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Punitive Attitudes Toward Criminals: Exploring the Relevance of Crime Salience and Economic Insecurity

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This article examines whether and in what ways punitive attitudes toward criminals can be understood as having roots in two hypothesized sources of anxiety in western society. The first is the danger of crime and its salience and the second is economic insecurity. Both have been seen as sources of growing perceptions that the State is failing in its responsibility to provide for citizen's physical safety and economic security. Punitiveness toward criminals is hypothesized by some to be a way to act decisively in a time of relative uncertainty. It also serves to distinguish between the `undeserving poor' and those who are economically insecure. Interviews with 2250 randomly selected Florida residents provide the data for this study. Our results indicate that crime salience, especially fear and concern about crime consistently predict punitiveness. When economic insecurity is measured in terms of expected circumstances in the near future, it is significantly linked to punitive attitudes among white males, particularly those who are less well educated and earn less income. The results are consistent with some aspects of an `angry white male' phenomenon, particularly to the extent that those negative sentiments have a racial focus.
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Punishment & Society
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DOI: 10.1177/1462474508098131
2009 11: 25Punishment & Society
Michael T. Costelloe, Ted Chiricos and Marc Gertz
salience and economic insecurity
Punitive attitudes toward criminals : Exploring the relevance of crime
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Punitive attitudes
toward criminals
Exploring the relevance of crime salience
and economic insecurity
MICHAEL T. COSTELLOE, TED CHIRICOS AND MARC GERTZ
Northern Arizona University, Florida State University and Florida State University, USA
Abstract
This article examines whether and in what ways punitive attitudes toward criminals
can be understood as having roots in two hypothesized sources of anxiety in western
society. The first is the danger of crime and its salience and the second is economic
insecurity. Both have been seen as sources of growing perceptions that the State is failing
in its responsibility to provide for citizens physical safety and economic security. Puni-
tiveness toward criminals is hypothesized by some to be a way to act decisively in a
time of relative uncertainty. It also serves to distinguish between the ‘undeserving poor’
and those who are economically insecure. Interviews with 2250 randomly selected
Florida residents provide the data for this study. Our results indicate that crime salience,
especially fear and concern about crime consistently predict punitiveness. When
economic insecurity is measured in terms of expected circumstances in the near future,
it is significantly linked to punitive attitudes among white males, particularly those
who are less well educated and earn less income. The results are consistent with some
aspects of an ‘angry white male’ phenomenon, particularly to the extent that those
negative sentiments have a racial focus.
Key Words
crime salience • economic insecurity • punitive attitudes
CRIME SALIENCE, ECONOMIC INSECURITY AND SUPPORT FOR
PUNITIVE POLICIES
It is well documented that in recent decades, criminal justice policy in the United States
has taken an extraordinary and unprecedented turn toward punitiveness (Beckett and
Sasson, 2000; Austin and Irwin, 2001; Garland, 2001; Whitman, 2003). One indi-
cator of this is seen in mushrooming rates of incarceration. Between 1980 and 2006,
25
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the number of inmates held in state and federal prisons rose 77 percent – from 275 to
501 per 100,000 of the population. Adding jail inmates raised the national rate of
incarceration to 738 per 100,000. By the end 2006, 1 of every 39 US residents was in
prison or jail or on probation or parole (US Department of Justice, 2007).
But incarceration statistics cannot capture the full dimensions of this surge in puni-
tiveness toward criminals. Indeed, the range of punitive initiatives is seemingly limited
only by legislative imagination. It is illustrated by such things as the proliferation of
mandatory minimum sentencing structures like ‘three-strikes’ and ‘10–20–Life’, the
increased use of juvenile waivers to adult court, the renewed use of the death penalty,
the implementation of draconian drug laws, the use of various public shaming
activities, forced labor at the rock pile and the reintroduction of chain gangs among
other measures.
There is some evidence that the expansion of punitive policies clearly resonates with
popular attitudes about crime and punishment (Flanagan and Longmire, 1996; Cullen
et al., 2000; Roberts et al., 2003). It is not certain whether public opinion in this area
is more influenced by policy than is policy by public opinion and they may, in fact, be
mutually determining. But it has been argued that a kind of ‘penal populism’ has come
to characterize the culture of punishment in the United States, an important component
of which is the close correlation of punitive policy and popular attitudes (Roberts et al.,
2003). Even with the extraordinary run-up in criminal punishment, 65 percent of
Americans in 2006 still believed the courts in their communities are not harsh enough
in dealing with criminals (Roper Center for Public Opinion Research, 2008, 2008).
The possible antecedents of popular support for punitive policies are many and have
been well summarized elsewhere (Cullen et al., 2000). Several recent observers have
called particular attention to two issues that are the focus of the present research. These
are the salience of crime and ‘diffuse anxieties’ engendered by social and particularly
economic change (Garland, 2001; Roberts et al., 2003). The argument is made that
even with crime rates declining, the salience of crime has actually increased because
more people are ‘exposed’ to it by intense media attention and the recurring emphasis
on crime by political candidates. Garland (2001: 147) refers to this as a growing
collective cultural experience’ of crime. So-called globalization, downsizing and
outsourcing have become a staple of economic life in the United States, and have been
well documented (e.g. Stiglitz, 2002). The attendant insecurities of these and other
economic changes have also been well documented (e.g. New York Times, 1996).
Garland (2001: 133) succinctly blends the two issues into the core of his thesis for
why policy and popular attitudes about crime have become significantly more punitive:
Such policies become particularly salient where a more general insecurity – deriving from the
precariousness of social and economic relations in late modern society – is widely experienced
and the state is deemed to have failed in its efforts to deliver physical and economic security.
The hypothesized consequence is that harsh policies toward crime provide such senti-
ments with a ‘ready made, deeply unpopular target population’ – criminals – against
whom these sentiments can be directed (Garland, 2001: 133).
The present research tests that portion of Garlands thesis that relates to popular
sentiments. To do this, we make use of survey data from a state-wide random sample
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(N = 2250) of Florida residents. We are specifically concerned with the extent to which
support for punitive measures toward criminals may be explained by several indicators
of crime salience and economic insecurity. In addition, we assess whether these relation-
ships may be demographically concentrated in ways that support an ‘angry white male’
thesis. Finally, we explore the possible interaction of objective indicators of economic
vulnerability with expressed perceptions of insecurity in predicting punitiveness.
CRIME SALIENCE AND ECONOMIC INSECURITY:
THEORETICAL ISSUES
The rationale for expecting crime salience to help sponsor punitive attitudes is straight-
forward. People for whom crime is a more problematic issue might be reasonably
expected to endorse tougher measures to deal with it. What may be less straightforward,
is the rationale for why crime salience would remain high – and it clearly has – even as
crime rates in the United States have trended downward since 1991. One measure of
that salience is found in Gallup Poll responses to the question of whether crime in this
country is going up or not. While 89 percent of respondents thought crime was still
increasing in 1992, a majority (52%) thought it was rising as late as 1998 – after seven
years of decreasing crime rates. The belief that crime was increasing bottomed out at
43 percent in 2001, but rose again to 60 percent in 2003 (Gallup Survey, 2004).
What keeps crime salience high, in the face of falling crime rates? Garland argues
that it is primarily three things (see Roberts et al., 2003 for a similar argument). The
first is the extraordinary rise in crime rates (468%) from 1960 to 1980, after which
‘high rates of crime have become a normal social fact – a routine part of modern
consciousness’ (Garland, 2001: 147). The second involves the role of television in re-
inforcing public knowledge of and ‘collective representations’ of crime. In Garland’s
view, which is shared by many others (e.g. Surrette, 1992; Barak, 1994; Chiricos and
Eschholz, 2002) television provides ‘selective coverage of factual crime stories’ and ‘un-
realistic crime dramas’ which ‘tend to distort public perceptions of the problem
(Garland, 2001: 158). Third is the relentless use of crime as a political lever by poli-
ticians of all stripes, who readily exploit ‘the TV encounter – with its soundbite rapidity,
its emotional intensity and its mass audience’ in the pursuit of electoral advantage
(Garland, 2001: 157). The result of these factors is that ‘a collectively raised conscious-
ness of crime’ has become gradually institutionalized with a sustaining consequence for
crime salience (Garland, 2001: 163).
Economic insecurity has direct roots in the profound changes that have character-
ized the market for labor in the past 30 years. Starting with deindustrialization
(Bluestone and Harrison, 1982) the continued ‘outsourcing’ of jobs to foreign
economies and the relentless ‘globalization’ of the market for labor (Stiglitz, 2002) has
exerted strong downward pressure on wages, benefits and pensions (Wallulis, 1998;
Mishel et al., 2005). In constant dollars, the average weekly earnings for private sector,
non-supervisory workers declined by 22 percent from 1973 to 1995, though rebound-
ing slightly (7%) since then (Council of Economic Advisors, 2004). It so happens that
during this period, white males with less than a high school education experienced a
sharper decline in economic well-being than any other demographic group (New York
Times, 1996; Mishel et al., 2005).
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One result of these objective changes has been a marked increase in economic
insecurity and anxiety among both blue collar and white collar workers in the United
States. That anxiety has been well captured in public opinion surveys. For example, a
New York Times survey reported that 65 percent of respondents made ‘cutbacks in day
to day spending’ as a result of ‘uncertainty and insecurity’ about their economic future
and 78 percent report being ‘worried’ about their financial security in retirement (New
York Times, 1996: 293). A Washington Post survey found that 86 percent of respondents
had family incomes that were ‘falling behind’ or at best ‘staying even’ with the cost of
living, and most of those expected the same to be true in coming years (Washington Post
et al., 1996: 5–6).
The potential for a link between economic insecurity and punitiveness toward
criminals has been widely recognized (Melossi, 1993; Gans, 1995; Chancer and
Donovan, 1996; Greenberg, 1999; Garland, 2001). In this regard, Garland (2001: 148)
has noted that ‘shifts in the economic and social position of large sections of the middle
and working classes’ have led to support for ‘more aggressive controls for an “underclass
that was perceived to be disorderly, drug-prone and dangerous’. The precise rationale for
such a relationship has been variably described. For example, Greenberg (1999: 334)
suggests that the punishment of others, including criminals, may provide ‘compensatory
satisfaction’ for some who have difficulty ‘being validated by their occupational successes’.
The New York Times (1996: 24) has suggested that job insecurity has created ‘a floating
anger that is attaching itself to all sorts of targets as a form of scapegoating’. A similar
theme is struck by Chancer and Donovan (1996: 52) who note that criminals provide
‘relatively concrete targets of blame to be identified’ and provide a ready opportunity for
the channeling of anxious insecurities into rage’. The particularity of criminals as targets
of punitive attitudes may also serve, as Gans (1995: 7) suggests, to sharpen the moral
and social distinction between those who are economically insecure and those who may
be considered as representative of the ‘undeserving poor’.
Because white males with low educational achievement experienced the sharpest
economic decline during recent decades, there has been considerable attention paid to
the emergence of an ‘angry white male’ phenomenon. Much of the ‘anger’ associated
with this emergence has been directed toward the presumed beneficiaries of affirmative
action – minorities and women (Pollitt, 1995; Winant, 1995) – as well as immigrants
(Stengel and Bonfante, 1995; Wartzman, 1995). However, the resentment against those
who may be perceived as ‘getting something for nothing’ (Schor, 1991; Sidel, 1996)
could understandably be expanded to include criminals as well. This potential con-
fluence of resentments has been recognized by a number of scholars (Sidel, 1996;
Greenberg, 1999; Garland, 2001).
In light of the foregoing considerations, the present research addresses the following
research questions. Are punitive attitudes stronger among those for whom crime has a
greater salience? Are punitive attitudes stronger for those who express a greater insecurity
about their economic circumstances? Is there any evidence of an ‘angry white male
phenomenon in the constellation of punitive attitudes? Are expressed insecurities more
strongly linked to punitive attitudes for those whose objective circumstances may be
objectively less secure?
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PRIOR RESEARCH: CRIME SALIENCE AND PUNITIVENESS
Crime salience has been operationalized in punitive attitude research in several ways.
These include the fear of crime, victimization experience, vulnerability to crime and a
general concern about crime as a social problem. Concerning fear, early research in this
area generally found a positive link between fear of crime and punitiveness although
the effect was small (Taylor et al., 1979; Stinchcombe et al., 1980). More recent studies
have shown a somewhat stronger relationship of punitiveness to fear (Langworthy and
Whitehead, 1986; Schwartz et al., 1993; Applegate et al., 2000). Hogan et al. (2005)
found that fear was unrelated to punitiveness for white respondents, but strongly
predicted punitiveness for others. Cohn et al. (1991) similarly found that fear of crime
significantly influenced punitiveness for black respondents, but not for whites. The
present research disaggregates our sample by race, sex and other demographic charac-
teristics to assess the variable nature of the possible link between several crime salience
measures and punitiveness.
It would be reasonable to hypothesize that those who have been victimized by crime
would express more punitive sentiments. Surprisingly, the research bearing on this issue
has consistently failed to find a significant direct relationship between prior criminal
victimization and punitiveness (Blumstein and Cohen, 1980; Stinchcombe et al., 1980;
Cullen et al., 1985; Langworthy and Whitehead, 1986; Rossi and Berk, 1997;
Applegate et al., 2000). In addition to actual victimization experiences, researchers have
assessed the relevance of vicarious victimization by asking whether respondents had a
neighbor who was recently victimized (Langworthy and Whitehead, 1986; Durham et
al., 1996). While no direct effect of vicarious victimization on punitiveness was found,
Langworthy and Whitehead (1986) report indirect effects through fear for both
vicarious and actual victimization.
The ‘vulnerability hypothesis’ (Langworthy and Whitehead, 1986: 578) suggests
that those who are more vulnerable to criminal victimization, regardless of whether
they have actually ever been victimized, may be more punitive than those less vulner-
able. From this perspective, older respondents and women might be expected to be
more punitive. Though few studies explicitly articulate a vulnerability thesis, there is
evidence that older respondents are more punitive (Cullen et al., 1985; Brillon, 1988;
Hough et al., 1988; Jacoby, 1988) but little to support the notion that women are as
well (Stinchcombe et al., 1980). However, Langworthy and Whitehead’s (1986)
explicit test of the vulnerability hypothesis finds no support, inasmuch as older respon-
dents are neither more fearful nor more punitive and men were generally more punitive
than women.
The final set of studies that address the issue of crime salience measure a more general
and cognitive ‘concern’ for crime as opposed to individual issues like fear and victim-
ization. In these approaches respondents may be asked how concerned they are about
crime (Rankin, 1979), or if crime is among the most important problems facing the
country (Stinchcombe et al., 1980; Hogan et al., 2005), or whether respondents believe
crime is increasing (Thomas and Foster, 1975; Hogan et al., 2005). Stinchcombe et al.
(1980: 70) term this more general concern as the ‘public salience of crime’. The findings
from these studies consistently show that greater concern about crime is related to
increased punitiveness (Thomas and Foster, 1975; Rankin, 1979; Stinchcombe et al.,
1980; Hogan et al., 2005).
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PRIOR RESEARCH: ECONOMIC INSECURITY AND PUNITIVENESS
To our knowledge only two previous studies have directly tested the relationship
between economic insecurity and punitive attitudes toward crime. In the first, Devon
Johnson (2001) used data involving whites only from several years of the General Social
Survey. She employed two measures of punitiveness, including support for the death
penalty and whether respondents think the courts deal too harshly or not harshly
enough with criminals. Her indicators of insecurity include an objective measure of
income and combined responses to a question about respondents current financial situ-
ation and a question about whether it had gotten better or worse in recent years.
Contrary to the insecurity hypothesis income was positively and significantly related to
support for harsher courts, though the effects are described as ‘very small’. No other
relationships between insecurity (objective and perceived) and punitiveness (harsh
courts and capital punishment) were statistically significant (Johnson, 2001: 44–6).
Johnson (2001: 48) speculated that the lack of significant results could be due to the
measures of insecurity used, with the possibility that it is insecurity about the macro-
economy – not an individual’s personal situation – that could have more bearing upon
attitudes toward crime and punishment. Concerning the measures of insecurity used
by Johnson, there are two additional issues that bear notice. First, income itself may
not be a good indicator of economic insecurity, especially for those who have saved well,
invested wisely or have secure jobs. Also, the items operationalizing the subjective
measure of ‘insecurity’ may actually be measuring satisfaction with one’s current and
recently past financial circumstances. As Manski and Straub (1999: 2, emphasis added)
observe, individual perceptions of ‘insecurity are given form through the expectations
they are assumed to hold’. Arguably, dissatisfaction with one’s recent past or current
situation would not necessarily translate into insecurity about the future, though it
could. A more appropriate indicator of insecurity might be more forward looking.
One study that does make use of a forward looking measure of insecurity was
published by Hogan and his colleagues (2005) using survey data from a single county
in Florida. They had two measures of economic insecurity. The first, like Johnson
(2001), asked respondents if they were better or worse off financially than a year ago.
The second asked whether they expected their financial situation to improve or decline
in the coming year. Punitiveness was gauged by support for eight punitive measures
including chemical castration for sex offenders, making prisoners work on chain gangs,
making all prisoners serve 85 percent of their sentence and so on.
Generally, when a sizable number of other factors were controlled, economic
insecurity was unrelated to punitive attitudes in their research. One exception was that
expectations of a decline in future financial circumstances – probably the more appro-
priate measure of insecurity – did significantly predict punitiveness among those who
were not white (primarily black respondents with a small number of Hispanics) (Hogan
et al., 2005: 403–4).
The failure to find a significant effect of economic insecurity on punitiveness among
white males runs counter to the angry white male hypothesis. However, it is possible
that the expected relationship may be particular to some white males and not others.
For instance, it is possible that those with less education and lower incomes may be
more vulnerable in times of economic change and uncertainty. For these more
vulnerable subgroups, it is possible as well, that economic insecurity projects into
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punitiveness more readily than it does among subgroups who are objectively less vulner-
able. That is one of the issues that the present research explores.
RESEARCH METHODOLOGY
The data for this study were generated by a state-wide survey of 2250 randomly selected
Florida residents, who were interviewed between October and December of 1997.
1
The demographic characteristics of the sample are as follows: female, 53 percent;
black, 11 percent; Hispanic, 14 percent; median age, 42. All traits closely approximate
the demographic characteristics of Florida in 1997, except for median age, which is
higher than the actual Florida median age of 38.4 years. The over-sampling of older
respondents is not uncommon in telephone surveys (see Lavrakas, 1987).
DEPENDENT VARIABLE: SUPPORT FOR PUNITIVE POLICIES
Respondents’ punitiveness is measured by their indicated level of support for seven
policies to deal with crime. Each had been proposed or implemented recently in Florida.
Respondents were asked to indicate on a scale of one to ten, with one being the least
support and ten being most support, how much they would support each of the
following:
(1) Death penalty for juveniles who murder.
(2) Send repeat juvenile offenders to adult court.
(3) Lock up more juveniles offenders.
(4) Make sentences more severe for all crimes.
(5) Limit appeals to death sentences.
(6) Make prisoners work on chain gangs.
(7) Take away television and recreational privileges from prisoners.
A principal component factor analysis indicates that a one-factor solution fits the
data best.
2
An index was then created using the factor-weighted scores for all items.
Higher scores on this index indicate greater levels of punitiveness. Reliability analysis
showed a Cronbachs alpha reliability coefficient of .76 for this index.
PRIMARY INDEPENDENT VARIABLES: CRIME SALIENCE AND
ECONOMIC INSECURITY
Three indicators of crime salience are used in this study. Fear of crime is measured using
an index consisting of six items. Respondents were asked: ‘on a scale of one to ten, with
one being not at all fearful and ten being very fearful, how much would you say you
fear?’:
(1) Having your car stolen.
(2) Having someone break into your home while you are away.
(3) Having someone break in to your home while you are there.
(4) Being robbed or mugged on the street.
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(5) Being raped or sexually assaulted.
(6) Being murdered.
As with punitiveness toward crime, weighted-factor scores were used to create an
index measuring individual fear of criminal victimization. Higher scores on this index
indicate greater fear. Reliability analysis of these items produced a cronbachs alpha
coefficient of .91.
Respondents were also asked how concerned they were about various aspects of crime.
Individual concern about crime is also a factor-weighted index (alpha = .89), which
consists of four items asking respondents to indicate ‘on a scale of one to ten, with one
being not at all concerned and ten being very concerned how concerned are you about
the following activities?’:
(1) Crime in the United States.
(2) Crime in Florida.
(3) Violent crime in Florida.
(4) Drug trafficking.
Finally, we include a measure of past crime victimization experiences, which is based
on responses to a question asking whether anyone in the respondents’ household had
been a victim of a crime within the past year (yes = 1).
As previously discussed, measures of economic insecurity that focus on respondents
current situation or that situation relative to the past, may not be as useful as those that
are forward looking. For that reason, we measure economic insecurity by asking respon-
dents: ‘looking ahead, do you expect that at this time next year you will be financially
better off than now, or worse off than now?’ The response categories included ‘better’,
same’ and ‘worse’. Two dummy variables were created to reflect people who did not
expect their economic future to improve. One variable reflects those who think things
would be worse (yes = 1) and another reflects those who expect their economic future
to be the same as now (yes = 1). The reference category includes those who expect to
do better financially in the coming year.
CONTROL VARIABLES
In addition to our primary independent variables, we control for several demographic
characteristics of respondents including sex (female = 1), age in years, race (black = 1),
ethnicity (Hispanic = 1) and marital status (married = 1). Education and household
income were initially measured using five ordered categories, but for purposes of increas-
ing the variance in each, they have been recoded. Education is recoded to approximate
the highest grade completed, with values of 8, 12, 14, 16 and 18. Income is recoded
to reflect the following midpoints of each category, in thousands of dollars: 7.5, 22.5,
39.5, 62.5 and 87.5.
On the basis of prior research, we expect that women may be less punitive than men
(Blumstein and Cohen, 1980; Grasmick and McGill, 1994; Rossi and Berk, 1997);
blacks may be less punitive than whites (Blumstein and Cohen, 1980; Cohn et al., 1991;
Rossi and Berk, 1997) and those with more education may be less punitive than others
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(Miller et al., 1991; Grasmick and McGill, 1994; Rossi and Berk, 1997). The incon-
sistent evidence concerning income and punitiveness (Blumstein and Cohen, 1980;
Sandys and McGarrell, 1994; Applegate et al., 1996) precludes a reasonable expectation.
Political conservatism is a central component of the emergent ‘culture of
control’ (Garland, 2001) and has proven relevant in prior punitive attitudes research
(Langworthy and Whitehead, 1986; Barkan and Cohn, 1994; Sandys and McGarrell,
1995). We include a measure of it in our analysis. For this, respondents were asked to
indicate whether the following policy initiatives should be increased, kept at the present
level, decreased or ended altogether:
efforts to help women achieve equality with men in the workplace;
efforts to help minorities achieve equality with whites;
the amount of tax money being spent on health care for the poor.
Responses were factor analyzed and resultant factor scores were then used to create
an index measuring conservatism. Reliability analysis of the three item index produced
an alpha of .61.
3
Higher scores on this index indicate a more conservative political
ideology. It is expected that this variable will be positively related to punitiveness.
We acknowledge that these are certainly not all the variables that are likely related to
punitiveness. For example, studies have shown the importance of such influences on
punitiveness as symbolic politics (Sears et al., 1979, 1980) and social and political values
such as religious beliefs (Applegate et al., 2000), racial prejudice (Barkan and Cohn,
1994) authoritarianism (Narby et al., 1993), liberalism (Langworthy and Whitehead,
1986) and perceptions of procedural fairness (Tyler et al., 1997). We are aware that
punitive attitudes have their roots in self-interested concerns, such as fear and economic
security, but also in the need to express moral boundaries and engender social cohesive-
ness. In fact, as research has shown, the latter may be a more important determinant
than the former (see, for example, Tyler and Boeckmann, 1997). However, the goal of
this article is to explicitly test the link between crime salience and punitiveness and,
more importantly, the link between economic insecurity and punitiveness and not to
provide a complete explanation for why one might harbor punitive attitudes.
Table 1 provides a description of all of the variables used in the analysis along with
their means, standard deviations and bivariate correlation with the dependent variable.
There it can be seen that the strongest correlates of punitiveness are two measures of
crime salience – concern and fear.
ANALYSIS AND RESEARCH FINDINGS
The data are analyzed using ordinary least squares regression. There are apparently no
problems of multicollinearity. Tolerance levels are consistently above .70 and no bivari-
ate correlations among the independent variables exceed .44. There were, however indi-
cations, that the assumption of homoscedasticity was being violated. A Modified Glesjer
Test for the full sample found that the variance of the residuals was significantly and
negatively correlated with the fear of crime measure (FEAR). In order to address this
problem, LIMDEP’s (7.0) OLS, in addition to SPSS (11.5) OLS, was used to analyze
all ordinary least square equations. LIMDEP applies Whites (1980) correction for
heteroscedasticity of standard errors.
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Results of the regression estimate for punitive attitudes toward crime for the full
sample are presented in Table 2. Unstandardized regression coefficients are reported with
standardized Beta coefficients in parentheses.
4
Examining the control variables first,
these data show that punitive attitudes are significantly lower for those who are black,
and those who are better educated. They are significantly higher for those who are
married or more conservative.
Regarding our variables of primary interest, both concern, the cognitive aspect of
crime salience, and fear, the affective aspect of salience, are significant predictors of
punitive attitudes. The experiential aspect of salience – victim experience – is not, a
result that is consistent with much prior research. In fact, concern and fear are the two
strongest predictors of punitive attitudes when the standardized Beta coefficients (.304
and .164, respectively) are compared to the other variables. For the full sample, neither
measure of economic insecurity is significant.
The next step in the analysis disaggregates the full sample by sex to determine how
the various predictors of punitive attitudes interact with respondent’s sex. Table 3, shows
the result of regressing punitive attitudes on crime salience and economic insecurity for
males and females separately. It is apparent that race, education and conservativeness
have the same consequence for both genders, with lower levels of punitiveness for blacks
and those with more education and higher levels for those who are more conservative.
While females generally (Table 2) were slightly less punitive than men, married women
are significantly more punitive than those who are unmarried.
PUNISHMENT & SOCIETY 11(1)
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TABLE 1 Description of variables used in OLS and logistic regression models
VARIABLE MEAN SD r PUNISH DESCRIPTION
PUNISH 49.82 13.51 1.00 R’s punitive attitude score
AGE 44.64 17.48 .017 R’s age
FEMALE 0.53 0.50 .026 R is female
BLACK 0.11 0.32 –.047* R is black
HISPANIC 0.15 0.35 .033 R is Hispanic
MARRIED 0.53 0.50 .100** R is married
EDUCATION 13.87 2.61 –.084** R’s education level
INCOME 39.01 24.25 –.011 R’s family income
CONSERV 4.28 1.51 .072** R’s conservatism index
CONCERN 34.04 7.06 .294** R’s concern about crime index
FEAR 28.14 16.59 .194** R’s fear of crime index
VICTIM 0.16 0.36 .007 R’s household experienced
victimization in the last year
SAME 0.25 0.43 –.009 R expects to do the same financially
next year (dummy variable; 1 = same)
WORSE 0.09 0.29 .022 R expects to do worse financially next
year (dummy variable; 1 = worse)
* p < .05; ** p < .01.
Note: For all indices, the descriptive statistics presented here are for summed total of the
items making up the index. That is, before they were created using weighted factor scores,
which standardize the indices to have a mean of 0 and a standard deviation of 1.
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With regard to crime salience, it is clear that for both males and females, concern
about crime and fear of victimization significantly increase support for punitive
measures to deal with crime. However, victim experience is unrelated to punitiveness
for women, and inversely related to punitiveness for men. Standardized coefficients
show that concern and fear are the strongest predictors of support for punitive policies
among both groups. As the p-values for slope differences
5
at the bottom of the table
show, the only significant difference between males and females with regard to the effects
of crime salience involve victim experience. We have computed the significance of these
differences and those in subsequent tables only for our primary variables of interest –
crime salience and economic insecurity.
COSTELLOE ET AL. Punitive attitudes toward criminals
35
TABLE 2 OLS regression of punitiveness toward crime on crime salience, economic
insecurity and control measures for the full sample
FULL SAMPLE
Variable b
(beta)
AGE –.002
(–.033)
FEMALE –.069
(–.035)
BLACK –.252**
(–.081)
HISPANIC .016
(.005)
MARRIED .135**
(.067)
EDUCATION –.034**
(–.086)
INCOME .001
(.013)
CONSERV .094**
(.091)
CONCERN .310**
(.304)
FEAR .169**
(.164)
VICTIM –.024
(–.009)
SAME –.005
(–.002)
WORSE .129
(.037)
Constant .537
Adjusted R
2
.16
N 1458
* p < .05; ** p < .01.
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Table 3 also shows that neither measure of economic insecurity is significantly related
to punitiveness for female respondents. Among males, the expectation that ones
economic circumstances would be the same next year as the present, had no bearing on
punitiveness. However, those men who expected their economic situation to become
worse, were significantly more punitive than those who expected to be doing better.
There are no statistically significant differences by sex for the effects of insecurity on
punitive attitudes.
PUNISHMENT & SOCIETY 11(1)
36
TABLE 3 OLS regression of punitiveness toward crime on crime salience, economic
insecurity and control measures by gender
MALES FEMALES
Variable b b
(beta) (beta)
AGE –.003 –.002
(–.042) (–.037)
BLACK –.340** –.206*
(–.100) (–.071)
HISPANIC .144 –.074
(.047) (.027)
MARRIED .093 .159*
(.046) (.081)
EDUCATION –.028* –.040**
(–.070) (–.103)
INCOME .002 –.001
(.057) (–.036)
CONSERV .105** .073*
(.111) (.062)
CONCERN .335** .276**
(.349) (.240)
FEAR .133** .196**
(.113) (.202)
VICTIM –.196* .115
(–.069) (.046)
SAME .112 –.094
(.045) (–.040)
WORSE .221* .046
(.066) (.013)
Constant .395 .624
Adjusted R
2
.19 .15
N 721 737
* p < .05; ** p < .01.
p-value for slope differences
::
Concern: .14 Same: .06
Fear: .13 Worse: .16
Victim: .01
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In developing the possibility of an ‘angry white male’ phenomenon, we turn next to
the interaction of race with crime salience and economic insecurity. Table 4, shows the
results of the OLS analyses that were performed separately for white, black and Hispanic
respondents. Apart from the crime salience measures, there are a number of notable
differences between the three groups in terms of which factors predict punitive atti-
tudes. Being married or conservative increases the level of punitiveness only for white
respondents. Higher levels of education reduce punitiveness only for blacks; being
female does the same only for Hispanics and being older reduces punitiveness only for
whites.
COSTELLOE ET AL. Punitive attitudes toward criminals
37
TABLE 4 OLS regression of punitiveness toward crime on crime salience, economic
insecurity and control measures disaggregated by race and ethnicity
WHITES BLACKS HISPANICS
Variable b b b
(beta) (beta) (beta)
AGE –.005** .008 .007
(–.090) (.093) (.123)
FEMALE –.073 .043 –.249*
(–.037) (.020) (–.132)
MARRIED .132* .165 –.026
(.066) (.075) (–.013)
EDUCATION –.029* –.103** .004
(–.071) (–.243) (.013)
INCOME –.000 .005 –.000
(–.001) (.106) (–.002)
CONSERV .111** –.037 .057
(.111) (–.025) (.049)
CONCERN .344** .288** .187**
(.343) (.242) (.179)
FEAR .130** .354** .204**
(.119) (.346) (.229)
VICTIM –.100 .383* –.198
(–.037) (.147) (–.078)
SAME .025 –.109 .048
(.011) (–.037) (.019)
WORSE .171* .243 –.066
(.052) (.054) (–.018)
Constant .651 .441 –.085
Adjusted R
2
.17 .30 .07
N 1023 168 206
* p < .05; ** p < .01.
p-value for slope differences:
WHITE VS BLACK
1
/WHITE VS HISPANIC
2
Concern: .26
1
/.03
2
Same: .27/.46
Fear: .00/.16 Worse: .41/.19
Victim: .01/.31
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For all three subsamples, concern about crime and fear of criminal victimization are
significantly related to the expression of more punitive attitudes. Fear is the strongest
predictor of punitiveness in the model for both black and Hispanic subsamples, and it
is the second strongest predictor for white respondents. For whites, concern is the
strongest predictor and for blacks and Hispanics it has the second strongest effect after
fear. Finally, previous victimization experience significantly increases punitiveness only
for black respondents. There are several noteworthy slope differences involving crime
salience in Table 4. The effect of concern on punitiveness is significantly higher for
whites than Hispanics, and the effects of both fear and victim experience on punitive
attitudes are significantly stronger for blacks than for whites.
With regard to economic insecurity, the expectation that ones financial circumstances
will be unchanged in the coming year has no consequence for punitive attitudes in any
of the race/ethnicity subsamples. However, the expectation of declining economic
circumstances, while inconsequential for black and Hispanic respondents, significantly
increases support for punitive measures among white respondents. None of the
differences between whites and either blacks or Hispanics in this regard are statistically
significant.
These data have shown that concern about crime and fear of victimization predict
increased punitive attitudes for females and males and for black, Hispanic and white
respondents alike. The data also have shown that the only significant effects of economic
insecurity involve males and whites. Table 5 sharpens the focus on white males by
comparing a model of punitiveness estimated for that group with a model estimated
for all others.
Comparing white males with others provides several interesting contrasts. Being
married increases punitiveness only among those who are not white males and more
education leads to less punitive attitudes for the same group. Conservative orientation
increases punitiveness among white males, but not among others. Concern about crime
and fear of crime significantly raises support for punitive measures for both groups, but
the effect of concern is stronger for white males and the effect of fear is stronger for
others. Victim experience reduces punitiveness among white males and the difference
with others is significant.
In terms of economic insecurity, the expectation of stagnant financial circumstances
elevates punitive attitudes among white males modestly, but not significantly. The effect
for others is modestly negative. The slope difference between white males and others in
relation to this measure approaches statistical significance (p = .08). For white males,
the expectation that ones financial situation is going to get worse in the next year,
significantly increases the support for punitive measures. For others, this expectation is
unrelated to punitiveness. However, slope differences between white males and others
on the effects of this measure are not statistically significant.
The final step in our analysis examines whether objective circumstances of white
males that may be indicative of economic vulnerability, interact with crime salience and
economic insecurity in helping to sponsor punitive attitudes. As noted above, white
males without a high school degree have been hit hardest by economic changes since
the mid-1970s (New York Times, 1996: 189–90). In fact, between 1972 and 2003 the
real wages of men with less than a high school degree have declined, while those for
men with higher education levels and for women at all education levels have increased
PUNISHMENT & SOCIETY 11(1)
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(Mishel et al., 2005: 152–5). It is also the case that in that same period, real wages
dropped for male workers in the bottom five deciles of income, while increasing for
men in the top five deciles and for women in all income deciles (Mishel et al., 2005:
124–6). It may be reasonable then to assume that low education and income levels for
males increase the objective economic vulnerability that some may experience, and this
could intensify the effects of perceived economic insecurity on punitive attitudes toward
criminals.
In Table 6, we disaggregate white males into ‘high’ and ‘low’ levels of education and
household income. The division is made at approximately the median of each for our
sample, which produces education categories of no college degree vs college degree or
more and less than or equal to $30,000 and above $30,000. For white males, concern
COSTELLOE ET AL. Punitive attitudes toward criminals
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TABLE 5 OLS regression of punitiveness toward crime on crime salience, economic
insecurity and control measures for white males and others
WHITE MALES OTHERS
Variable b b
(beta) (beta)
AGE –.004 –.001
(–.073) (–.023)
MARRIED .100 .181**
(.049) (.092)
EDUCATION –.020 –.039**
(–.049) (–.101)
INCOME .000 .000
(.012) (–.004)
CONSERV .129** .054
(.138) (.045)
CONCERN .370** .280**
(.387) (.247)
FEAR .089* .215**
(.071) (.217)
VICTIM –.220* .034
(–.075) (.013)
SAME .107 –.087
(.045) (–.036)
WORSE .236* .061
(.075) (.017)
Constant .444 .495
Adjusted R
2
.19 .17
N 517 849
* p < .05; ** p < .01.
p-value for slope differences:
Concern: .05 Same: .08
Fear: .02 Worse: .17
Victim: .04
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about crime significantly increases punitive attitudes for each education and income
group, with the tendency for the effect to be stronger – though not significantly so –
among better educated and higher income respondents. Fear of crime predicts puni-
tiveness only for white males with less education. But the difference from better
educated respondents and the difference between income groups in relation to the
effects of fear is not significant. Victim experience has a negative influence on punitive-
ness for all four groups, and is significant only for less well educated white males.
The expectation that ones financial circumstances will remain the same over the
coming year increases punitiveness modestly for the low education subsample and
PUNISHMENT & SOCIETY 11(1)
40
TABLE 6 OLS regression of punitiveness toward crime on crime salience, economic
insecurity and control measures for white males disaggregated by education and
income
LOW HIGH LOW HIGH
EDUCATION EDUCATION INCOME INCOME
Variable bbbb
(beta) (beta) (beta) (beta)
AGE –.004 –.003 .000 –.009**
(–.074) (–.051) (.009) (–.135)
MARRIED .224* –.068 .207 .017
(.112) (–.032) (.096) (.008)
EDUCATION –.003 –.030
(–.008) (–.069)
INCOME .001 –.001
(.033) (–.015)
CONSERV .100* .160** .145* .119**
(.109) (.167) (.153) (.128)
CONCERN .313** .411** .278** .413**
(.323) (.437) (.280) (.442)
FEAR .111* .068 .129 .080
(.095) (.049) (.112) (.060)
VICTIM –.263* –.102 –.330 –.094
(–.092) (–.034) (–.112) (–.032)
SAME .183 –.021 .309* .001
(.080) (–.008) (.138) (.000)
WORSE .461** –.085 .372* .215
(.149) (–.027) (.126) (.066)
Constant .068 .262 –.167 .933
Adjusted R
2
.17 .20 .14 .24
N 302 215 170 347
* p < .05; ** p < .01.
p-value for slope differences:
LOW VS HIGH EDUCATION
1
/LOW VS HIGH INCOME
2
Concern: .12
1
/.07
2
Same: .15/.08
Fear: .35/.33 Worse: .03/.29
Victim: .25/.23
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decreases it modestly for those with a college degree or more. Among low income white
males, the expectation of stagnant economic circumstances significantly increases the
support for punitive attitudes, but has no consequence for those with higher incomes.
The difference in the effect of this variable across the two income groups approaches,
but fails to achieve statistical significance (p = .08).
However, among white males, those with lower education and income levels, are
significantly more likely to be punitive toward criminals than their better educated and
better paid counterparts. The difference in the effects of white male insecurity on puni-
tiveness is significant for the education subsamples but not for income. Moreover,
among poorly educated white males, anticipated decline in economic circumstances is
the second strongest predictor, after conservatism of punitive attitudes.
DISCUSSION
During the past thirty years, two notable trends have had a transformative impact on
the social and political fabric of American society. The first has been a relentless ‘down-
sizing’ (which was peaking at the time of this survey) and ‘outsourcing’ of American
jobs. Beginning in the blue collar manufacturing sector and continuing to the present
in white collar managerial and even high skill technical work, tens of millions of jobs
have been eliminated completely or replaced by lower paying alternatives. Hardest hit
during this period, in terms of earning power, have been white males with low education
levels (Mishel et al., 2005). A second trend has been a steady escalation in the salience
of crime in American culture and consciousness. Despite a modest decline in the past
ten years, high levels of crime have become a fact of life, especially in and around large
urban centers. And given the persistent representation of crime in political discourse
and in media content, there has emerged a ‘collective cultural experience’ of crime
(Garland, 2001: 147) that extends to all social environments.
Following a lead indicated by Garland (2001) and by Roberts et al. (2003) this article
has examined whether punitive attitudes toward criminals have possible roots in two
hypothesized sources of anxiety rooted in the aforementioned trends. The first concerns
the danger of crime and the second, economic uncertainty. Both have been linked to
the perception that life is precarious and fraught with risk and that somehow the State
is seen as failing ‘in its efforts to deliver physical and economic security to key social
groups’ (Garland, 2001: 133). In response to such anxieties, it has been suggested that
a ‘culture of control’ (Garland, 2001) suffused with ‘penal populism’ (Roberts et al.,
2003) has emerged to focalize targets – especially criminals – about which something
decisive can be done. Punitive criminal justice policies and equally punitive public atti-
tudes are most likely, important co-determining correlates of this emergence.
Our data show that crime salience – when measured by concern about crime and
fear of crime – consistently and strongly predict punitive attitudes. Victim experience
does not. The significance of concern and fear in this regard is manifest regardless of
the sex, race or ethnicity of respondents. When economic insecurity is indicated by the
expectation that ones financial circumstances will not improve, but will stay the same
in the coming year, there is little consequence for punitiveness. However, among those
who expect their financial circumstances to get worse in the near future, support for
punitive measures to deal with criminals is consistently elevated. This link between
COSTELLOE ET AL. Punitive attitudes toward criminals
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punitive attitudes and economic insecurity is found only for white males, and in particu-
lar, those white males who are less well educated and have relatively low income.
Our findings with regard to the effects of crime concern on punitiveness are con-
sistent with results reported by several earlier studies (e.g. Rankin, 1979; Stinchcombe
et al., 1980; Hogan et al., 2005) and those involving fear also have precedent (Lang-
worthy and Whitehead, 1986; Schwartz et al., 1993; Applegate et al., 2000). However,
the consistency of the effects of fear on punitive attitudes that we found across racial
and ethnic groups, runs counter to earlier results which found no such relationship for
whites (Cohn et al., 1991; Hogan et al., 2005). This could be indicative of the increas-
ing and more widespread salience of crime in popular culture, which has been described
by Garland (2001) among others.
The finding that punitiveness is elevated by economic insecurity contrasts with
Johnsons (2001) null findings. However, our measure of insecurity, which is forward
looking, is different from those that she used (see previous discussion). Our finding that
the relationship between insecurity and punitive attitudes obtained only for white males
contrasts with results reported by Hogan et al. (2005) who found that relationship only
among those who were not white males. Why these results should differ is not readily
apparent, but there are several methodological disparities in the two studies that may
be relevant.
First, the present research uses a different measure of punitive attitudes than Hogan
and his colleagues and it includes three items concerning juveniles. This may be why
women, who comprise the vast majority of the non-white males in our sample, are
somewhat less punitive in general, while those in Hogan et al. (2005) were somewhat
more punitive. Also, the present research involves a state-wide sample, 11 percent of
which is black and 14 percent Hispanic, with a median age of 42 years. The research
by Hogan and associates (2005) is limited to a single county, with a sample that is 24
percent black (no Hispanics reported) and a median age of 29 years. As Hogan et al.
(2005: 407) point out, their research environment may be atypical because it is a state
capital with two major state universities and ‘as such . . . is somewhat insulated from
the range of instabilities experienced in many labor markets’. Those instabilities and
resultant insecurities may be more salient for white males like those in our sample, who
are drawn from a more diverse range of communities, and who are older on average.
The fact that economic insecurity increases punitiveness only among white males
who have relatively less education and income may suggest that the ‘angry white male
phenomenon may be somewhat broader in its application than previously noted. In
prior discussions, the targets of this anger have been the presumed beneficiaries of
affirmative action – women and especially minorities (Pollitt, 1995; Walker, 1995) – as
well as immigrants (Stengel and Bonfante, 1995; Wartzman, 1995) and welfare
recipients (Wartzman, 1995). The targets of white male antipathy – assuming punitive
attitudes are an expression of that sentiment, apparently includes criminals. Interest-
ingly, criminals might be seen by low income, poorly educated white males in similar
terms as they saw the putative beneficiaries of affirmative action and welfare. In their
eyes, all may be perceived as getting ‘something for nothing’ (Schor, 1991; Sidel, 1996),
while some white males are ‘making do with less’.
The conflation of objective conditions – low income and low education – with the
expressed expectation of declining economic circumstances may put a sharper point on
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what has sometimes been described and criticized (Leo, 1995) as a generalized ‘white
male’ phenomenon. It is likely not white males per se who have resentments about the
course of events, but low income white males who expect further economic distress and
have little educational capital to use in response to the insecurities of the increasingly
global workplace.
The previously noted resentments expressed toward affirmative action and welfare
had a clear racial undercurrent. It is reasonable to assume that expression of punitive
attitudes toward criminals has a similar racial component. The rationale for that assump-
tion can be found in the extent to which crime is conflated with race and ethnicity in
contemporary American culture (Hawkins, 1995; Barlow, 1998; Russell, 1998). As
Jerome Miller suggested: ‘when we talk about building more prisons, when we talk
about longer sentences . . . everyone knows that were talking about blacks’ (Szkowny,
1994: 12). In this regard, Chiricos et al. (2004) report higher levels of punitiveness
among those whites who equate crime with blacks. They also report that racial preju-
dice significantly increases punitive attitudes – a finding that has some precedence in
other research on punitive attitudes toward criminals (Cohn et al., 1991; Aguirre and
Baker, 1993; Barkan and Cohn, 1994).
A related point is that when punitive attitudes toward criminals are continually
expressed in political discourse and repeated by low income white males with low levels
of education, the result, whether intended or not, is to reinforce racial divisions among
members of the working and lower classes. Such divisions have historically weakened
the prospect of a progressive political agenda (Egerton, 1994; Wilson, 1999) and they
serve to deflect attention away from the actions of corporations – downsizing and
outsourcing – and complementary government policies that are the fundamental cause
of economic insecurity among blacks and whites alike.
The conversion of objective and subjective economic insecurities into punitive
attitudes toward criminals may be effected by a variety of linking mechanisms. Such atti-
tudes may be a way of ‘channeling anxious insecurities’ (Chancer and Donovan, 1996:
52) or a means to achieve ‘compensatory satisfaction’ (Greenberg, 1999: 334) for those
whose economic circumstances are precarious. They may be a way of scapegoating targets
in the context of a diffuse and free floating anger rooted in economic insecurity (New
York Times, 1996: 24). They may also may serve, as Gans (1995: 7) suggests, to reinforce
the moral and social distinction between those who are economically insecure and others
– such as criminals – who may be considered among the ‘undeserving poor’.
One limitation of the present analysis is that the available data precluded us from
including precise measures of ‘symbolic politics’ or political and social values which
some have linked to punitive attitudes. It has been suggested that through socialization
processes, people acquire early in life ‘general predispositions’, such as party identifi-
cation, liberal or conservative ideology, nationalism or racial prejudice which shape atti-
tudes toward a wide range of issues and may have greater consequence for policy related
attitudes than self-interest or material concerns (Sears et al., 1980; Tyler et al., 1997).
While our data did not allow an extensive test of these kinds of issues, our measure
of political ideology – conservatism – was a consistent predictor of punitiveness. This
provides evidence that certain ‘general predispositions’ are indeed, important predictors
of support for punitive policies and should be given considerable attention in future
research. However, it also noted that conservatism was not a consistently stronger
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predictor than variables that may measure self-interest, particularly fear of crime. In
fact, conservatism was only a stronger predictor than fear for white males. Neverthe-
less, it is likely that punitive attitudes are related to more than changing economic and
social circumstances and reflect in part, long held and firmly entrenched predispositions
that are beyond the scope of the present data.
Whatever the precise linking mechanism, the present research has demonstrated that
economic insecurity has a significant role to play – along with crime salience – in the
understanding of punitive attitudes toward criminals. These findings lend support to
Garland’s (2001: 139) contention that an emergent culture of control in western society
has its ‘roots in a new collective experience of crime and insecurity’. Whether measured
by fear or concern, the relevance of crime salience for punitiveness has long been recog-
nized. But the relevance of economic insecurity is a new factor in our attempt to under-
stand punitive attitudes.
The forces that have created the rising economic insecurity of the past 30 years were
all in place in the mid-1970s. In the face of growing competition from abroad, American
corporate profits had been declining since 1968 and reached a post-war low in 1974
(Bowles et al., 1984). That is when the editors of Business Week (1974: 120), reflecting
on corporate profits, observed that ‘Some people will obviously have to do with less . . .
yet it will be a hard pill to swallow – the idea of doing with less, so that big business
can have more.’ What followed was the rising tide of disinvestment, downsizing and
outsourcing that has caused the well documented insecurities of American workers
among other things. Interestingly, the early 1970s witnessed the lowest rates of
incarceration – a key indicator of punitiveness – since the 1920s (US Department of
Justice, 1986). Since 1973, rates of incarceration have increased by more than 400
percent (US Department of Justice, 2007) and at the same time, an emergent ‘penal
populism’ has grown apace (Roberts et al., 2003). So at almost the same point in time,
forces were set in motion that have dramatically increased both economic insecurity
and levels of punitiveness. In the context of these corresponding historical patterns at
the macro level, the present findings that connect inequality and punitiveness at the
micro level, may not be surprising.
Acknowledgements
We are indebted to the two anonymous reviewers for their thoughtful comments and
suggestions. This is a much improved article because of their efforts. Please do not cite
or quote without written permission from authors.
Notes
1 Random-digit dialing was used to access households in which the adult (18 years and
older) having the most recent birthday in the household was surveyed. The survey
was conducted by the Research Network, Inc. in Tallahassee, Florida, using a two-
stage Mitofsky-Waksberg sampling design. This is a two-stage sampling process. In
the first stage a sample of clusters is selected, where each cluster was an assigned area-
code and prefix combined with the first two digits of an assigned suffix and a random
two-digit number (AAA-PPP-SSRR). Then one of the 100 numbers within the
cluster was randomly sampled and dialed. The first-stage cluster (bank of 100
numbers) is retained in the sample only if the randomly sampled number in the
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cluster was residential (Waksberg, 1978). A cooperation rate of 80 percent was
realized, meaning that interviews were completed for 80 percent of all contacts known
to be eligible respondents. Cases of unknown eligibility (busy signals, no answer and
answering machines) and known ineligibility (business, fax and disconnected) were
excluded from the calculation of this rate as recommended by the American Associ-
ation for Public Opinion Research (1998). Spanish-speaking interviewers were used
for telephone calls to predominantly Hispanic areas.
2 Two factors with eigenvalues of greater than 1.00 were found (results not provided
here), but the most pronounced break was clearly between the first and second
factors, with the first factor explaining over 40 percent of the variance in the items
and the second factor explaining only about 14.5 percent of the variance. Addition-
ally, exploratory factor analysis revealed that all of the items loaded more heavily on
the first component than the second component, suggesting a one-factor solution.
3 The lower alpha associated with this scale primarily results from the fact that it is
constructed using only three items and because, for each item, the response range is
limited. Carmines and Zeller (1979) note that Cronbachs alpha is the lower bound
of reliability and that the affect of a low alpha is that it makes it more difficult to
discover a significant effect empirically when it exists in reality. In the analyses that
follow the effect of this variable is consistent with theoretical expectations, thereby
enhancing the confidence that it is a true effect and reducing the concern about the
lower alpha.
4 As there are theoretically based predictions for the direction of each of the effects,
one-tailed significance tests are used in all analyses.
5 Slope differences were calculated using the following formula as recommended by
Paternoster et al.(1998) Z-score = b1 – b2 / (SEb1
1
+SEb2
2
).
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MIKE COSTELLOE is an Assistant Professor in the Department of Criminology and Criminal Justice at
Northern Arizona University. He is also the Assistant Director of the Northern Arizona Justice Project. His
research interests include punitive attitudes, immigration sentiments, the policing of undocumented immi-
gration and the factors that lead to wrongful convictions.
TED CHIRICOS is the William Julius Wilson Professor of Criminology in the College of Criminology &
Criminal Justice at Florida State University. His research interests include the effects of race and social threat
on justice outcomes, as well as the various factors that contribute to punitiveness in the United States.
MARC GERTZ is a Professor at Florida State University’s College of Criminology and Criminal Justice. He
has published recently in Criminology, Journal of Research in Crime and Delinquency and Social Problems. His
research interests include the study of public opinion and the criminal justice system, the organization of
courts and interest groups and voting behavior.
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... A body of work has documented public attitudes toward criminal justice policies and reforms vary by gender and race/ethnicity. Research of gender differences or gaps in attitudes toward criminal justice issues are mixed (Anderson et al., 2017;Applegate et al., 2002;Carr et al., 2007;Chiricos et al., 2004;Clark, 2017;Costelloe et al., 2009;Haghighi & Lopez, 1998;Johnson, 2007;Johnson & Kuhns, 2009;Peffley & Hurwitz, 2007;Silver & Pickett, 2015;Wang et al., 2019). Similar research is less substantial in garnering such attitudes among underrepresented groups (Carr et al., 2007;Costelloe et al., 2009;Haider-Markel & Joslyn, 2017;Nelson et al., 2007;Peffley & Hurwitz, 2007;Wang et al., 2019). ...
... Research of gender differences or gaps in attitudes toward criminal justice issues are mixed (Anderson et al., 2017;Applegate et al., 2002;Carr et al., 2007;Chiricos et al., 2004;Clark, 2017;Costelloe et al., 2009;Haghighi & Lopez, 1998;Johnson, 2007;Johnson & Kuhns, 2009;Peffley & Hurwitz, 2007;Silver & Pickett, 2015;Wang et al., 2019). Similar research is less substantial in garnering such attitudes among underrepresented groups (Carr et al., 2007;Costelloe et al., 2009;Haider-Markel & Joslyn, 2017;Nelson et al., 2007;Peffley & Hurwitz, 2007;Wang et al., 2019). A remarkable trend as minority groups disproportionately represents deadly encounters with police and the imprisonment population (Carson, 2020;Mapping Police Violence, 2020). ...
... A remarkable trend as minority groups disproportionately represents deadly encounters with police and the imprisonment population (Carson, 2020;Mapping Police Violence, 2020). Many of these studies also trail in relevancy, focusing on correctional policies, emphasizing punitiveness (e.g., death penalty) rather than reform (e.g., eliminating mandatory minimums) (Anderson et al., 2017;Chiricos et al., 2004;Clark, 2017;Costelloe et al., 2009;Haghighi & Lopez, 1998;Johnson, 2007;Peffley & Hurwitz, 2007;). As public interest in the death penalty continues to decline since 2004, these analyses fail to capture the American public's growing interest in policing violence and criminal justice reform (Google Trends, 2020). ...
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Divisive criminal justice issues are typically framed through gender and racial lenses, with little empirical work considering the increasing role of political partisanship. Using the 2016 Cooperative Congressional Election Study ( N = 55,000), we estimate multivariate models of support for four policing and correctional reforms. The models initially point to gender gaps and racial gaps. However, as with many public policy issues, support for criminal justice reforms are largely a product of political partisanship—the gender and racial gaps are largely a consequence of gender and racial gaps in partisanship and appear to be driven by white Republican men. As legislative bodies continue to be overrepresented with individuals with the same demographic profile, criminal justice reform prospects are limited.
... Using local and national samples, empirical research evaluating the link between emotions and support for mano dura has produced mixed results. While some scholars focusing on the United States disregarded the role of emotions as a predictor of punitiveness (Kleck & Jackson, 2017;Tyler & Boeckmann, 1997), a second strand of empirical work found a positive relationship (Costelloe et al., 2009;Dowler, 2003;Johnson, 2009;Unnever et al., 2005). The effects of emotions such as anxieties and fear of crime on punishment preferences have been also tested in other Western industrialized countries, including Great Britain (King & Maruna, 2009), Germany (Armborst, 2017), and Canada (Hartnagel & Templeton, 2012;Wanner & Caputo, 1987). ...
... In their regression analysis, the social sources of punitiveness are not limited to crime-related factors (Singer et al., 2020). Similar to other studies developed in the United States (Costelloe et al., 2009;Hogan et al., 2005;Singer et al., 2020) reveal that those who believe that the national economy is poor are more likely to support increased levels of punishment, although this correlation is reversed if the personal economic situation is measured. ...
... The results suggest that punitivism is highly contextual and likely associated with economic, political, and social insecurities occurring at the aggregate level. This is consistent with studies focused on the United States and other Western industrialized countries, which emphasize that fear of crime affects the public's punitive attitudes (Costelloe et al., 2009;Dowler, 2003). Singer et al. (2020) also find this correlation in Latin America. ...
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... A related line of inquiry focuses on economic anxieties, which can become conflated with feelings of anger and bitterness against social groups perceived as receiving "special treatment" via government financial assistance (Garland, 2001;Wacquant, 2010b). In the context of late modern societies where individualistic ideologies prevail and blame for crime and other social ills can be displaced onto marginalized groups, "diffuse anxieties" surrounding personal and societal economic conditions can fuel punitiveness (Costelloe et al., 2009;Hogan et al., 2005;Lehmann & Pickett, 2017;Ousey & Unnever, 2012). Finally, some prior research has found that fear of crime is associated with heightened punitive sentiments (e.g., Costelloe et al., 2009;Dowler, 2003;Kleck & Jackson, 2017;Singer et al., 2020;Sprott & Doob, 1997;Unnever et al., 2005). ...
... In the context of late modern societies where individualistic ideologies prevail and blame for crime and other social ills can be displaced onto marginalized groups, "diffuse anxieties" surrounding personal and societal economic conditions can fuel punitiveness (Costelloe et al., 2009;Hogan et al., 2005;Lehmann & Pickett, 2017;Ousey & Unnever, 2012). Finally, some prior research has found that fear of crime is associated with heightened punitive sentiments (e.g., Costelloe et al., 2009;Dowler, 2003;Kleck & Jackson, 2017;Singer et al., 2020;Sprott & Doob, 1997;Unnever et al., 2005). According to Unnever and Cullen (2010b), there is "a pervasive and deeply felt sense that anyone could be the next victim of the everescalating increase in criminality" but that "the welfare state no longer can be trusted to put victims' interests ahead of offenders' interests" (p. ...
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Eva Groß zeichnet in ihrem Beitrag zum einen empirisch nach, wie sich die subjektive Kriminalitätsfurcht zu Entwicklungen in der offiziell registrierten Kriminalität verhält. Zum anderen beleuchtet sie empirische Verbindungslinien zwischen der Wahrnehmung ethnischer Heterogenität, allgemeinen sozialen Abstiegsängsten, fremdenfeindlichen Einstellungen, Punitivität und Kriminalitätsfurcht.
... The studies report mixed findings about the relationship between perceptions of crime, fear of crime, prior victimisation, and support for punitive crime-control policies. , for instance, showed that in the USA prior victimisation and fear of crime weakly predict support for the death penalty, whereas Costelloe et al. (2009) reported that fear of crime, concern about crime, and prior victimisation explain punitive attitudes in a randomly selected sample of Florida residents. Mears and Pickett (2019) found that people favour more punitive policies when they believe that crime is high or rising. ...
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