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Racial Resentment, Empathy, and Support for Release during COVID-19: Results from a Survey Experiment

Coronavirus disease 2019 (COVID-19) has presented the American criminal justice system with unprecedented challenges, including protecting the safety of incarcerated men and women. Given the ill-suited structure of correctional facilities to facilitate health and safety guidelines, one solution is decarceration. Yet decarceration has faced political and public backlash. As no evidence currently exists on how the public views this emergency solution, the authors examined the correlates of support for decarceration by conducting a survey experiment in which respondents were randomly presented with information on the dangers of COVID-19 in prisons and jails. Respondents’ attitudes toward releasing various subgroups of the incarcerated population were then measured. The findings indicate that learning about the health risks of COVID-19 in correctional facilities had no discernable effect on support for decarceration for any subgroup. Racial resentment consistently predicted opposition to release for all groups, although its effect largely operated through empathetic identification with those who commit crimes.

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Original Article
On January 30, 2020, the World Health Organization declared a global health emergency in response to the rapid spread of the novel coronavirus. By early February, the United States had experienced its first coronavirus-related death (Fuller and Baker 2020). At the time of this writing, at least 191 countries have registered cases, with a global total of more than 109 million confirmed cases and more than 2.4 million deaths (Johns Hopkins University 2020). The United States alone has confirmed more than 27 million cases of coronavirus disease 2019  and more than 488,000 deaths (CDC 2020c). The elderly, those with preexisting medical conditions, and racial and ethnic minorities are among those most vulnerable to severe illness and death if they contract the virus (CDC 2020a(CDC , 2020b. One of the most pressing ramifications of the coronavirus pandemic has been its toll on the nation's prisons and jails. U.S. correctional facilities are ill equipped to handle viral outbreaks of any kind, let alone a virus as communicable as COVID-19 (Marcum 2020). Correctional institutions are often unhygienic, offer little ventilation, require close contact in common areas and living quarters, struggle to provide adequate health care, and are frequently overcrowded (Nowotny et al. 2020). These conditions make it nearly impossible to adhere to the recommended practices for reducing the spread of coronavirus (Burki 2020).
Beyond the structural vulnerabilities of correctional facilities, the individuals who populate prisons and jails face an elevated risk for contracting and succumbing to the virus. Compared with their peers in the community, incarcerated populations are more likely to have preexisting chronic health conditions that weaken immunity, including tuberculosis, hepatitis C, and asthma (Binswanger, Krueger, and Steiner 2009). Furthermore, the U.S. prison population has grown progressively older over the past several decades (Travis, Western, and Redburn 2014). The vulnerabilities of prisons as institutions, combined with the vulnerabilities of those housed there, have led to the emergence of correctional facilities as COVID-19 hotspots in the United States, with 385,709 confirmed cases and 2,324 deaths among incarcerated adults across state and federal prisons thus far (COVID Prison Project 2020). According to data from the COVID Prison Project (2020), of the 2 million COVID-19 tests administered to persons incarcerated in U.S. correctional facilities, 18.4 percent have shown positive results. Incarceration has also been identified as a key driver of COVID-19 spread in communities (Reinhart and Chen 2020), as correctional officers serve as a vector of transmission between correctional facilities and the surrounding community.
In light of these circumstances, there is growing pressure to mitigate the harm caused to incarcerated populations by . Coalitions composed of community activists, public health officials, medical professionals, legal scholars, and district attorneys have joined forces to demand the immediate release of vulnerable groups (Giorgis 2020), including the elderly and those with underlying medical issues, as well as individuals who have served a majority of their sentences, those being held in pretrial detention for inability to pay bail, and those incarcerated for technical violations of probation or parole (Marcum 2020;Nowotny et al. 2020). In keeping with nearly all contemporary criminal justice reforms, demands for release have been limited almost exclusively to those serving time for nonviolent offenses (Marcum 2020). Although state and federal prisons have released more than 100,000 individuals from custody in response to the pandemic, these efforts have fallen short of hitting the number of releases necessary to meaningfully lower the public health threats facing correctional facilities (Wang et al. 2020).
Given the risks for infection, hospitalization, and mortality in correctional facilities and the subsequent calls for large-scale decarceration, we examine whether learning about the public health threats posed by COVID-19 increases support for releasing people from incarceration. Specifically, we conducted an opt-in online survey experiment in which we randomly exposed one group of respondents to information about the health risks of incarceration during the pandemic, then measured their support for releasing various subgroups of individuals from prisons and jails. Furthermore, we assessed whether traditional predictors of punitive attitudes are associated with support for release in a manner consistent with previous research, and appraised the underappreciated role of empathy in punitive attitudes, as well. Although specific to the COVID-19 pandemic, our study contributes to the small, yet growing body of literature on attitudes toward decarceration and provides a preliminary basis for public policy development in this area.

The Dangers of COVID-19 in Prisons and Jails
Compared with the general population, incarcerated persons are uniquely susceptible to COVID-19 and medical complications linked to viral infection. Correctional facilities are incubators for infectious disease. They disproportionately house the poor and disenfranchised (Alexander 2010), groups with higher than average rates of preexisting health conditions (Wakefield and Uggen 2010). Yet research also suggests that incarceration detrimentally affects health (see Massoglia and Pridemore 2015), especially with regard to infectious disease (Massoglia 2008). Environmental conditions in correctional facilities, including overcrowding, exposure to contaminated food, poor access to hygiene products, and inadequate ventilation, increase risks for adverse health outcomes (Wang et al. 2020).
COVID-19 presents added risks in part because prisons and jails are ill equipped to implement Centers for Disease Control and Prevention guidelines currently in place to limit or reduce exposure to the virus (see The White House 2020). Preliminary research has already established wide variation in the provision of personal protective equipment, with some state departments of corrections offering masks for all incarcerated persons and others banning the use of masks for stated security reasons (Novisky, Narvey, and Semenza 2020). Maintaining at least six feet of physical distance between individuals at all times is also impractical in close living quarters where many adults share supplies, toilets, bunks, showers, and eating spaces. Incarcerated persons lack uninhibited access to sanitation supplies, including soap, hand sanitizer, and surface cleaners (Wang et al. 2020). Prisons and jails are also highly fluid environments. With more than 400,000 correctional staff members coming in and out of correctional facilities each day as they go to work and return home after their shifts (Bureau of Labor Statistics 2020), any efforts to quarantine or medically isolate prisoners have limited utility. In combination, these deficiencies lead to particularly severe consequences among incarcerated persons given their compromised health statuses at baseline. After adjusting for age and sex distributions, the COVID-19 death rate in the U.S. prison population currently exceeds the community death rate by 3 times (Saloner et al. 2020).
The most plausible ways to mitigate the harms associated with COVID-19 and incarceration are front-end and backend policies that share a mutual goal: reductions in population size. Front-end policies consist of decreasing new admissions into facilities. Reducing flow into institutions can help steer any individuals not currently incarcerated away from the COVID-19 health risks associated with incarceration. Doing so can also help lower risks for currently incarcerated individuals, as their exposure to potentially new sources of infection would theoretically decrease. Examples of implementable front-end policies include reductions in the use of pretrial detention, declining to prosecute crimes, and lowering arrest rates. By contrast, back-end policies entail reducing carceral populations by releasing individuals currently incarcerated. Although back-end policies are more difficult to implement because of a lack of legal mechanisms for release, some viable options include paroling individuals early or transferring conditions of supervision to home confinement (Wang et al. 2020). Compassionate release, another back-end option in 46 U.S. states, permits terminally ill incarcerated individuals to die in their communities (Holland et al. 2020). The importance of reducing population size is twofold. First, exposure to COVID-19 hotspots (i.e., prisons and jails) would decline. Second, Centers for Disease Control and Prevention mitigation guidelines, including enforcement of physical space parameters, would become more realistic. Without such reductions, both correctional staff members and the incarcerated face greatly elevated risks for infection, illness, and death.

The Role of Information Exposure
In America's politicized criminal justice climate, it is important to understand the conditions under which people will be more or less supportive of a policy shift such as decarceration. Americans are affected by release decisions through both public health risks, by exposure to COVID-19 via those who are released, and potential public safety concerns, as crime rates could rise if large numbers of individuals are released. Thus, as with most discussions of punishment, we expect individuals to hold strong opinions about releasing incarcerated persons (Garland 1990). These opinions, in turn, can influence public policy in two ways. First, politicians will be attentive to the desires of the public so as to not support policy that is outside the "boundaries of political permission," that is, the range of policies deemed acceptable (not too punitive, not too lenient) (Doble 2002:160). Second, if elected officials violate the public's wishes by supporting a policy with which constituents disagree (e.g., decarceration), voters can mobilize to oust politicians or elected legal actors (e.g., judges, district attorneys). Thus, elected officials must be prudent in their policy decisions so as to retain office.
Studies assessing attitudes toward returning citizens (i.e., those returning to communities following periods of confinement) generally find that people view them as untrustworthy, dangerous, and less deserving of full social inclusion (Hirschfield and Piquero 2010). However, scant research has examined public attitudes toward decarceration. Findings from the few studies that have been conducted indicate that respondents are often supportive of releasing individuals convicted of low-level offenses (Thielo et al. 2016) or those who have exemplified good behavior while incarcerated (Sundt et al. 2015). Although these findings are instructive, there is a dearth of literature on public views toward releasing incarcerated people from prisons and jails. The present study begins to fill this gap.
With regard to releasing incarcerated individuals in the face of COVID-19, one fundamental issue is that the public knows very little about the day-to-day functioning of the criminal justice system , and very little about conditions inside prisons (Wozniak 2014). In light of this reality, we are left with several important questions. First, does providing information on the harms associated with incarceration and coronavirus affect levels of support for releasing people who are incarcerated? On this question, previous experimental research on death penalty attitudes provides some guidance. Over the past several decades, research has explored whether exposing participants to information about the death penalty (e.g., the prevalence of wrongful convictions, the lack of a deterrent effect, the probability of executing innocent people) affects support for capital punishment. On the whole, these studies have found partial support for the notion that information affects death penalty attitudes, although several have found no effect (Cochran and Chamlin 2005). More generally, numerous studies have demonstrated that when given accurate information about crime and punishment, individuals express reduced support for punitive policies (for a review, see Pickett 2019).
In the context of the COVID-19 pandemic and the effect of information on attitudes toward release, research on the affect heuristic provides useful theoretical insight. Put simply, the affect heuristic is the notion that a person's automatic, affective evaluation of a stimuli-good or bad, like or dislike-will guide his or her decision making, especially the assessment of risks and benefits (Slovic and Peters 2006). Previous research has found that benefits and risks are often inversely correlated in people's minds (i.e., as benefits increase, risks decrease; Alhakami and Slovic 1994). Furthermore, when researchers manipulate affective evaluations by providing respondents with information on the risks associated with some phenomenon, respondents' evaluations of the benefits associated with that phenomenon shift accordingly, despite no mention of benefits being made to respondents, indicating that overall affective assessments determine benefit-risk calculations (Finucane et al. 2000). It follows that providing respondents with information on the risks of COVID-19 in correctional facilities may alter their affective assessments of decarcerative policies, thus influencing their likelihood of supporting such measures. Thus, we hypothesize that participants who are exposed to information on the harmful impact of COVID-19 in correctional facilities will be more likely to support decarceration policies than those in the control condition. With national news outlets publishing stories about the myriad dangers posed to people in prisons and jails (see, e.g., Editorial Board 2020; Giorgis 2020), it is of practical importance to investigate whether exposure to these stories might soften attitudes toward releasing people from these facilities.
A related question is whether information effects operate asymmetrically in this context. In other words, does learning about the impact of coronavirus in prisons and jails condition support for releasing one group of people (e.g., the elderly) but not another group (e.g., those with violent convictions)? Prior public opinion research tells us that people are typically more punitive toward those who commit violent crimes (Cullen, Fisher, and Applegate 2000) and repeat offenders (Roberts and Stalans 1997). Furthermore, of the studies that have examined public attitudes toward decarceration, one showed that respondents were supportive of releasing certain groups of incarcerated persons, such as those who earned good behavior credits or completed treatment programs (Sundt et al. 2015), while other studies have shown that individuals support alternatives to incarceration and shortened sentences for "nonviolent drug offenders" (Thielo et al. 2016) and the elderly (Scurich and Monahan 2015). In line with this literature, we hypothesize that respondents in the treatment condition will be more likely to support releasing individuals facing nonviolent charges, the elderly, and those with medical conditions.

Racial Resentment, Empathy, and Support for Decarceration
Beyond information effects, it is theoretically generative to examine how respondent characteristics might condition support for release during a pandemic, as this situation may provide a novel context in which traditional associations between respondent characteristics and punitive attitudes take different forms. Previous research has identified several strong predictors of punitive attitudes which we examine here (Brown and Socia 2017;Unnever and Cullen 2010). Two potentially countervailing factors merit attention: racial resentment and empathetic identification.
Racial resentment is the belief that Blacks' inadequate work ethic and subsequent failure to convert legitimate opportunities into success, rather than racial discrimination, are the source of racial inequality in the United States; as such, Black people should not receive special government assistance (Henry and Sears 2002;Kinder and Sanders 1996). Racial resentment is one of the strongest and most consistent predictors of punitiveness (Barkan and Cohn 1994;Brown and Socia 2017;Unnever and Cullen 2010). Because of the collectively ingrained association of African Americans with crime and dangerousness (Muhammad 2010), often called the racial typification of crime (Chiricos, Welch, and Gertz 2004), we hypothesize that individuals with higher levels of racial resentment would generally oppose decarceration. Importantly, racial resentment may operate differently for subgroups of releasees. Because media often overrepresent Black involvement in violent crimes and underrepresent Black involvement in nonviolent crimes (Gilliam et al. 1996), we expect that respondents with high levels of racial resentment will more strongly oppose release for individuals accused of violent crimes.
Conversely, empathy for those who commit crime might diminish punitive attitudes and thus increase support for decarceration. In their "middle range theory" of empathetic identification, Unnever and Cullen (2009) argued that some people are more apt than others to identify with individuals who commit crime, and thus "people will oppose harsher correctional policies because they empathetically identify with the undue suffering the offender will experience if the policy is enacted" (p. 287). Indeed, previous empirical work has shown that those with higher levels of empathy are less likely to endorse punitive policies (Metcalfe, Pickett, and Mancini 2015;Unnever, Cullen, and Fisher 2005) and more likely to hold positive attitudes toward those who have committed crimes (Batson et al. 1997;Johnson et al. 2002).
Because empathy is grounded in one's ability to imagine another person's distress as one's own (Unnever et al. 2005), the coronavirus pandemic may increase empathetic identification with incarcerated individuals. As American citizens are involuntarily forced into social isolation because of lockdown orders and social distancing guidelines, the idea of being incarcerated away from family and friends may resonate particularly strongly (Giorgis 2020). As a result, "people who can empathetically identify with the offender should be angered that this individual is confronted by forces largely not of his or her own doing [and] feel the distress in the person's life," thereby increasing support for decarceration (Unnever and Cullen 2009:298). Accordingly, we hypothesize that respondents with higher levels of empathetic identification would be more likely to support decarceration policies. It is useful to note, however, that empathetic identification with people who commit crimes is not uniform across all offense categories; it will be higher for those in which the individual identifies with the "typical" perpetrator they imagine when thinking of the crime (Unnever and Cullen 2009). Thus, we should not expect empathy to operate similarly for all subgroups of potential releasees. Because we cannot forecast how individuals may or may not identify with particular characteristics, we did not have specific hypotheses on this point.
The concept of imagining a "typical" person who commits crime or receives punishment is useful because it suggests that empathetic identification should mediate the relationship between racial resentment and support for decarceration. Several scholars posit that individuals create mental images of a stereotypical perpetrator when thinking of particular crimes and punishments (Chiricos and Eschholz 2002;Roberts and Stalans 1997). According to Unnever and Cullen (2009:294-95), if one holds animus toward this imagined subject, he or she will be less likely to empathetically identify with the subject and more likely to attribute remorselessness on his or her behalf, both of which will lead to more punitive attitudes toward this person. In support of this hypothesis, Metcalfe et al. (2015) demonstrated that higher levels of racial typification of violent juvenile crime lead to lower levels of empathy, which in turn lead to increased punitiveness. However, to our knowledge, no studies have directly examined the relationships among racial resentment, empathy, and punitiveness toward adults who commit crime, despite the theoretical utility of this framework. Thus, any empirical relationship between racial resentment and decarceration may be carried through a respondent's empathy for the hypothetical beneficiary of decarceration, which in turn affects support for release. Our final hypothesis is that empathetic identification will at least partially mediate the effect of racial resentment on support for decarceration.

The Present Study
In this study we examine whether individuals are likely to support measures to counteract the harm caused by COVID-19 in prisons and jails, namely, decarceration through the release of particular subgroups of people who are incarcerated. Primarily, we investigate whether learning about coronavirus in correctional facilities conditions support for release, which factors predict support or opposition to release policies, and whether the influence of certain factors varies across subgroups of potential releasees. As we describe in more detail below, we conducted a survey experiment in which some individuals were randomly exposed to information about COVID-19 in prisons in jails, with all respondents then being asked to express their support for or opposition to releasing various groups of incarcerated people.

Participants
We recruited participants through Amazon Mechanical Turk (MTurk) between April 15, 2020, and April 19, 2020, to participate in an experiment embedded in a larger survey about criminal justice attitudes in return for $0.75. To begin, 678 respondents were assigned to an experimental condition (n = 339 in each condition). Because of listwise deletion of cases with missing data on key variables, and to make comparisons across our outcomes, our final analytic sample consists of 650 respondents who have full information on all variables. Specifically, there were 327 respondents in the control group and 323 in the treatment group. 1 Consistent with other studies using MTurk, our sample composition does not reflect the exact characteristics of the U.S. population (Levay, Freese, and Druckman 2016;Thompson and Pickett 2020). In the analytic sample, respondents reported an average age of 39.75 years (SD = 13.4 years); 54 percent of the sample was male, 79 percent selfidentified as non-Hispanic white, and 13 percent were Latino. Furthermore, 70 percent reported being employed full-time, and 57 percent were married. Regarding Republicanism, respondents were slightly more Republican on average (M = 2.80, SD = 1.21 where 1 = strong Democrat and 5 = strong Republican). Approximately 21 percent of respondents reported that they or family members had been victimized within the past 5 years. Despite the nonrandom and nonrepresentative nature of the sample, our parameter estimates should remain unbiased provided that the variables that influence selection into the sample are included in our models (Solon, Haider, and Wooldridge 2015;Thompson and Pickett 2020;Winship and Radbill 1994). Prior research (Levay et al. 2016) suggests that MTurk workers and probability samples of the U.S. population typically differ on observable characteristics (e.g., demographics, political ideology), so our inclusion of these covariates in the regression models should mitigate the threat posed by the nonrandom nature of the sample. See Table 1 for full descriptive statistics for the sample, disaggregated by experimental condition.
To ensure data quality, we followed the current best practices and limited our sample to MTurk workers who had completed at least 50 Human Intelligence Tasks and had a Human Intelligence Task approval rating of at least 95 percent (Peer, Vosgerau, and Acquisti 2014). As our focus is on American criminal justice policy, we limited our sample to U.S. residents. We also included two items designed to detect respondent inattention, which could contaminate data quality (Berinsky, Margolis, and Sances 2014).

Procedure
All participants received the following text: "The CORONAVIRUS (COVID-19) is a highly contagious virus that first infected people in China in 2019 and has since spread to the United States and other countries around the world, resulting in a worldwide pandemic." Those in the treatment condition received the following additional instructions: "Please read a brief summary from the following article about the impact of the CORONAVIRUS pandemic in PRISONS AND JAILS in the United States." To realistically replicate how citizens receive media exposure, treatment condition respondents were shown a picture of an online New York Times article heading titled, "'Jails Are Petri Dishes': Inmates Freed as the Virus Spreads Behind Bars," with the subtitle, "Some jails are releasing people to stem outbreaks, but critics say it is not happening quickly enough to save lives and resources" (Williams, Weiser, and Rashbaum 2020). The image was followed by a summary of the information in the article: Many scholars are concerned that inmates are in danger during the coronavirus pandemic. Prisons and jails are often crowded and unsanitary. Many inmates are old, come from backgrounds of poverty, and have a history of poor healthcare. Some inmates suffer from respiratory problems and heart conditions. Practices to slow the spread of the virus-avoiding crowds, frequent handwashing, disinfecting clothing-are nearly impossible inside prisons and jails.

Measures
Dependent Variables. To gauge support for decarceration policies, we first presented respondents the following prompt to ensure that they understood the meaningful distinction between prisons and jails: "In general, JAILS hold people AWAITING TRIAL or convicted of MISDEMEANORS, whereas PRISONS hold people convicted of FELONIES." We then asked them to indicate how much they support or oppose "RELEASING the following types of INMATES during the CORONAVIRUS (COVID-19) PANDEMIC" (1 = "strongly oppose," 5 = "strongly support"). The following subgroups were presented in random order: (1) "elderly inmates awaiting trial for nonviolent charges" [EJNV], (2) "jail inmates who are serving short sentences for nonviolent crimes (e.g., DUI)" [JNV], (3) "prison inmates who have already served at least 85% of their sentences" [P85], (4) "jail inmates awaiting trial for violent charges" [JV], (5) "elderly prison inmates with violent convictions" [EPV], (6) "elderly prison inmates with nonviolent convictions" [EPNV], and (7) "jail inmates awaiting trial who have underlying medical conditions" [JMC]. We differentiate the subgroups on these various characteristics (incarceration facility, offense type, age, proportion of sentence served, conviction status, health status) because they reflect current debates about who should be eligible for release under emergency decarceration measures in terms of perceived dangerousness, risk for severe illness, and societal debts paid (Editorial Board 2020).
Empathetic Identification. We measure empathetic identification using a scale adapted from Metcalfe et al. (2015). 2 Respondents were asked to indicate the extent to which they agreed or disagreed with the following statements on a fivepoint scale (1 = "strongly agree," 5 = "strongly disagree"): (1) "despite the bad things they have done, I would still feel sorry for offenders if they were having problems in life"; (2) "even though they have committed crimes, I still feel pity for offenders"; (3) "offenders' problems do not disturb me a great deal"; (4) "if I saw an offender in pain, it wouldn't bother me much." Items 1 and 2 were reverse-coded such that higher values indicate higher levels of empathy. Exploratory factor analysis determined that the items load on a single factor; we averaged respondents' responses to the four items to create a mean index for empathetic identification (α = 0.75, M = 3.25, SD = .82).
Racial Resentment. We operationalized racial resentment as the average response to five Likert-type statements adapted from Henry and Sears's (2002) Symbolic Racism 2000 scale.
Respondents were asked to indicate how much they agree or disagree (1 = "strongly agree," 5 = "strongly disagree") with the following statements: (1) "Irish, Italians, Jewish, and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors"; (2) "Generations of slavery and discrimination have created conditions that make it difficult for Blacks to work their way out of the lower class"; (3) "Over the past few years, Blacks have gotten less than they deserve"; (4) "It's really a matter of some people not trying hard enough; if Blacks would only try harder they could be just as well off as Whites"; (5) "There is a lot of discrimination against Blacks in the U.S. today, limiting their chances to get ahead." These items load on a single factor and demonstrate a strong degree of internal consistency (α = 0.88). We generated our measure of racial resentment by averaging responses. Higher values indicate greater racial resentment (M = 2.77, SD = 1.06).

COVID-19-Related Fear and Exposure to News Coverage.
Previous research shows that personal and altruistic fear can affect the way citizens think about and respond to crime and crime control (Drakulich 2015;Warr and Ellison 2000).
Accordingly, we included items to measure the level of personal and altruistic fear respondents feel regarding potential consequences of the coronavirus pandemic. Personal fear was measured with a single item that asked, "How worried are you that you will become sick from the coronavirus?" (1 = "not worried at all," 4 = "very worried") (M = 2.77, SD = .87).
For altruistic fear, we asked respondents how often (1 = "very rarely," 5 = "very often") they worried about the following six groups of people becoming sick from the coronavirus: (1) "First responders, police, and correctional officers"; (2) "your family members"; (3) "your neighbors"; (4) "doctors and nurses"; (5) "people across America"; (6) "your friends." Responses loaded on one factor with loadings ranging from .77 to .83. We averaged the items to create an index of altruistic fear (α = 0.91, M = 3.35, SD = .99). Finally, because of the widespread news coverage of the COVID-19 pandemic, and evidence that news media consumption is linked to attitudes about crime and punishment (Baranauskas and Drakulich 2018), we asked respondents how closely they had followed news about the pandemic (1 = "not at all closely," 4 = "very closely") (M = 3.32, SD = .74).
analyzing the main effects of the experimental manipulations as well as the independent and control variables. 4 In keeping with recommendations in the experimental literature (Freedman 2008;Lin 2013), we first estimate a model with only the experimental manipulations and then introduce the remainder of the independent and control variables. Finally, we estimated supplementary models excluding respondents who failed one or both of the attention checks, as well as those who completed the survey in the fastest 10th percentile (less than eight minutes). The coefficients presented in the tables are log odds. For ease of interpretability, we discuss these effects in terms of average marginal effects, which can be interpreted as the effect of a one-standard deviation change in the independent variable on the predicted probability of a given outcome (e.g., strongly oppose).
To determine whether empathetic identification mediates the effect of racial resentment on support for decarceration, we use the user-written khb package in Stata 15 (Kohler, Karlson, and Holm 2011), which allows us to assess the direct and indirect effects of racial resentment on support for decarceration through empathy. Note that coefficients derived from nonlinear probability models are scaled relative to the residual standard deviation of the underlying linear model. For example, an estimator, b, for a binary logit model takes the form b = β/σ, where β is the underlying linear coefficient, and σ is the residual standard deviation of the linear model. Of course, the residual standard deviation of a full model will be smaller when another variable, Z (e.g., a mediator), is introduced and this variable is correlated with the outcome. Thus, when comparing coefficients across nested nonlinear probability models, it is impossible to distinguish whether differences in the coefficients are due to mediation or to the rescaling of coefficients across the models.
The khb method overcomes this issue by first regressing the mediator variable, Z, on the variable thought to be mediated, X. The residual from this equation-that is, the portion of Z that is not correlated with X-is then used in the reduced regression model so that the residual standard deviation is the same in the reduced model as in the full model, thus avoiding the issue of rescaling. One can also assess the statistical significance of the indirect effect by testing the null hypothesis that the difference between the X coefficient in the reduced model versus the full model is zero (see Kohler et al. 2011 for more information on significance testing and the khb command in Stata generally).
Two other analytical considerations bear mention. First, because theory suggests that racial resentment and empathetic identification may exert differential effects on our outcomes, we compare the magnitude of these coefficients across models through a series of seemingly unrelated regression models. Second, because of the large number of significance tests we conduct, we use Bonferroni-adjusted α levels to guard against the increased risk for type I error that we incur when making multiple comparisons. The Bonferroni correction is recognized as being a conservative correction (Abdi 2007), which allows us to have more confidence in the robustness of statistically significant results that meet the more stringent threshold. With 21 main regression models (3 models per seven outcomes), four equality of coefficients tests, and 21 khb mediation tests (3 tests per seven outcomes), we use an α level of .0011 (.05/46). Table 1 shows the percentage of respondents who supported or strongly supported releasing each of the seven subgroups of incarcerated individuals during the COVID-19 pandemic. Only three of the seven subgroups-elderly people in prison with nonviolent convictions (61 percent), elderly people in jail with nonviolent charges (64 percent), and people in jail for nonviolent charges (57 percent)-received a majority of support for release. Alternatively, we found the lowest levels of support for releasing individuals whose charges or convictions were violent: only 16 percent of respondents favored releasing elderly people in prisons with violent convictions, and only 14 percent supported release for individuals in jails facing violent charges. These findings are consistent with the juxtaposition of violent versus nonviolent offenses in contemporary criminal justice reform discourse (Gottschalk 2015). Between these two extremes were individuals who have served 85 percent of their prison sentence (with 47 percent supporting release), followed by those with underlying medical conditions incarcerated in jails (with 45 percent supporting release). It is worth repeating that these point estimates may not represent the opinion of all American citizens because of the nonrandom nature of our sample. Nonetheless, they offer preliminary insight into broader conceptions of deservingness when it comes to considering some incarcerated subgroups for release during the pandemic. Table 2 displays the results of ordered logistic regression models predicting support for release for each subgroup, including only the experimental manipulation as a regressor. With these preliminary models, we find no evidence of information effects on support for releasing any of the seven subgroups during the coronavirus pandemic. In other words, informing respondents of the various risks of coronavirus in prisons and jails did not affect their expressed support for decarceration. Thus, we find no support for our first hypothesis.

Results
Examining the reduced model across each dependent variable in Table 3, we find that racial resentment and altruistic fear for others are the most consistent predictors of whether a respondent supports or opposes decarceration during the pandemic. 5 For five of the seven outcomes (EPNV, EJNV, P85, JMC, and JNV), altruistic fear increases the probability of supporting decarceration. For instance, a 1-SD increase in altruistic fear is associated with a .112 increase in the probability of strongly supporting release for individuals serving a jail sentence for a nonviolent offense (p < .001), holding all else constant. Confirming our hypotheses, racial resentment increases the likelihood that an individual will oppose release. For example, a 1-SD increase in racial resentment is associated with a .030 increase in the probability of strongly opposing release for individuals serving time in jail for a nonviolent offense (p < .001), holding all other variables constant. Besides racial resentment, only two other covariates-authoritarianism (significant in the EPNV and EJNV models) and personal fear of COVID-19 (significant in the JNV model)-also emerged as significant predictors, both decreasing the likelihood of expressing support for decarceration.
We next examine whether the effect of racial resentment varies across the seven outcomes, particularly for violent offenses versus nonviolent offenses. To assess this possibility, we estimate seemingly unrelated regression analysis using Stata's suest command for the JV and JNV outcomes, then tested for the equality of the racial resentment coefficients across each model. 6 The results indicate that the difference between the effects of racial resentment on support for decarceration between the two subgroups is statistically indistinguishable from zero (χ 2 = .55, p = .459). We reach the same conclusion when comparing the racial resentment coefficients Note: b = unstandardized log odds; COVID-19 = coronavirus disease 2019; EJNV = elderly inmates awaiting trial for nonviolent charges; EPNV = elderly prison inmates with nonviolent convictions; EPV = elderly prison inmates with violent convictions; JMC = jail inmates awaiting trial who have underlying medical conditions; JNV = jail inmates who are serving short sentences for nonviolent crimes (e.g., DUI); JV = jail inmates awaiting trial for violent charges; P85 = prison inmates who have already served at least 85 percent of their sentences; SE = standard error. 5 All models in Table 3 include standard demographic controls, but being that none of these variables reached statistical significance in the analyses, they are omitted from the table for ease of presentation. Models presenting coefficients for all covariates are available in the Online Supplementary Appendix. 6 The results and corresponding code for these analyses are available online at https://osf.io/v2hxs/files/.
between the EPV and EPNV models (χ 2 = 1.64, p = .200). Therefore, we find no support for our hypothesis that the effect of racial resentment varies between subgroups associated with violence and those associated with nonviolence. Model 3 introduces the measure of empathy. The likelihood ratio tests show that the addition of empathy significantly improves model fit for each of the seven outcomes. The full models confirm our hypothesis that empathetic identification with those who commit crime is an important factor in whether a respondent expresses support for decarceration; it is a significant predictor for all seven outcomes. A 1-SD increase in empathy, for example, is associated with a .090 increase in the probability of strongly supporting release for people in jail serving sentences for nonviolent charges (p < .001), holding all else constant. To test our hypothesis regarding asymmetrical effects for empathy, we next examine whether there are differential effects of empathy on support for releasing subgroups. Comparing the coefficients for empathy in the JV and JNV models, we find no evidence of a statistically distinguishable difference (χ 2 = 2.43, p = .1189). 7 Thus, there do not appear to be differential effects of empathy on support for decarceration between subgroups associated with violent versus nonviolent offenses.
We turn now to the mediating role of empathy between racial resentment and support for decarceration. When empathy is included in the regression equations in model 3, the coefficient on racial resentment diminishes across all seven outcomes and retains statistical significance for only one of the subgroups under consideration: those in jail awaiting trial for violent charges. Taken together, these findings offer preliminary support for the hypothesis that empathy mediates the impact of racial resentment on support for decarceration.
Results of the mediation analyses indicate that empathy fully mediates the direct effect of racial resentment on support for decarceration in the EPNV, EPV, EJNV, P85, JMC, and JNV models. 8 Although the direct effects are attenuated 7 As with racial resentment, there is no difference between the empathy coefficients in the EPV and EPNV models either (χ 2 = 0.00, p = .972). 8 See Table B1 in Appendix B for results from khb mediation analysis. . .0000 .0000 .0000 .0004 .0000 .0000

Note:
Coefficients are presented with standard errors in parentheses; "LR test" presents results from likelihood ratio test comparing model 2 and model 3; the models include standard controls for demographics (race, ethnicity, gender, age, marital status, educational attainment, income, employment status) and political ideology, but we omit them for ease of presentation. COVID-19 in the full models, racial resentment retains a statistically significant indirect effect through empathy. In the JV model, we see that racial resentment retains a statistically significant and negative direct effect on expressed support for decarceration during the pandemic, but the coefficient is reduced from b = −.519 to b = −.393, a change of −24.29 percent (p < .001). As with the other outcomes, racial resentment exerts a statistically significant indirect effect on support for decarceration through empathy (b = −.126, p < .001).

Supplementary Analyses
In an effort to assess the robustness of our results, we report two sets of supplementary analyses. First, as our experiment requires that respondents actually read the treatment information for it to have an effect, we included two attention check items, or "screeners," in the questionnaire that "work by instructing subjects to demonstrate they are paying attention by following a precise set of instructions when choosing a survey response option" (Berinsky et al. 2014:739). In total, 78 percent of respondents passed the first item, 91 percent passed the second item, and 77 percent passed both.
Although attention check items are imperfect assessments of whether a respondent received the intended treatment, it is best practice to examine findings with and without these respondents (Berinsky et al. 2014). When we limit the sample to those who passed one or both attention checks (n = 603), we find that racial resentment is no longer significant at the Bonferroni-corrected α level in model 2 for the EPNV (b = −.284, p = .003) and EJNV (b = −.295, p = .002) regressions. We next reestimated our models after excluding individuals who completed the survey much more quickly than other respondents, as it is possible that they did not properly receive the treatment. To do so, we reran our analyses without individuals whose survey completion time was less than 7.83 minutes, meaning that they finished faster than 90 percent of the respondents in the analytic sample. 9 With this restricted sample (n = 586), we see similar changes as when we stratified the sample on the basis of a respondent's passing or failing of attention checks: racial resentment again fails to achieve the Bonferroni-corrected α value in the EPNV (b = −.256, p = .0078) and EJNV (b = -.304, p = .0017) regressions.

Discussion and Conclusion
Incarceration is a powerful social determinant of health (Massoglia and Pridemore 2015), and the COVID-19 pandemic offers but one timely example of how experiences with incarceration can structure exposure to health-related harms. In particular, "prisoners and correctional staff share an environment known to amplify, accelerate, and act as a reservoir for outbreaks of respiratory diseases" (Montoya- Barthelemy et al. 2020:1). Coupled with correctional facilities' inability to implement even the most basic public health measures necessary to mitigate the spread of COVID-19 (Burki 2020), these circumstances have left incarcerated persons especially vulnerable to COVID-19 infection, hospitalization, and mortality, with perceptions among prisoners that "it was not a matter of if, but when, the virus would ultimately reach their facility" once the outbreak began (Pyrooz et al. 2020:301).
The single measure with the greatest capacity to curb the spread of COVID-19 in American correctional facilities is drastic reductions in prison and jail population sizes through the release of incarcerated persons (Wang et al. 2020). However, elected officials are unlikely to endorse and authorize such releases without support from their constituents. In turn, constituents' attitudes toward release may well hinge on the information conveyed to them by the media given the general lack of knowledge of correctional conditions (Wozniak 2014). It is therefore important to understand (1) whether American citizens support decarceration for particular subgroups during the COVID-19 pandemic, (2) how support for decarceration may vary on the basis of media exposure, and (3) what other factors are related to attitudes toward decarceration. The results of our study shed light on these questions.
Although the specific levels of support in our sample are not generalizable to the American public because of the nonrandom nature of the sample, the rank ordering of potential releasee subgroups may hint toward broader notions of deservingness among U.S. citizens. Indeed, a wealth of evidence indicates that across demographic groups, cultures, and time periods, humans are remarkably consistent in ranking the relative severity of various offenses (see Robinson and Kurzban 2007). In our study, respondents were most likely to support release for subgroups associated with nonviolence, followed by old age. These findings are consistent with prior research on deservingness of compassionate release, where sampled undergraduate students ranked convicting offense (violent vs. nonviolent) as the single most important decision-making factor for compassionate release of terminally ill incarcerated adults (Boothby and Overduin 2007). Our results also reinforce broader discussions of criminal justice reform and who is generally viewed as "deserving" of compassion (Gottschalk 2015), as well as previous research demonstrating more punitive attitudes toward those accused or convicted of violent offenses (Cullen et al. 2000). Together, these findings suggest that officials could reasonably release individuals convicted or charged with nonviolent crimes without much backlash. Future research should explore this possibility more fully and in the context of contemporary criminal justice reforms which often juxtapose "deserving" and "undeserving" groups.
Our study also expands the literature by exploring how public support for decarceration is related to exposure to information about the health risks of being incarcerated during COVID-19. Specifically, in all models we found that learning about COVID-19 had no discernable impact on support for release. One potential explanation for this null finding is periodicity: the data were gathered in the early stages of the U.S. outbreak (between April 15, 2020, andApril 19, 2020), when case numbers and deaths were far fewer. As knowledge about the novel coronavirus grows with each passing day, and as public perceptions of its gravity wax and wane (Laughlin 2020), the impact of information on support for decarceration may fluctuate as well. As the U.S. death toll continues to rise, learning about the harmful effect of COVID-19 on prisons and jails may alter citizens' affective assessments of the pandemic and its attendant risks and benefits (Slovic and Peters 2006) and thus have a greater impact on whether someone supports releasing subgroups of individuals from incarceration.
On the other hand, these results may signal further evidence that Americans are insensitive or apathetic toward the needs of people who are incarcerated, even when faced with information as to the unreasonable harms faced by those behind bars, and regardless of factors that make incarcerated persons especially vulnerable (e.g., elderly age, illness) or "deserving" of release (e.g., majority of sentence completed, nonviolent conviction). It is possible that exposure to information about incarceration-specific COVID-19 health risks had no impact on support for release because respondents simply perceive COVID-19 risks as another layer or reasonable "pain of punishment" (Sykes 1958). Considering the dehumanizing nature of incarceration in general (Haney 2012), the pandemic may not be viewed as a severe enough departure from the ordinary to warrant support for release. In other words, individuals' views about incarceration may be so entrenched and unwavering that little will change their minds, including awareness that incarcerated people will be subjected to various, potentially lethal, collateral consequences should they remain behind bars. In this light, our null findings align with the idea that crime and punishment represent important symbolic aspects of society about which the public's views are firmly held and resistant to change (Garland 1990).
Our finding that racial resentment is consistently related to opposition to release across all seven subgroups adds to the substantial body of literature on the centrality of racial animus for punitive attitudes. Many previous studies have determined that racial resentment reliably predicts support for punitive crime policies (Barkan and Cohn 1994;Brown and Socia 2017;Unnever and Cullen 2010). Alternatively, our study, along with others (e.g., Wozniak 2018) demonstrates that racial resentment is significantly and negatively related to nonpunitive policies aimed at reducing the incarcerated population as well. Thus, not only is American racial animus important for the enactment and enforcement of harsh crime policies, but it inhibits reforms aimed at dialing back the harm caused by those harsher policies, such as decarceration. Interestingly, we did not find stronger effects of racial resentment for subgroups associated with violence, a finding that controverts our theoretical expectations. Still, the results paint a particularly dismal picture for those who advocate decarceration as a means to reduce high levels of incarceration: even during the worst public health crisis of the past century, in which incarcerated populations face extreme risk for illness and death, Americans with racial animus consistently oppose releasing people from prisons and jails, even those who are especially vulnerable.
As our results show, however, this relationship is largely carried through empathetic identification with those who commit crime, which offers theoretical and practical implications. Theoretically, our study is the first to our knowledge to empirically test the mediating role of empathy between racial resentment and punitiveness, as theorized by Unnever and Cullen (2009). Practically, several leading scholars (e.g., Austin et al. 2019;Sered 2019) have emphasized the need to contextualize crime and the complex life histories that lead to crime and incarceration to curtail the American tendency toward severe punishment and thereby reduce imprisonment. Our results, coupled with research that empathy can be externally induced (e.g., Batson et al. 1997;Johnson et al. 2002), suggest that humanizing depictions of people who commit crime or who are incarcerated may increase support nonpunitive policies such as decarceration.
It is important to consider our findings in the context of certain limitations. First, our null finding for the experimental treatment may be because the instrument was too weak. Although we believe our treatment mimics a realistic scenario of news consumption in an era of information inundation, respondents may need more (or different) information to adequately alter their attitudes toward decarceration. Relatedly, our null finding may be due to the source of information; it is possible that information derived from a public health authority, rather than news media as in our experiment, may be more likely to sway respondents' opinions regarding decarcerative policies. Furthermore, some informational sources may be more or less effective at influencing opinion depending on respondents' characteristics (e.g., political ideology). Although some research (Rydberg, Dum, and Socia 2018) has found that varying the source of information of criminological knowledge has no impact on respondents' policy preferences, we encourage researchers to explore these possibilities in future research.
Second, our data are composed of an opt-in, online sample and results may not be generalizable to the American public. Although several studies have shown that results from MTurk experiments can be extrapolated to the U.S. population (Coppock 2018;Mullinix et al. 2015;Weinberg, Freese, and McElhattan 2014) and that relational inferences are generally consistent with probability samples (Thompson and Pickett 2020), it remains true that point estimates of population parameters, such as the level of support for releasing a specific subgroup, are not externally valid. However, the primary foci of our analysis are the experimental effects of information exposure and the covariates of support for decarceration, and as such, concerns about generalizability largely hinge on effect heterogeneity in the population (Thompson and Pickett 2020).
Finally, we assess desirability of release only for some subgroups of incarcerated persons in the context of the pandemic. Although we believe that these subgroups capture key factors that organize contemporary discussions of decarceration, they are unlikely to attend to the full range of nuanced differences in individual circumstances, or respondents' beliefs related to culpability and the sufficiency of punishment. It is possible, for example, that people will more readily support decarceration efforts for incarcerated women versus men, especially if participants are given information about the often nonviolent nature of women's offending and information that explains how women's pathways to incarceration are often driven by histories of victimization and marginalization (Salisbury and Van Voorhis 2009).
It is also important to consider the broader implications of our findings for the criminal justice system beyond the pandemic. For example, although the majority of U.S. states have compassionate release programs in place, they are rarely used (Wang et al. 2020). Providing information to individuals about the stringent criteria for compassionate release, including prognosis of less than six months of life, older age, and assurances that the individual does not pose public safety risks (Holland et al. 2020), may result in higher levels of support. Another possibility is to explore how information exposure on the health-related harms of parental incarceration for children could relate to support for decarceration (Turney 2017;Turney and Goodsell 2018). Furthermore, although research has found that drawing attention to racial disparities in incarceration influences support for both punitive (Hetey and Eberhardt 2014) and progressive (Gottlieb 2017) criminal justice policies, no research has examined the impact of such information on support for decarceration. We urge for further work in these areas to cast a wider net in terms of the range of subgroups examined, the types of information exposure assessed, and the policies under consideration.
The COVID-19 pandemic has introduced unforeseen complexities into the administration of criminal justice in the United States. Despite substantial knowledge of the potential effects of COVID-19 in prisons and jails, the response has been meager at best: although local jails have reduced their populations by about 20 percent on average, state prisons, wherein the lion's share of the U.S. incarcerated population resides, have averaged reductions of roughly 5 percent (Wang et al. 2020). As the coronavirus continues to ravage states across America, and as in-custody deaths continue to climb (COVID Prison Project 2020), the need to reduce the number of people incarcerated becomes ever more pressing. Although our study offers pessimistic conclusions about support for decarceration among Americans with high levels of racial animus, it also suggests that releasing groups associated with nonviolent offenses, particularly the elderly, is comparatively more palatable than releasing those associated with violent offenses. Decarceration, of course, must be balanced against veritable public safety concerns regarding potential increases in crime, and precautions must be taken to ensure releasees who may have been exposed to the virus do not become vectors for transmission in their communities. Yet in the absence of other measures to stem the spread of COVID-19 in prisons and jails, decarceration remains the most humane and public health-oriented measure to protect vulnerable populations incarcerated during the pandemic.