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.2 −0.1 0.0 0.1 −0.2 −0.1 0.0 0.1 0.2 Coefficient Estimate Coefficient Estimate (a) Demonstrations (b) Violence

Effect of Witnessing Use of Military Force While Interned Effect of Being Interned in Highly Militarized Camp

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.1 0.0 0.1 0.2 −0.1 0.0 0.1 Coefficient Estimate Coefficient Estimate (c) Force (d) Militarism

16 Figure 15: Eects of Internment on Respondents Born in Los Angeles

Effect of Witnessing Demonstrations While Interned Effect of Witnessing Violence While Interned

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.50 −0.25 0.00 0.25 0.50 −0.2 0.0 0.2 0.4 Coefficient Estimate Coefficient Estimate (a) Demonstrations (b) Violence

Effect of Witnessing Use of Military Force While Interned Effect of Being Interned in Highly Militarized Camp

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.2 0.0 0.2 0.4 0.6 −0.4 0.0 0.4 Coefficient Estimate Coefficient Estimate (c) Force (d) Militarism

17 Table 17: Internment Status, Income, and Military Service

Dependent variable: Military Service Post-Treatment Income OLS OLS Direct Exposure to Internment −.057 (.037) .306∗∗ (.124) Family-Only Exposure to Internment −.023 (.039) −.165 (.134) Observations 2,626 3,879 ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01

H Additional Robustness Checks

Military Service Nisei and Sansei respondents were asked whether they or their spouses had ever served in the U.S. armed forces. ere is some missingness in this variable: 179 of 2,304 Nisei have no recorded response for military service, as do 347 of 802 Sansei. Our results do not suggest that specic features of internment camps produced meaningful dierences in Japanese-American military service. is provides additional evidence for the fact that, prior to internment, Japanese Americans who were interned were similar to Japanese Americans who were not. One potential threat to inference might reside in the possibility that a latent form of patriotism may have both led some Japanese Americans to voluntarily relocate away from the coasts (thereby avoiding internment) and to serve in the military later. is does not appear to be the case in our data.

Income Another possible threat to inference is the possibility that Japanese-Americans who were not interned had higher (or lower) earning potential than Japanese Americans who were. If so, that potential is likely to have translated into higher family income aer internment. In Table 17, we show that there are dierences in income among those who personally and indirectly experienced internment, and these dierences are statistically signicant at the .05 level. However, these estimates run in the opposite direction, and thus, cannot explain the directionally consistent estimates that we observe for both groups in our models.

Returning Home Our data makes it dicult to identify how many people returned home aer internment. e WRA data does not provide post-camp locations for internees. While the JARP does contain specic information on the places Japanese- American internees returned to aer WWII, their pre-camp locations are recorded with less precision. Accordingly, all we can say is whether or not Issei (the only generation for whom post-camp location is recorded) returned home to the same state and sub-state area aer internment. If the 849 Issei for whom post-camp location is recorded, 425, or just over 50%, returned to the same area within their state.

Selection into Internment Experience e U.S. Army’s records detailing the procedure by which Japanese- Americans were assigned and transferred to internment camps suggests that internees were not assigned to camp destinations based on their social, economic, or political characteristics. Still, one potential source of concern might be how responses to internment and interrogation among internees ultimately aected their experience once they were assigned to internment camps. For instance, readers might worry that internees who resisted internment might have been assigned to more punitive or more militarized facilities. One prominent example of this includes the WRA’s loyalty questionnaire - launched in the winter of 1943. Men over the age of 17 who were still incarcerated in WRA camps were asked to ll out a questionnaire that asked them whether they would comply with selective service if they were draed into the U.S. military and whether they could pledge their unqualied allegiance to the United States. Approximately 12,000 of 78,000 respondents to this survey answered “no” to both questions, and were sequestered at the Tule Lake camp for “disloyalty” as a result. To address possible selection issues like this, we replicated our analysis with a restriction just

18 Figure 16: Eects of Internment for Internees Younger than 17 in 1945

Effect of Witnessing Demonstrations While Interned Effect of Witnessing Violence While Interned

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.2 −0.1 0.0 0.1 0.2 −0.2 −0.1 0.0 0.1 0.2 Coefficient Estimate Coefficient Estimate (a) Demonstrations (b) Violence

Effect of Witnessing Use of Military Force While Interned Effect of Being Interned in Highly Militarized Camp

Political Political Interest Interest

Political Political Distrust Distrust

Group Group

Direct Exposure Direct Exposure Family−Only Exposure Family−Only Exposure Outcome Outcome

Political Political Advice Advice

Leadership Leadership Approach Approach

−0.1 0.0 0.1 0.2 −0.2 0.0 0.2 Coefficient Estimate Coefficient Estimate (c) Force (d) Militarism

to respondents under the age of 17. ese results are statistically and substantively consistent with the internment experience eects we report in the main body of this paper.

Age as a Moderator of Internment Experience e previous section demonstrates that people who were under 17, and therefore could not have entered the “’no-no” group that resisted the government by refusing to pledge their loyalty on the questionnaire, found internment as demobilizing as our larger sample. By subseing our sample to just individuals who were under 17, we implicitly interact age with our treatment eect (the slopes on coecients for various features of internment can dier for this group relative to the older people in our sample). Examining whether the eects of internment are dierent for people interned at dierent ages makes sense, and we expand on this idea by explicitly interacting respondent age with various features of internment. We include age as both the full range of respondent ages and as a binary indicator for whether or not respondents were

19 minors when they were interned. For this analysis, we focus on people who experienced internment directly. It is more dicult to understand how age interacts with internment for people who only experienced internment via communication with family members because we ultimately cannot know how old they were when they learned about their family members’ experiences even if we know how old they were when internment actually took place. Tables 18-19 and Figures 17-20 summarize these interaction eects. Given that evidence of conditional eects may be a result of extrapolation and model dependence, especially with a continuous variable like age, we use the binning estimator described in Hainmueller, Mummolo and Xu (2019). e estimator discretizes the moderator variable and computes marginal eects within each bin as a way of reducing bias due to severe extrapolation or interpolation. As shown in Figures 17-18, none of the pairwise comparisons of marginal eects across bins are statistically signicant at the .05 level. erefore, consistent with the results in the previous section, age does not seem to signicantly moderate the eects of internment for these aitudinal outcomes. Part of the reason for this may be that we control for cohort (or survey wave). is is important because slightly dierent questions were asked of Issei, Nisei, and Sansei, but it may compress the possible dierences that age can make within cohort groups if internment was an experience shared culturally within cohorts more than age bins.

Table 18: Internment Status (Conditional Eects by Age)

Dependent variable: Political Distrust Political Leadership Interest Advice Approach OLS OLS OLS OLS (1) (2) (3) (4) Being a Minor x Direct Exposure .108∗ −.015 −.019 −.011 (.066) (.059) (.044) (.092) Generation Fixed Eects XXXX Pre-Internment Location Fixed Eects XXXX Controls XXXX Observations 4,101 3,068 3,069 2,982 R2 .316 .011 .031 .039 Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01

20 Table 19: Internment Length (Conditional Eects by Age)

Dependent variable: Political Distrust Political Leadership Interest Advice Approach OLS OLS OLS OLS (1) (2) (3) (4) Being a Minor x Internment Length .014 −.017 .004 .034 (.028) (.023) (.017) (.035) Generation Fixed Eects XXXX Controls XXXX Observations 2,690 1,891 1,892 1,858 R2 .346 .012 .030 .030 Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01

Figure 17: Interaction Eects between Continuous Age and Direct Exposure to Internment

Political Interest Political Distrust 0.2 L M H L M H 0.1 0.1 ●

● ● 0.0 ● 0.0

● −0.1 ● −0.1 −0.2 −0.2 −0.3 25 50 75 20 40 60 Political Advice Leadership Style 0.1 L M H 0.2 L M H

● ● 0.0 ● ● 0.0 ● ●

−0.1 −0.2

−0.2 −0.4 20 40 60 20 40 60

21 Figure 18: Interaction Eects between Continuous Age and Internment Length

Political Interest Political Distrust

0.1 0.1 LMH LMH● ● ● 0.0 ● 0.0 ●

−0.1 ● −0.1

−0.2 20 40 60 80 20 30 40 50 60 70 Political Advice Leadership Style 0.2 LMH 0.00 LMH ● ● 0.1 ● ● −0.05 ● ● 0.0 −0.10

−0.15 −0.1 20 30 40 50 60 70 20 30 40 50 60 70

22 Figure 19: Interaction Eects between Continuous Age and Internment

Violence x Age Demonstrations x Age Violence x Age Demonstrations x Age

0.3 0.3

0.0 0.2 0.0 0.2

0.1 −0.1 0.1

−0.1 0.0 Political Distrust Political Distrust Political Interest in Politics −0.2 Interest in Politics 0.0 −0.1

−0.2 −0.3 20 40 60 80 20 40 60 80 20 30 40 50 60 70 20 30 40 50 60 70 Age Age Age Age CI(Max − Min): [−0.334, 0.127] CI(Max − Min): [−0.235, 0.187] CI(Max − Min): [−0.085, 0.467] CI(Max − Min): [−0.184, 0.361] Force x Age Militarism x Age Force x Age Militarism x Age 0.2 0.4 0.2 0.2

0.1 0.1 0.2 0.0 0.0 0.0

−0.1 −0.2 Political Distrust Political Distrust Political

Interest in Politics Interest in Politics 0.0

−0.1 −0.2

−0.4 20 40 60 80 20 40 60 80 20 30 40 50 60 70 20 30 40 50 60 70 Age Age Age Age CI(Max − Min): [−0.162, 0.319] CI(Max − Min): [−0.032, 0.511] CI(Max − Min): [−0.467, 0.149] CI(Max − Min): [−0.591, 0.078] (a) Interest in Politics (b) Political Distrust

Violence x Age Demonstrations x Age Violence x Age Demonstrations x Age

0.10 0.2

0.2 0.05 0.0

0.0 0.00

0.0 −0.1

Political Advice Political −0.05 Advice Political

Leadership Approach Leadership Approach −0.2 −0.10

−0.2 20 30 40 50 60 70 20 30 40 50 60 70 20 30 40 50 60 70 20 30 40 50 60 70 Age Age Age Age CI(Max − Min): [−0.43, 0.42] CI(Max − Min): [−0.617, 0.192] CI(Max − Min): [−0.173, 0.216] CI(Max − Min): [−0.251, 0.123] Force x Age Militarism x Age Force x Age Militarism x Age 0.15 0.2

0.10 0.2 0.1 0.25 0.05 0.0 0.0 0.00

0.00 −0.1

Political Advice Political −0.05 Advice Political

Leadership Approach Leadership Approach −0.2 −0.10 −0.2

−0.25 20 30 40 50 60 70 20 30 40 50 60 70 20 30 40 50 60 70 20 30 40 50 60 70 Age Age Age Age CI(Max − Min): [−0.296, 0.646] CI(Max − Min): [−0.49, 0.537] CI(Max − Min): [−0.169, 0.259] CI(Max − Min): [−0.419, 0.057] (c) Leadership Approach (d) Political Advice

23 Figure 20: Interaction Eects between Being a Minor and Internment

Violence x Minor Demonstrations x Minor Violence x Minor Demonstrations x Minor 0.05 0.05 0.12 0.15

0.00 0.08 0.00

0.10 0.04 −0.05 −0.05 0.00 −0.10 0.05 Political Distrust Political Distrust Political Interest in Politics Interest in Politics

−0.10 −0.04 −0.15 0.00 0 1 0 1 0 1 0 1 Minor Minor Minor Minor CI(Max − Min): [−0.074, 0.155] CI(Max − Min): [−0.098, 0.118] CI(Max − Min): [−0.139, 0.065] CI(Max − Min): [−0.11, 0.085] Force x Minor Militarism x Minor Force x Minor Militarism x Minor 0.10 0.2 0.10 0.05 0.05

0.05 0.00 0.1 0.00

−0.05 0.00 −0.05 0.0 Political Distrust Political Distrust Political Interest in Politics Interest in Politics −0.10 −0.10 −0.05

−0.1 −0.15 0 1 0 1 0 1 0 1 Minor Minor Minor Minor CI(Max − Min): [−0.158, 0.084] CI(Max − Min): [−0.242, 0.038] CI(Max − Min): [−0.049, 0.166] CI(Max − Min): [−0.06, 0.179] (a) Interest in Politics (b) Political Distrust

Violence x Minor Demonstrations x Minor Violence x Minor Demonstrations x Minor 0.20 0.05 0.20 0.15 0.15 0.00 0.00 0.10 0.10

0.05 0.05

Political Advice Political Advice Political −0.05 −0.05

Leadership Approach Leadership Approach 0.00 0.00

−0.05 −0.05 0 1 0 1 0 1 0 1 Minor Minor Minor Minor CI(Max − Min): [−0.191, 0.127] CI(Max − Min): [−0.105, 0.187] CI(Max − Min): [−0.045, 0.103] CI(Max − Min): [−0.042, 0.094] Force x Minor Militarism x Minor Force x Minor Militarism x Minor

0.10

0.1 0.05 0.1

0.05 0.00 0.0

0.0 0.00

Political Advice Political −0.05 Advice Political −0.1 Leadership Approach Leadership Approach

−0.1 −0.05 −0.10 0 1 0 1 0 1 0 1 Minor Minor Minor Minor CI(Max − Min): [−0.194, 0.13] CI(Max − Min): [−0.141, 0.233] CI(Max − Min): [−0.133, 0.02] CI(Max − Min): [−0.118, 0.056] (c) Leadership Approach (d) Political Advice

24 I Voting and Partisanship

We do not address voting and partisanship explicitly in the manuscript for several important reasons. First, only Issei were asked explicitly about whether or not they turned out to vote in elections. Nisei and Sansei were asked generally about which political party they support, but turnout cannot be inferred from the question text or responses. Of 1,047 Issei in the sample, 606 were not asked about voting behavior because they were noncitizens or ineligible. Of the remaining 441, 411 claimed to have voted in 1956, 1960, or 1964, making turnout in this group approximately 93%. ere is therefore extremely lile variation in turnout among Issei eligible voters regardless of camp assignment. is leaves open the question of whether or not camp assignment aects voting via the willingness to apply for naturalization in the postwar period. If we regress citizenship on an indicator for having personally been interned at all (controlling for age, gender and pre-internment location), we yield a point estimate of -0.09 with a p-value of 0.13. is suggests that people who were interned were less likely to seek citizenship in the postwar period than people who were not interned, but our estimates are not statistically dierent from zero at conventional signicance level. Conditional on being interned, we see no evidence that camp characteristics aect Issei’s willingness to obtain citizenship post internment. Issei who did naturalize before 1941 are excluded from this sample. ese results are summarized in Figure 21.

Figure 21: Null Eects of Internment Experience on Postwar Citizenship

Effects of Internment Camp Experience on Citizenship

Militarism

Force

Camp Characteristic Demonstrations

Violence

0.0 0.1 Likelihood of Obtaining Citizenship After 1941

Similarly, we do not discuss partisanship as an outcome. e reason for this is that our theory anticipates demobilization and our empirical evidence supports this claim. e implications of demobilization are retreat from political life, not a swing from one political aliation to another. In addition, even if internees sought to apply electoral punishments to either major party as a consequence for internment, it is not clear which would suer the consequences because they were interned by a Democratic administration - but at the urging of entrenched Republican political elites in California. alitative accounts of internment do not suggests coalescence around either political party, which is why we would expect to see null results for the eects of particular type of internment experience on vote choice. is is exactly what we observe; results are presented in Figure 22.

25 Figure 22: Null Eects of Internment Experience on Party Aliation

Effects of Internment Camp Experience on Partisanship

Militarism

Force

Group

Direct Exposure Family−Only Exposure

Camp Characteristic Demonstrations

Violence

−0.3 −0.2 −0.1 0.0 0.1 More Likely to Support Democratic Party (−1) or Republican Party (1)

J Additional Eects on Assimilation

One measure of assimilation recorded in the JARP asked Issei respondents how Japanese or how American they felt themselves to be. Respondents could indicate whether they felt 100%, 80%, 65% Japanese (or American) or about 50-50. Responses to this question provide some additional evidence for the idea that internment fragmented and demobilized Japanese Americans. Figure 23 shows considerable variation in where respondents positioned themselves based on where they were interned. While each camp’s distribution tends to skew Americanized, the modal respondent at Manzanar, for instance, only believes herself to be 50% American. Figure 24 shows the results of a regression of this continuum variable (where 1 indicates 100% Japanese and 7 indicates 100% Americanized and intermediate values take on intermediate integers) on specic features of internment. While these results do not reach conventional levels of signicance at 5%, they generally indicate that experiencing force, violence, and living in militarized space contributed to feeling less Americanized at the time of JARP survey. Our analyses using internment length corroborate these ndings. As shown in Table 20, for each year spent in an internment camp, perceptions of Americanism decline by 8pp (± 5pp). To place these numbers into context, those interned for 4 years are 24pp less likely to see themselves as American relative to those who were interned for under a a year; a 12% movement across the scale. Focusing on internment status, those who were interned score 3pp higher on perceptions of feeling American than those who were not interned. However, this estimate does not approach conventional levels of statistical signicance, and is imprecisely estimated (SE = 8.61). Taken together, these ndings provide some mixed evidence that the internment experience reduced perceptions of being American.

26 Figure 23: Position on the Japanese-American Continuum by Camp

Amache Gila River Heart Mountain Jerome

Manzanar Minidoka Poston Rohwer

Frequency 10

Topaz Tule Lake

80% J 65% J 65% A 80% A 80% J 65% J 65% A 80% A 100% J 100% A 100% J 100% A 30 50%−50% 50%−50%

80% J 65% J 65% A 80% A 80% J 65% J 65% A 80% A 100% J 100% A 100% J 100% A 50%−50% 50%−50% Position on the Japanese−American Continuum

27 Figure 24: Eects of Internment Experience Type on Assimilation

Effects of Internment Camp Experience on Assimilation

Militarism

Force

Camp Characteristic Demonstrations

Violence

−0.4 −0.2 0.0 0.2 Position on Japanese (Left) − American (Right) Continuum

Table 20: Internment Status/Length and Assimilation

Dependent variable: Japanese-American Continuum OLS (1) (2) Direct Exposure 2.376 (8.784) Family Exposure 11.191 (18.321) Internment Length −8.105∗∗∗ (2.679) Observations 1,015 784 Controls XX R2 .031 .012 Note: ∗p<0.1; ∗∗p<0.05; ∗∗∗p<0.01