American Public Opinion About Prisons

Abstract

Politicians in the United States frequently cite public anger when they attack “country-club” conditions in prisons. Despite the ubiquity of this rhetoric, it is backed by limited empirical support. Few studies measure American citizens’ attitudes toward prison conditions, and even fewer studies do so with data from random samples of the population. To address this limitation in our knowledge, I measure public perceptions of life in prison and opinions about the appropriate severity of punishment in prison with data from an original public opinion survey administered to a national sample of the U.S. population. I find that a plurality of respondents both perceive life in prison to be unpleasant and voice the opinion that life in prison should be harsher still. I contextualize these findings within the broader study of public opinion about punishment.

Keywords

prison corrections crime policy public opinion survey methods politics

Introduction

The Politics of Punishment

One of the most significant changes to American society over the past 40 years has been the rise of the “penal harm movement” and “mass incarceration” (Clear, 1994; Garland, 2001; Gottschalk, 2006). Beginning in the 1970s, policy makers abandoned the rehabilitation-centric paradigm that dominated corrections in the 1960s in favor of policies that lengthened prison sentences, abolished parole, and curtailed judicial discretion. These policy changes sparked an exponential increase in the nation’s incarceration rate, culminating in the present reality that the United States imprisons over two million of its citizens and has an incarceration rate several times higher than that of any other industrialized nation in the world (Blumstein & Beck, 1999; Warren, Gelb, Horowitz, & Riordan, 2008).

Beyond expanding the scope of punishment, advocates of “tough on crime” policies also worked to increase the harshness of punishment. Politicians framed criminal justice as a “zero-sum game” in which any policy choice that was good for offenders was bad for victims of crime. Under this logic, the only way to deliver justice to crime victims was to make offenders suffer (Simon, 2007; Zimring, Hawkins, & Kamin, 2001). A notable manifestation of this principle was the “no-frills” movement of the early 1990s (Finn, 1996). One survey found that about 60% of state departments of corrections raised the requirements for inmates to participate in programs or eliminated privileges in prison, such as free weights, radios, and TVs. Even Congress enacted the “No-Frills Prison Act” in 1996, which was designed to eliminate “luxurious” conditions in federal prisons (Wunder, 1995).

Importantly, many wardens believed that “the single most powerful driving force behind [no-frills bills was] legislators who believe the legislation helps them to get elected or reelected by offering the impression that they are tough on crime” (Finn, 1996, p. 36; see also Johnson, Bennett, & Flanagan, 1997). Politicians and the media believed that the public angrily resented conditions in prisons that they perceived to be like a resort or country club (Bidinotto, 1994; Welch, Weber, & Edwards, 2000). As an illustrative example, Boulard (1995, p. 24) quotes a Colorado state senator who said, “There is a concern that crime is out of control and that the people responsible for it come to prison and live the good life. It is now up to us as lawmakers to address those concerns and see what needs to be improved upon or taken away or just changed” (see also Crist, 1996; Gottschalk, 2006; Lynch, 2010, for other examples of politicians attacking prison amenities). Roberts and Hough (2005) argue that the public perception of life in prison as “easy” fueled penal populism and politicians’ support for longer, harsher sentences. Beyond the “no-frills” movement, politicians frequently cited punitive public opinion as their justification for supporting all the penal policies that gave rise to mass incarceration (Beckett, 1997), and a growing body of research indicates that a relationship does exist between mass public opinion and criminal justice system outcomes (Enns, 2014; Nicholson-Crotty, Peterson, & Ramirez, 2009).

In spite of the politicized debate over prison living conditions, the ongoing court battles about overcrowding, and the simple fact that the United States imprisons more people than any other industrialized country in the world, we possess surprisingly little data that actually measure citizens’ opinions about prisons. Furthermore, the few studies that measure these attitudes possess limited generalizability. From a scientific point of view, we do not properly understand the extent to which politicians’ claims of public antipathy toward country-club prisons are supported by empirical evidence (if at all).

Public Opinion About Prisons: A Dearth of Research

Most of what criminologists know about public opinion is pertinent but tangential to the present study. Several studies found that pluralities of citizens in countries around the world classify rehabilitation as a more important purpose for imprisonment than retribution (e.g., Cullen, Fisher, & Applegate, 2000; Cullen, Pealer, Fisher, Applegate, & Santana, 2002; Flanagan & Caulfield, 1984; Roberts & Hough, 2005). Other surveys find that a majority of U.S. citizens support educational and vocational programs in prisons, as well as the ability to earn good time credit toward a sentence reduction (Flanagan, 1996; Haghighi & Lopez, 1998). While these findings reveal what people want prisons to do, these studies do not measure public perceptions of and attitudes about the prison environment that formed the political core of the no-frills movement. As such, they shed no light on the empirical question of whether or not people perceive and resent so-called country-club conditions in prisons.

Our most in-depth information about American public perceptions of life in prison comes from qualitative focus groups and/or interviews. Most of these studies do find that participants perceive prison life to be too easy and comfortable for inmates, and many people resent inmates’ access to amenities, like TV and exercise equipment (Cook & Powell, 2003; Doble, 1987; Doble, Immerwahr, & Richardson, 1991; Doble & Klein, 1989; Sasson, 1995). This punitive view is the majority opinion among participants in most, but not all, focus groups. For example, researchers in Massachusetts found that only 1 single person out of all the participants in 20 different focus groups challenged the characterization of prison conditions as “plush” (Beckett & Sasson, 2004). In contrast, Gaubatz (1995) found that only 2 of the 24 interviewees from California perceived prison conditions to be easy; the majority of her participants expressed opinions that prison life was uncomfortable and stressful for inmates.

While interviews and focus groups are excellent methods to gather rich data on the substance of people’s opinions, the inherently limited nature of these samples prevents scholars from generalizing these findings to a wider population. In the absence of data from probability samples, we cannot determine whether the opinions voiced in these focus groups represent the views of a majority of Americans or merely a minority of citizens with particularly strong views about criminal justice who would be motivated enough to take part in a focus group.

Only a handful of studies analyze data from samples with stronger external validity. Two studies analyze data from probability samples of Florida citizens, and they find that, on average, at least 50% of respondents support retaining most amenities in prison, though the precise level of support varies from amenity to amenity and differs according to whether respondents are told that funding for the amenities comes from tax dollars or from inmates themselves (Bryant & Morris, 1998; Lenz, 2002). Analyzing data from a nonrandom, quota sample of citizens from Orange County, Florida, Applegate (2001) found that, on average, respondents supported retaining 16 of the 26 proposed amenities (such as books, TV without cable, and air conditioning), and no respondent said that he or she would eliminate all amenities. While we cannot use these studies to generalize to the entire U.S. population, they do possess stronger external validity than the focus group studies. Importantly, they paint a different picture; when we measure the opinions of citizens across a wider area, such as a county or state, we see much more support for amenities in prison than the level of support voiced in the focus groups.¹ These data suggest that the qualitative studies may have attracted participants who hold more antithetical attitudes toward prisons than most Americans.

I am aware of only a single survey that directly measures public opinion about the prison environment using a nationally representative sample. Researchers at the survey firm Belden Russonello and Stewart Research and Communications (2001) asked respondents, “From what you know, do you think life in prison is too harsh, not harsh enough, or about right?” They found that only 10% of respondents believed that prison life is too harsh, 35% believed that it is about right, and 42% believed that it is not harsh enough. In addition, 59% of respondents agreed or somewhat agreed with the statement, “Prisons are too comfortable and criminals don’t mind being sent to prison.” These findings suggest that the antipathy toward “country-club prisons” voiced by respondents in the focus groups is, indeed, the majority opinion among American citizens across the country (as indicated by the finding that a plurality of respondents want life in prison to be harsher). While this poll was an important step forward, the authors presented only sample statistics; without analyzing the predictors of people’s attitudes about life in prison, we cannot compare this issue to the broader literature on public opinion about punishment.

The Current Study

In order to overcome the limitations in past studies on public opinion about the prison environment, I measured people’s attitudes about prisons through an original survey administered to a national sample of the U.S. population. Beyond attempting to replicate the descriptive findings of Belden Russonello and Stewart (2001) with a new data set, I seek to analyze the factors that shape opinion about prison by also measuring other beliefs and characteristics that influence people’s opinions about punishment.

Theoretical expectations

While dozens of studies have explored the empirical correlates of people’s attitudes toward punishment, Unnever and Cullen (2009) note that no general theory organized the myriad predictor variables into a single explanatory framework. The long-standing absence of a general theory of public opinion about punishment was exacerbated by the fact that scholars agree upon no single, consensus definition or theory of punitiveness more broadly (Matthews, 2005). Thus, to guide my present model specification, I draw upon the handful of public opinion theories that do exist, and I supplement their guidance with past findings from the various empirical studies that analyzed correlates of punitive attitudes piece by piece.

In response to the paucity of theory in this body of literature, Unnever and Cullen (2009) proposed a “middle-range” theory of individual differences in punitive attitudes. They identify empathy as a key variable and posit a negative relationship between a person’s ability to empathize with offenders and his or her support for punitive punishments. While the survey that is the source of the current data did not include a direct measure of empathetic identification with offenders, it did include several other social belief variables that Unnever and Cullen theorize to be important predictors of empathetic identification. The first is a person’s “attribution of blame” for crime, which captures the degree to which a respondent believes that crime is caused by individual failings (dispositional attribution) or environmental forces (situational attribution). Unnever and Cullen posit a negative relationship between dispositional attribution and empathy but a positive relationship between situational attribution and empathy. Several previous studies show that attribution of blame is a consistent and strong correlate of punitive attitudes (Grasmick & McGill, 1994; Green, Staerkle, & Sears, 2006).

The second antecedent variable is racial beliefs—specifically “symbolic racism” or “racial resentment,” which is a belief that race-based inequalities in society are caused by an inadequate work ethic among minorities rather than structural barriers to social advancement. Numerous studies show that a person’s beliefs about race relations in America are one of the strongest predictors of his or her attitudes about punishment (Hurwitz & Peffley, 2005; Johnson, 2008; Unnever & Cullen, 2010; Unnever, Cullen, & Jonson, 2008). Unnever and Cullen (2009) theorize a negative relationship between symbolic racism and empathy, largely driven by the “racial typification” of crime (Chiricos, Welch, & Gertz, 2004).

The third antecedent variable is political ideology. Unnever, Cullen, and Fisher (2007, p. 313) argued that punitiveness and political conservatism are “two peas in the same pod.” Unnever and Cullen (2009) extend their logic, arguing that conservatives lack empathy for criminals, whom they perceive to choose lawlessness and feel no remorse for the harm they cause to victims. In summary, while this study cannot directly test the relationship between empathetic identification and punitiveness, my models contain other core constructs from Unnever and Cullen’s theory.

A second theory that shapes my analysis is Beckett’s (1997) elite manipulation hypothesis. She argued that American politicians vocalized support for harsh punishment before the public began to be concerned about crime and hold punitive sentiments; in other words, exposure to punitive political rhetoric caused people to espouse punitive opinions. Other scholars posit that news consumption exposes people to elite rhetoric (Zaller, 1992), and research indicates that the news has sensationalized crime stories (Gilliam & Iyengar, 2000) and disseminated the “prisons as country clubs” rhetoric (Welch et al., 2000). Perhaps for these reasons, news consumption is sometimes positively related to fear of crime and punitive attitudes (Chiricos, Padgett, & Gertz, 2000).

While not tied to a single, specific theory, the debate within the literature over whether public opinion about punishment is more influenced by tangible experiences with crime and justice, such as crime victimization or acquaintance with an inmate (Johnson, 2008, 2009; Mancini, Barrick, DiPonio, & Gertz, 2010; Rose & Clear, 2004), or by beliefs and values (Tyler & Boeckmann, 1997) has implications for this study. Given that this study measures people’s perceptions of and attitudes toward the prison environment, it is logical to posit that people with firsthand exposure to a prison and/or vicarious exposure through knowing an inmate may have significantly different perceptions than people without any exposure to prisons, even holding constant their values and news consumption. Indeed, some scholars have found that knowing someone in prison significantly affects a person’s punitive attitudes (Johnson, 2008, 2009) and willingness to use tax money to support corrections programs (Mancini et al., 2010), while others have found that a relationship with an inmate moderates the effect of a person’s beliefs on his or her opinions about social control (Rose & Clear, 2004).

Finally, I control for other variables that scholars who study punitive attitudes have identified as important. Studies show that perceptions of fairness in the criminal justice system predict punitive attitudes and partially explain the differences in overall punitiveness between White and Black Americans (e.g., Hurwitz & Peffley, 2005; Johnson, 2009). Doble found that his participants’ perception that inmates are idle rather than productively engaged in work or education fueled their beliefs that prison life is too easy (Doble, 1987; Doble & Klein, 1989; Doble et al., 1991), so I also control for respondents’ perception of inmate idleness. Frost (2010) notes that measures of fear of crime and personal victimization have generated inconsistent results across the empirical literature, but recent studies increasingly suggest that fear of crime, in particular, is an important predictor of punitive attitudes.

Method

Data

The data for this study come from an original public opinion survey conducted between September 2010 and March 2011. The sampling frame for the study was purchased from the marketing research service InfoUSA, which maintains a regularly updated database of 230 million U.S. households. The frame was comprised of 3,000 addresses randomly sampled from InfoUSA’s database. I designed and pretested the survey questionnaire, and I contracted with the Center for Social Sciences and Public Policy Research at Missouri State University to administer the survey.

I chose a paper, mail-based delivery method. Research indicates that interaction between interviewers and respondents (i.e., in-person and telephone surveys) can generate race-related bias (Krysan, 1998). Given the racialized nature of the crime debate in the United States, as well as evidence that attitudes about race are strong predictors of opinions about criminal justice (Chiricos et al., 2004; Hurwitz & Peffley, 2005), I chose the survey mode that minimizes social desirability bias in questions related to race (Krysan, 1998).

I followed the “tailored design method” advocated by survey methodologists (Dillman, 1991; Dillman, Smyth, & Christian, 2009; Groves et al., 2004). The survey utilized several elements that increase response rates, such as multiple waves of mailings of reminder postcards and replacement questionnaires, envelopes with a university seal and hand-printed addresses, and prepaid return envelopes.

I received a total of 501 usable responses, plus an additional 228 undeliverable packets. The response rate was 18.1% (501/2,772 contacted respondents). The racial distribution of the sample is 76.9% White, 9.8% Black, 1.5% Asian, 1.1% Indian, and 5.5% other. Five percent of respondents identified their ethnicity as Latino. The sample is 39.5% female and 60.5% male. The average age of respondents is 57.2 with a standard deviation of 15.5 years. Just over 50% of respondents are 60 years of age or older. Twenty percent of respondents have a high school diploma or less formal education, 36.7% have some college education or an associate’s degree, 22.7% have a bachelor’s degree, and 20.6% have a graduate or professional degree. About 40% of respondents have a household income of US$50,000 or less, 40.2% have household incomes between US$51,000 and US$110,000, and 20.2% have household incomes greater than US$110,000. The sample includes residents of 48 different states plus the District of Columbia.

While the response rate is low, survey methodologists note that response rates have been declining dramatically in recent years (de Leeuw & de Heer, 2002). Importantly, they also demonstrate that response bias is not a direct function of the response rate because a survey with few respondents could still theoretically possess sample statistics that match the population parameters (Groves, 2006; Groves & Peytcheva, 2008; Keeter, Miller, Kohut, Groves, & Presser, 2000). To assess the external validity of these data, I compare the demographic characteristics of my sample to data from the 2010 census of the U.S. population in Table 1.

Table 1.

Sample Versus 2010 U.S. Census Demographic Comparison.

Characteristic	Survey Data (%)	Census Data (%)
White/Caucasian	76.9	72.4
Black/African American	9.8	12.6
Latino	5.0	16.3
Male	60.5	49.2
Age 18–64	63.3	62.9
Age 65 and older	36.7	13.0
College, graduate, or advance professional degree	43.3	38.2

This comparison shows that my sample is disproportionately non-Latino White, male, educated, and older compared to the population.² It is difficult to assess a priori how these disparities will bias my estimates of people’s opinions because they skew in contradictory directions. Some studies indicate that African Americans oppose punitive punishment more frequently than Whites (Borg, 1998; Chiricos et al., 2004; Unnever & Cullen, 2005), so the overrepresentation of Whites might make my sample more punitive than the population. On the other hand, college-educated respondents are overrepresented, and studies often reveal a negative relationship between education and punitiveness (Chiricos et al., 2004; Green et al., 2006; Unnever & Cullen, 2010). The age and gender disparities in my sample relative to the population are larger in magnitude than race, but past studies find inconsistent relationships between these variables and punitiveness (Borg, 1998; Green et al., 2006; Jacoby & Cullen, 1999). In total, the fact that my sample does not perfectly match the parameters of the population means that it is not nationally representative in the strictest sense of the term. However, the nature of the disparities between the sample statistics and the population parameters does not allow us to clearly predict bias in the opinions under study, and the fact that these data are drawn from a random sample of the national population does give them much higher generalizability than virtually all prior tests of this research question (see Wozniak, 2012, for additional details about the questionnaire, pretest, and evaluation of external validity).

Dependent Variables

Perceptions of life in prison: Three questions measured respondents’ perceptions of life in prison. They shared the same root format, which was “Overall, do you think that life in prison is _____, or is it _____?” Respondents could choose between two contrasting adjectives, which were (a) hard or easy, (b) depressing or enjoyable, and (c) dangerous or safe. The response options were 6-point, bipolar scales. For example, the response option to the first question was “6 = very hard, 5 = moderately hard, 4 = slightly hard, 3 = slightly easy, 2 = moderately easy, 1 = very easy.” Each of these questions measure facets of the “country-club” characterization of prison life (Bidinotto, 1994). I reverse coded these questions so that higher values indicate perceptions that are more consistent with the image of plush prisons (i.e., higher values indicate perceptions of life as easy, enjoyable, and safe), and I combined these 3 items into an additive scale. The correlations among these 3 items are moderate to strong (ranging from 0.46 to 0.64), and the Cronbach’s α of the combined scale is .80.

Prison punitiveness: One question measured respondents’ preferences for harsh prisons, which was “Overall, do you think that the living environment in prisons is too harsh, about right, or not harsh enough for inmates?” This question had a 3-point response scale, where “1 = too harsh, 2 = about right; neither too harsh nor too lenient, 3 = not harsh enough.” I adapted this question from the General Social Survey item that asks respondents whether their local courts deal too harshly, about right, or not harshly enough with criminals. This measure of perceived sentencing severity has been used in past research as a measure of punitive attitudes under the logic that people who say that courts do not sentence harshly enough desire more severe punishment for criminals (Applegate, Cullen, & Fisher, 2002; Cohn, Barkan, & Halteman, 1991; Unnever, Cullen, & Fisher, 2007). So, too, I argue that people who respond that the prison environment is not harsh enough agree with the goals of the no-frills movement to make prisons more austere and uncomfortable for inmates. This measure is also nearly identical to the question asked by Belden Russonello and Stewart (2001).

I recoded the measure so that 1 = not harsh enough and 0 = too harsh or about right. I collapsed the categories because (1) very few respondents stated that the prison environment is “too harsh” (see subsequently), (2) dichotomous measures are easier to interpret than nominal measures, and (3) the theoretical construct of punitive attitudes toward prison policy is best captured in the contrast between “not harsh enough” and the other categories.

Independent Variables

Attribution of blame: Following the work of Unnever, Cochran, Cullen, and Applegate (2010), I construct separate, additive scales for a respondent’s dispositional and situational attributions of blame. I replicated the 7 questionnaire items that operationalize these two variables directly from Unnever et al. (2010). Higher values on these scales indicate stronger agreement with each type of attribution. The Cronbach’s α of the dispositional attribution scale is .47, and the Cronbach’s α of the situational attribution scale is .56.³

Symbolic racism: This variable is comprised of 6 items that I adapted from the American National Election Study and the Los Angeles County Social Survey (see Green et al., 2006; Unnever & Cullen, 2007). It includes statements such as “It’s really a matter of some people not trying hard enough; if Blacks would only try harder they would be just as well off as Whites” and “Generations of slavery and discrimination have created conditions that make it difficult for Blacks to work their way out of the lower class.” Each of these items had a 6-point Likert-type scale to indicate strength of agreement or disagreement. All items were coded in such a manner that higher values on the additive, combined scale indicate stronger agreement with the tenets of symbolic racism. The Cronbach’s α of the scale is .79.

Political ideology: This construct was measured with a single-item, 7-point scale that ranges from extremely liberal (lowest score) through moderate to extremely conservative (highest score).

Exposure to political rhetoric: This survey was part of a larger project designed to test the effect of exposure to political rhetoric on people’s opinions about criminal justice (see Wozniak, 2012). The survey contained an embedded framing experiment in which participants were randomly assigned to one of the three conditions: two elite rhetoric conditions that presented quotes from members of the U.S. House of Representatives discussing crime and punishment, or a control group with no elite rhetoric. The tough on crime condition presented politicians endorsing harsh punishment and rejecting rehabilitation. This condition included a quote from Representative Cliff Stearns supporting the 1994 Violent Crime Control and Law Enforcement Act, a bill that he said “will also abolish country club comforts for prison inmates. No more video games, no more pool tables. Just a requirement to work.” In contrast, the smart on crime condition presented politicians rejecting a “lock ‘em up and throw away the key” approach. This condition included a quote from Representative Jim Clyburn supporting the 2007 Second Chance Act, saying “As a former judge, I know well that we have got to do a better job of rehabilitating, of educating, with drug treatment and alcohol treatment for those that are incarcerated in our prisons.” Both quotes relate to life in prison, so both may influence the attitudes currently under study.

News consumption: This variable is an additive scale that measures the number of days during a typical week that the respondent consumes the news via TV, radio, Internet, and/or newspaper; higher values on this scale indicate a greater volume of news consumed from a greater variety of sources.

Fear of crime: A single-item variable measures this construct with a respondent’s answer to the question, “Within the past six months, have you ever felt afraid that you would become the victim of a crime?” The response options were yes (coded 1) or no (coded 0).

Victimization: Another single-item variable measures whether or not the respondent was the victim of a crime with the question, “Have you ever been the victim of a serious crime? This would include such things as someone breaking into your home, having your car stolen, or being physically assaulted or robbed.” This item had the same dichotomous response options as the fear of crime question.

Prison entry: Respondents answered yes (1) or no (0) to the question, “Have you ever been inside a prison beyond the visitor’s area (i.e., have you seen the cell blocks, the dining hall, etc.)?”

Prisoner relationship: This variable measures the number of current or former inmates who are personally known by the respondent. Respondents could indicate that they had a significant other, family member, friend, and/or acquaintance presently or formerly incarcerated. Respondents received a point for each category, resulting in a 0–4 scale that assesses the number of different types of relations with a prison record the respondent possesses (if any).

Perception of inmate idleness: A single question asked the respondents, “How do you think that most prisoners actually spend their time? Do you think that most prisoners spend their time being idle and lazy, or do you think that most prisoners spend their time being productively engaged in prison jobs or educational classes?” Similar to the perceptions of life in prison questions, this question had a 6-point, bipolar response scale ranging from very idle to very productive, which I coded so that higher values indicate a stronger belief that inmates are idle and lazy.

Perception of fairness in the criminal justice system: This variable combines 3 items that measure a respondent’s level of agreement or disagreement with statements that the criminal justice system is fair regardless of race, the death penalty is applied fairly regardless of race, and a Black person is likely to receive a harsher sentence than a White person who committed the same crime (the last item is reverse coded). The Cronbach’s α of the additive scale is .78.

Control Variables

I control for a variety of demographic characteristics in order to partially address the response disparities between the sample and the population. Dummy variables contrast the opinions of Democrats and Independents against those of Republicans (the omitted category). Dummy variables identify African Americans (1 = Black, 0 = all other races) and women. Age is a continuous variable. Education and household income are each ordinal variables coded so that higher scores indicate higher levels of educational achievement and income. Finally, dummy variables identify respondents who live in states in the northeast, central, and west regions of the country, contrasted to those who live in the south (the omitted category); I use the U.S. Census categorization of regions.

Table 2 presents the descriptive statistics of the variables, as well as the sign of the expected relationship between each predictor variable and the dependent variables based upon theory and previous research. Positive signs indicate that a variable is hypothesized to make a respondent more likely to describe prisons as easy, enjoyable, and/or safe and more likely to say that the prison environment is “not harsh enough,” whereas negative signs indicate that a variable is hypothesized to have the opposite effect.

Table 2.

Descriptive Statistics.

Variable	Hypothesized Effect	N	M	SD	Minimum	Maximum
Perceptions of prison	NA	487	8.74	3.78	3	18
Prison punitiveness	NA	481	0.47	0.50	0	1
Dispositional attribution	+	488	11.30	3.41	3	18
Situational attribution	−	485	16.57	3.81	4	24
Symbolic racism	+	471	21.32	6.88	6	36
Political ideology	+	474	4.35	1.42	1	7
Tough on crime rhetoric	+	501	0.35	0.48	0	1
Smart on crime rhetoric	−	501	0.31	0.46	0	1
News consumption	+	478	15.56	5.63	1	28
Fear of crime	+	483	0.18	0.39	0	1
Victimization	+	486	0.36	0.48	0	1
Prison entry	−	485	0.24	0.42	0	1
Prisoner relationship	−	492	0.73	0.73	0	3
Perceived fairness of CJS	+	480	10.87	4.37	3	18
Perception of inmate idleness	+	494	3.89	1.39	1	6
Democrat	−	482	0.35	0.48	0	1
Independent	−	482	0.27	0.45	0	1
Republican	(Omitted)	482	0.37	0.49	0	1
African American	−	459	0.10	0.30	0	1
Female	−	486	0.40	0.49	0	1
Age	?	474	57.16	15.47	21	89
Education	−	480	4.04	1.48	1	6
Income	+	460	3.28	1.69	1	8
Northeast	−	501	0.23	0.42	0	1
Central	−	501	0.24	0.43	0	1
West	−	501	0.18	0.38	0	1
South	(Omitted)	501	0.35	0.48	0	1

Note. CJS = criminal justice system; SD = standard deviation.

Plan of Analysis

I begin by presenting the descriptive statistics of respondents’ answers to the dependent variable questions, the perception of inmate idleness item, and the exposure to prison or prisoners items. I proceed with multivariate regressions to analyze the factors that shape people’s perceptions of prisons. Given that the perception of life in prison scale is functionally continuous (with values ranging from 3 to 18), I analyze this dependent variable with ordinary least squares (OLS). Because dichotomous variables violate the underlying assumptions of OLS, I analyze the prison punitiveness variable with logit maximum likelihood estimation (Long, 1997).

Variance inflation factors scores revealed no evidence of problematic multicollinearity in any model. I conducted all analyses with Stata.

Results

Descriptive Statistics

Given the nation’s high incarceration rate, it is perhaps unsurprising that 57.9% of respondents personally know at least one person who is currently or was previously imprisoned; this finding suggests that a majority of Americans are now touched by mass incarceration (see also Rose & Clear, 2004). Among these respondents, 1.6% have a significant other who is or was incarcerated, 24.8% have a family member, 19.9% have a friend, and 26.6% have an acquaintance (these categories are not mutually exclusive). Despite the prevalence of relationships with inmates among this sample, only 23.5% of respondents report that they have ever been inside a prison beyond the visitor’s area to experience the inmates’ living quarters firsthand.

Table 3 presents the distribution of respondents’ answers to the questions about their perceptions of life in prison and inmates’ activity. A majority of respondents in this sample perceive life in prison to be hard (54.2%), depressing (67.5%), and dangerous (78.8%) to varying degrees. A majority of respondents also believe that most inmates are idle most of the time (55.3%), although the modal response to this question was “slightly productive” (28.7%). These responses suggest that most citizens recognize the “pains of imprisonment” inherent in prison life (Johnson, 2002).

Table 3.

Distribution of Respondents' Perceptions of Life in Prison.

Overall, do you think that life in prison is…
Very	Moderately	Slightly	Slightly	Moderately	Very
Hard	Hard	Hard	Easy	Easy	Easy
66 (13.4%)	101 (20.5%)	100 (20.3%)	77 (15.7%)	94 (19.1%)	54 (11.0%)
Very	Moderately	Slightly	Slightly	Moderately	Very
Depressing	Depressing	Depressing	Enjoyable	Enjoyable	Enjoyable
129 (26.3%)	103 (21.0%)	99 (20.2%)	70 (14.3%)	65 (13.2%)	25 (5.1%)
Very	Moderately	Slightly	Slightly	Moderately	Very
Dangerous	Dangerous	Dangerous	Safe	Safe	Safe
122 (24.7%)	159 (32.1%)	109 (22.0%)	35 (7.1%)	54 (11%)	16 (3.2%)
How do you think that most prisoners actually spend their time? Do you think that most prisoners spend their time being idle and lazy, or do you think that most prisoners spend their time being productively engaged in prison jobs or educational classes?
Very	Moderately	Slightly	Slightly	Moderately	Very
Idle	Idle	Idle	Productive	Productive	Productive
70 (14.2%)	124 (25.1%)	79 (16.0%)	142 (28.7%)	61 (12.4%)	18 (3.6%)

Note. Row percentage in parentheses.

On the other hand, 46.6% of respondents believe that the living environment in prisons is not harsh enough, 41.6% believe that it is neither too harsh nor too lenient, and only 11.9% believe that it is too harsh. This finding suggests that a plurality of Americans across the country desire prisons to be more austere, just as Belden Russonello and Stewart (2001) found over 10 years ago. Even though a majority of respondents perceive prisons to be at least slightly hard, depressing, and dangerous places, a plurality of respondents still wish them to be made even harsher.

Multivariate Analyses

Table 4 presents the results of an OLS regression analysis of the life in prison scale. Respondents who more strongly agree with a situational attribution of blame, more strongly perceive that inmates spend their time idly, personally know inmates, are more educated, or identify as Independents also more strongly believe that prisons are hard, depressing, and/or dangers places to live. In contrast, African American respondents more strongly believe that prisons are easy, enjoyable, and/or safe. Note, though, that the effects of race and education are only marginally significant.

Table 4.

Results of OLS Regression of Perceptions of Life in Prison Scale on Personal Values, Experiences With Crime and/or Corrections, and Elite Manipulation Variables.

Variables	b	β
Personal beliefs and values
Dispositional attribution of blame	.02 (.06)	.02
Situational attribution of blame	− .26 (.05)***	−.26
Symbolic racism	.07 (.05)	.13
Perceived fairness of CJS	.03 (.06)	.04
Political ideology (liberal to conservative)	.14 (.17)	.05
Experience with crime and corrections
Fear of crime	.41 (.44)	.04
Victimization	− .58 (.38)	−.07
Prison entry	.51 (.45)	.06
Prisoner relationship	− .60 (.27)*	−.12
Perception of inmate idleness	− .58 (.14)***	−.21
Elite manipulation
News consumption	.004 (.03)	.06
Tough on crime rhetoric	− .44 (.44)	−.05
Smart on crime rhetoric	.47 (.42)	.06
Control variables
Democrat	.17 (.52)	.02
Independent	− 1.17 (.52)**	.02
African American	1.23 (.73)^†	.10
Female	− .47 (.39)	−.06
Age	− .02 (.01)	−.08
Education	− .24 (.14)^†	−.10
Household income	.16 (.12)	.07
Northeast	− .71 (.46)	−.08
Central	− .58 (.48)	−.07
West	− .10 (.54)	−.01
Constant	15.06 (1.87)
N	369
Adjusted R ²	.22

Note. OLS = ordinary least squares; CJS = criminal justice system.

Unstandardized and standardized coefficients with robust standard errors in parentheses.

*p ≤ .05. **p ≤ .01. ***p ≤ .001. ^† p ≤ .10.

Table 5 presents the results of a logit regression analysis of the prison punitiveness question. Individuals who more strongly agree with the tenets of dispositional attribution and symbolic racism are more likely to believe that prisons are not harsh enough, while individuals who more strongly endorse situational attribution are less likely to hold a punitive preference for prison life. Respondents who perceive that life in prison is easy, enjoyable, and/or safe are also more likely to believe that the prison environment is not harsh enough. Similarly, people who know inmates and perceive inmates to spend their time idly are also more likely to believe that prisons are not harsh enough, though these effects only reach marginal statistical significance. None of the measures of exposure to elite rhetoric significantly affected respondent’s preferences for the prison environment. Education and household income both exerted significant, positive effects on punitiveness. African American respondents were also more likely to state that the prison environment is not harsh enough; indeed, the odds ratio indicates that effect of being Black on one’s preference for the nature of life in prison is substantively the largest in magnitude.

Table 5.

Results of Logit Regression of Prison Punitiveness on Personal Values, Experiences With Crime and/or Corrections, and Elite Manipulation Variables.

Variables	Odds Ratio
Personal beliefs and values
Dispositional attribution of blame	1.10 (.04)*
Situational attribution of blame	.92 (04)*
Symbolic racism	1.07 (.03)*
Perceived fairness of CJS	.98 (.04)
Political ideology (liberal to conservative)	1.23 (.13)
Experience with crime and corrections
Fear of crime	.71 (.32)
Victimization	1.30 (.26)
Prison entry	1.21 (.30)
Prisoner relationship	1.41 (.20)^†
Perception of inmate idleness	1.18 (.10)^†
Perception of life in prison	1.23 (.04)***
Elite manipulation
News consumption	.98 (.02)
Tough on crime rhetoric	.74 (.33)
Smart on crime rhetoric	.76 (.30)
Control variables
Democrat	.81 (.42)
Independent	1.35 (.33)
African American	2.86 (.52)*
Female	1.44 (.30)
Age	1.00 (.01)
Education	1.18 (.10)^†
Household income	1.26 (.09)*
Northeast	.75 (.34)
Central	1.02 (.33)
West	.83 (.38)
Log pseudo likelihood	− 196.33
N	362
Adjusted count R ²	.39

Note. CJS = criminal justice system.

Odds ratios with robust standard errors in parentheses.

*p ≤ .05. **p ≤ .01. ***p ≤ .001. ^† p ≤ .10.

These findings indicate that both personal beliefs and perceptions and vicarious experience with criminal justice shape people’s perceptions of prisons and their preferences about the quality of life in prisons, but elite manipulation does not affect said perceptions and preferences.

Discussion

It was my goal in this article to (1) determine whether or not a majority of Americans across the country believe that our nation’s prisons are “like resorts” and (2) analyze the correlates of people’s opinions about prisons. The present findings replicate Belden and Stewart (2001), which suggests that a plurality of Americans do believe that the environments in our prisons are insufficiently harsh. These opinions appear quite stable; I found nearly the same distribution of answers among “too harsh” (11.9%), “about right” (41.6%) and “not harsh enough” (46.6%) as did the survey researchers at Belden Rusonnello and Stewart Research and Communications ten years ago (10%, 35%, and 42%, respectively). This study suggests that the strong condemnation of leisure time and “creature comforts” in prisons voiced by focus group participants may be a mainstream rather than fringe opinion in the United States.

The findings of this study also contribute to our theoretical understanding of American public opinion about punishment. Many of the variables in the multivariate analyses generated results that are consistent with previous research and Unnever and Cullen’s (2009) theory of empathetic identification. Belief in a dispositional cause of criminality and minority disadvantage (i.e., symbolic racism) increased the likelihood that people perceive prisons to be insufficiently harsh, while belief in a situational cause of criminality increased the likelihood that people perceive prisons to be overly harsh. Numerous other studies find the same relationships between dispositional attribution, situational attribution, symbolic racism, and punitive opinions about other forms of punishment, such as the death penalty and sentencing. This congruence supports Unnever and Cullen’s work to craft a general theory of the predictors of punitive attitudes about punishment. Unfortunately, the present data did not include a measure of empathetic identification with offenders, which means that I could not test the central component of their theory. Still, the fact that the hypothesized antecedents of empathy generated results consistent with their model indicates that scholars who study punitive attitudes should continue to test Unnever and Cullen’s theory with new data.

In contrast, none of the variables that measure exposure to elite rhetoric were significant. In regard to the one issue of public opinion about prisons, I find no support for the hypothesis that people’s opinions are shaped by the things politicians say about punishment (Beckett, 1997). It is possible that “elite manipulation” may affect public opinion about other facets of the criminal justice system.

The findings of this study also contribute to the debate about the relative importance of personal beliefs and values versus perceptions and experience with crime and punishment on people’s opinions about criminal justice. While this study affirms the central importance of personal beliefs as predictors of punitiveness (attribution of blame and symbolic racism), it did also find significant effects from variables that capture a respondent’s exposure to the criminal justice system. The variables that measured whether or not the respondent knows someone with a prison record, as well as the respondent’s perception about inmates’ idleness, significantly predicted both respondents’ perceptions of the prison environment and their punitive attitude toward said environment.⁴ Many scholars have concluded that “instrumental” measures of people’s direct or indirect experiences with crime and the justice system do not shape people’s punitive attitudes once their beliefs are taken into account. However, the only instrumental variables tested in most previous studies were fear of crime and victimization, neither of which were significant in the present analyses, either. However, perhaps scholars have overlooked a significant relationship between instrumental experiences with crime and justice and punitive attitudes because they have not included a broad enough variety of instrumental measures. If so, then our theory should identify both “classes” of variables as predictors of opinion about punishment, and scholars should further explore the relative contribution of each to punitive attitudes.

Another notable finding is that African American respondents in this sample were significantly more likely than White respondents to state that the prison environment is not harsh enough, controlling for their belief in the racial fairness of the criminal justice system. Though this finding may seem surprising given that Blacks are disproportionately incarcerated in our nation’s prisons, it is actually consistent with previous evidence that African American offenders perceive prison to be a less punitive punishment than alternatives like probation or electronic monitoring (Applegate, 2014; Wood & May, 2003). Other scholars found that African American interviewees expressed the opinion that prisons do not make offenders “suffer enough” for their crimes (Gaubatz, 1995; Sasson, 1995), which suggests the existence of punitive backlash among law-abiding Blacks against Black offenders who are comparatively unintimidated by the prospect of a prison sentence.⁵

Implications for Politics and Policy

The findings of this article should raise a red flag for corrections professionals and criminal justice reformers. Wardens and correctional officers value amenities and leisure time for inmates as tools to maintain order within prisons (DeWine, 1997; Finn, 1996; Johnson et al., 1997; Tewksbury & Mustaine, 2005), yet it is these same “luxuries” that likely feed into the public perception that life in prison is insufficiently harsh. Given that Belden Russonello and Stewart (2001) and I both find that a plurality of respondents from across the country voice the opinion that prisons are not harsh enough, it appears that politicians correctly perceived that a significant number of Americans resent “country-club” conditions in prisons.

During the height of the “no-frills” movement, legislators’ desire to appeal to their constituents’ punitive sentiments led them to craft policies that stripped prisons of funding for amenities and programming. In other words, the common public belief that prisons are insufficiently harsh places for inmates to live was translated by politicians into zero-sum policy that deprived corrections professionals (and inmates themselves) of the amenities and tools that they valued to do their jobs in order to curry favor with constituents who probably had minimal contact with the prison system. This was a policy loss for the professionals who actually staff our nation’s prisons.

The fact that the public perception that prisons are not harsh enough endures over time creates a political problem for corrections professionals. The United States is presently experiencing an unprecedented level of criminal justice policy reform as states across the country are working to curb corrections costs and reduce their prison population (e.g., Porter, 2013), which might suggest that this is an ideal time for interested reformers to push for legislation to improve conditions in prisons. However, if we view the present findings in light of Arnold’s (1990) theory of legislator decision making, we can see that the policy preferences of corrections professionals and reformers will always be at a disadvantage in the legislative arena. Arnold argues that legislators are profoundly cautious creatures; they consider not only the policy preferences of their constituents in regard to visible, salient issues, but also all potential issues that might arise and become (negatively) salient to voters. Politicians are hesitant to support policy proposals that might become distasteful to voters if an electoral challenger or the media brings that policy to the public’s attention. The fact that public antipathy toward “insufficiently harsh conditions” in prison endures over time means that politicians will always be more inclined to support “no-frills” legislation over legislation designed to improve prison conditions because legislators will fear that supporting the latter type of legislation could make them vulnerable to being characterized as “procriminal” or “soft on crime.”

This political reality will make it more difficult for criminal justice reformers and corrections professionals to see their preferences enacted into policy even though corrections professionals bear the responsibility of running our nation’s prison systems. Ultimately, then, prisons have a public relations problem. The best way for reformers and corrections professionals to overcome this disadvantage is to educate the public about the benefits and practical value of amenities, programs, and humane living conditions. Research tells us that most people want prisons to rehabilitate inmates (Cullen et al., 2000; Cullen et al., 2002; Flanagan & Caulfield, 1984; Roberts & Hough, 2005). Corrections professionals and reformers should work to show citizens that inmates are best able to rehabilitate themselves when they live in a humane environment with resources at their disposal. The more that reformers can reduce the percentage of people who say that prisons are not harsh enough, the less likely it will be that no-frills policies will make their way back onto legislative agendas in the future.

Limitations

The most notable limitation of this study is the low response rate and the fact that the sample is disproportionately non-Latino White, male, educated, and older compared to the U.S. population. As such, these data are not nationally representative of the population in the strictest sense of the term, and I do not claim that this study possesses perfect generalizability. On the other hand, I do argue that these findings are comparatively more generalizable than the findings of previous studies of the same research question; whereas almost all past studies that measured public opinion about the prison environment and/or support for amenities used either nonprobability samples (Applegate, 2001; Beckett & Sasson, 2004; Cook & Powell, 2003; Doble, 1987; Doble & Klein, 1989; Doble et al., 1991; Gaubatz, 1995; Sasson, 1995) or samples of a single state (Bryant & Morris, 1998; Lenz, 2002), these data come from a probability sample drawn from a national level sampling frame, and respondents from 48 different states participated in this survey. I also believe that the close similarity between the present findings and those of Belden Russonello and Stewart (2001), the only other national level probability sample in this literature, suggests that this study possesses a nonnegligible degree of external validity.

I also acknowledge that several of the measures in this study are blunt instruments. For example, the dependent variables do not directly ask respondents if they perceive country clubs to be like resorts; rather, I rely upon the inference that a respondent who states that the prison environment is “not harsh enough” would agree with pundits’ and politicians’ characterization of prisons as overly plush. More importantly, the dependent variables in this study do not ask respondents to distinguish their preferences for the incarceration of violent versus nonviolent convicts, a distinction that typically has important implications for the measurement of punitive opinions (Cullen et al., 2000). Nor do the dependent variables ask the respondents to distinguish between different types of prisons, or prisons in different areas; it is quite plausible to imagine a sophisticated respondent saying, “Well, some prisons are dangerous, but others are safe. It depends.”

I view these measurement limitations as part and parcel of a quantitative design that employs close-ended questions. I sacrifice nuance and depth in order to be able to compare and contrast precise responses across participants. As such, I encourage the reader to view this study as complementary to the many fine qualitative studies that provide elaborate, detailed descriptions of people’s thoughts about prisons in particular and punishment in general (Beckett & Sasson, 2004; Cook & Powell, 2003; Doble, 1987; Doble & Klein, 1989; Doble et al., 1991; Gaubatz, 1995; Sasson, 1995). It is also important that other scholars seek to replicate the findings of this study in future surveys of the U.S. population (hopefully with a higher response rate). In particular, I believe that the study of American public opinion about prisons would most benefit from a survey that oversamples African Americans and Hispanics so that we would have sufficiently robust data to perform race-disaggregated analyses; most of our knowledge about minority perceptions of the severity of imprisonment comes from samples of offenders, not the general public (e.g., Applegate, 2014; Wood & May, 2003).

Conclusion

Analyzing data from a public opinion survey drawn from a national sample of the U.S. population, I find that a plurality of respondents both perceive life in prison to be unpleasant and voice the opinion that life in prison should be harsher still. These findings suggest that people across the nation resent “country-club” conditions in prisons. Furthermore, even in a sample that overrepresents older, White men (a population with a relatively low risk of imprisonment), nearly 60% of respondents report that they know someone who is or was previously imprisoned, which shows just how widely mass incarceration has permeated American society.

Public antipathy toward prisons sparked conflict between politicians and corrections officers in the past over how the institutions should be run, and the stability of this opinion over time leaves the door open for the specter of the no-frills movement to rise again. Corrections professionals and criminal justice reformers should take note and work to better communicate their perspective on living conditions, amenities, and prison programs to the public.

Footnotes

Acknowledgments

I would like to thank Joanne Savage, Robert Johnson, Jie Liu, and Devon Johnson for their advice regarding the design of the survey instrument; Brian Calfano and the staff of the Center for Social Sciences and Public Policy Research at Missouri State University for administering the survey; and American University for providing the grants to fund data collection.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author disclosed receipt of the following financial support for the research and/or authorship of this article: The American University provided the grants to fund data collection.

Notes

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