Running head: VICTIMIZATION AND VOTE
“A conservative is a liberal urban dweller who has been mugged”: A longitudinal study on the links between victimization and voting preferences
Silvia Russo Michele Roccato
Alessio Vieno
Authors’ note:
Silvia Russo, Department of Psychology, University of Torino, Via Verdi, 10, 10124 Torino, Italy. Telephone: ++390116702055, Fax: ++390116702061, E-mail: silvia.russo@unito.it
Michele Roccato, Department of Psychology, University of Torino, Via Verdi, 10, 10124 Torino, Italy. Telephone: ++390116702015, Fax: ++390116702061, E-mail:
michele.roccato@unito.it (corresponding author)
Alessio Vieno, Department of Developmental and social psychology, University of Padova, Via Belzoni 80, 35131 Padova, Italy. Telephone ++390498278479, Fax: ++390498278451, E-mail: alessio.vieno@unipd.it
“A conservative is a liberal urban dweller who has been mugged”: A longitudinal study on the links between victimization and voting preferences
Silvia Russo* Michele Roccato*
Alessio Vieno°
* Department of Psychology, University of Torino, Italy
° Department of Developmental and Social Psychology, University of Padova, Italy
ABSTRACT
We conducted a longitudinal study with a sample of Italians living in Piemonte, a North-Western Italian region (N = 799, 55.2% men, mean age = 53.57, SD = 15.90), aimed at analyzing the effects exerted by criminal victimization on participants’ voting preferences, assessed in terms of voting intention, between January 2005 (T1) and January 2006 (T2). Three sets of predictors of voting intention at T2 have been entered in a hierarchical moderated regression: (a)
socio-demographic variables and voting intention as measured at T1, used as control variables; (b) direct and indirect victimization occurred between T1 and T2; and (c) the interactions between direct and indirect victimization on the one side and some proxy indicators of community’s disorder and of participants’ vulnerability on the other side. As hypothesized, direct and indirect victimization did not influence our dependent variable. However, a significant interaction between indirect
victimization and living in a large town has been detected: Participants’ conservatism increased only among victimized urban dwellers. Implications, limitations, and possible developments of this research are discussed.
INTRODUCTION
According to the assumptive world perspective [Janoff-Bulman, 1989], under “normal” conditions people tend to develop an image of the relation between themselves and their social world that is based on three unquestioned assumptions: (a) benevolence of the impersonal world and of other people; (b) the existence of a just, meaningful and controllable world; and (c) self-worth. Criminal victimization, being based on the perpetrator’s intention to cause harm [Craig-Henderson & Sloan, 2003], is likely to jeopardize such assumptions. Hence, beyond its undesirable physical [Gidycz & Koss, 1991] and economic [Van Dorn, 2004] consequences, victimization may have negative psychological outcomes, fostering psychological distress [Norris & Kaniasty, 1994], post-traumatic stress disorder [Resnik, 1987], lowered levels of well-being [Denkers & Winkel, 1998], and lowered perceptions of health [Koss, Woodruff, & Koss, 1990]. The literature shows that the severity of these psychological consequences mainly depends on the kind of victimization suffered and on people’s physical, psychological, and economic vulnerability [Norris, Kaniasty, & Thompson, 1997].
Thus, it is far from surprising that victimized people try actively to neutralize the negative effects of this experience using coping strategies [Collins, Taylor, & Skogan, 1990; Winkel, 1998; Winkel & Denkers, 1995]. The degree of success of these strategies—which, according to the neutralization techniques perspective [Agnew, 1985], will depend on the nature of the
victimization, the characteristics of the individual, his/her degree of social support, and the characteristics of his/her community—will influence the consequences of victimization.
Unsuccessful coping will result in problems and difficulties in managing subsequent victimization, while successful coping will not [Winkel, 1999].
Generally speaking, in this research we conjectured that victimization could also influence people’s political preferences, and that victimized people could try to cope with the negative consequences of this experience by increasing their degree of conservatism, i.e. by increasing their preferences for the parties whose programs are hinged on law and order [Danigelis & Cutler, 1991].
We based our reasoning on three psycho-social literatures. First, the terror management theory [Greenberg, Pyszczynski, & Solomon, 1986; Stone, 2001] shows that people can successfully cope with death anxiety by adhering to values and views dominating in their society, i.e. raising their conventionalism, a construct traditionally conceived as strictly linked with conservatism [Adorno, Frenkel-Brunswik, Levinson, & Sanford, 1950]. Second, according to the last developments of the literature on authoritarianism, Right-Wing Authoritarianism (RWA), a construct strongly related with political conservatism [Altemeyer, 1988], reduces the impact of a distressed personality on depression and the physical and social negative consequences of many potentially stressful life events actually experienced. In this light, RWA, far from unavoidably being a dysfunctional trait, should be considered as an efficient mechanism people may use to cope with stress [Van Hiel & De Clercq, 2009]. Third, according to Jost and colleagues [2003], political conservatism is based on psychological needs that vary by situation and disposition to help people managing uncertainty and threat. Somewhat consistently with these literatures, Cavazza, Corbetta, and Roccato [2008] showed that concern for crime as a social problem was one of the main causes of the victory of the right-wing coalition in the 2008 Italian general election.
From the psychosocial standpoint, we conjectured that victimization should influence people’s conservatism via the mediation of increased vulnerability, of fear of new victimization experiences, and of anger with society for its inability to protect them [Langworthy & Withehead, 1986;
Zimring, Hawkins, & Kamin, 2001]. In this light, victims of criminality should be urged to defend themselves, the people in their social network, and their community by endorsing policies focused on law and order, which are typically supported by right-wing parties [Tyler, & Boeckmann, 1997].
This “mugging thesis” [Unnever, Cullen, & Fisher, 2007] sounds unpleasantly biased against left-wingers: If “a conservative is just a liberal who has been mugged” [King & Maruna, 2009], “people exposed to crime—those who have been victimized—will be more likely to see the wisdom of conservative views on crime and, more generally, on social policies. Liberal beliefs are thus portrayed as a luxury that only those insulated from the harsh realities of the world can afford to
espouse” [Unnever, Cullen, & Fisher, 2007, p. 311]. In fact, although widely spread in the public opinion, this thesis has been seldom tested empirically obtaining contrasting results. For instance, Sears, Lau, Tyler, and Allen [1980] showed that a composed index integrating victimization and fear of crime explained only 1% of the support for law and order policies. Moreover, Langworthy and Whitehead [1986], Stack [2000], and Unnever, Cullen, and Fisher [2007] did not find any significant link between victimization and liberalism/conservatism. Substantially analogous results stemmed from the research on the links between victimization and punitiveness [Evans & Adams, 2003; King & Maruna, 2009; Stack, 2003].
With few exceptions, these studies analyzed the direct effects exerted by direct victimization (i.e. that occurred to the participant him/herself) only. However, according to the literature on fear of crime, coping with indirect victimization (i.e. that occurred to people in one’s own social
network) can be much harder than coping with direct victimization, both because the latter is much more widespread that the former and because it “allows one’s imagination full scope without perhaps the same urgency to find some coping strategy” [Hale, 1996, p. 105]. Moreover, the literature shows that—at least in some cases—victimization fosters fear of crime only among people living in disordered areas, both at the perceived [Roccato, Russo, & Vieno, submitted] and at the objective [Vieno, Russo, & Roccato, submitted] levels. According to these authors,
victimization makes salient the negative contextual aspects of people’s community: Deeply inspecting ordered communities does not foster fear of crime, while doing so in a disordered community does, as it makes more salient its threatening features.
Thus, these two studies showed that, when analyzing the effects of victimization, it may be useful to take into account interactive effects among predictors. Even though the moderated effects Unnever and colleagues [2007] analyzed in their research aimed at testing the “mugging thesis” in 10 different GSS surveys were not statistically significant, the variables they used as moderators of the relation between victimization and political beliefs (mainly the years in which the GSS survey was performed, and participants’ social class and race) were different from those we used.
Moreover, they did not perform a longitudinal study: Hence, they could not analyze actual changes in participants’ political beliefs. In this chapter we tried to overcome these limitations in a
longitudinal study performed in Italy between 2005 and 2006.
THE 2005-2006 ITALIAN POLITICAL SITUATION
Between 2001 and April 2006 Italy was governed by a center-right coalition, the Casa delle Libertà (CDL). Its main party was Forza Italia (FI), and television tycoon Silvio Berlusconi was the leader of FI and of CDL and was also the country’s Prime Minister. Three other parties composed the coalition: (a) Alleanza Nazionale, an originally neo-fascist party which converted to democracy in 1994; (b) Lega Nord, a party rooted in the rich and affluent North of Italy that has politicized and mobilized voters in the past 10 years around the issue of immigration, with systematic ethnocentric campaigns; and (c) Unione Democratica di Centro, a catholic center-right party. The main
opposition parties were joined in the center-left Ulivo coalition, whose leader was Romano Prodi, Prime Minister between May 1996 and October 1998. The coalition included: (a) Democratici di sinistra (DS), a left-wing party that moved away from communism in 1991; (b) Margherita, a catholic center-left party; and (c) Verdi, an ecologist party. To the left of Ulivo, there was
Rifondazione Comunista (RC), the largest and most radical Italian Communist party. In 2005 the center-left coalition was renamed Unione, gathering together DS, Margherita, Verdi, RC, and other minor parties. As forecasted by all the pre-electoral polls performed in the previous 24 months (see Sani, 2006), on April, 9-10 2006 the Unione won the political election and its leader, Romano Prodi, became Prime Minister for the second time. Outside the two coalitions there were some other parties, among which the Partito radicale, a left-wing small party.
Research shows that, in Italy, the counterposition between left and right is still the main criterion that identifies different political positions and is the dimension that is most relied on to organize the perception of Italian political objects (leaders, parties, and coalitions) [Campus, 2000; Ricolfi, 1999, 2004].
GOALS AND HYPOTHESES
We aimed at analyzing longitudinally the effect of direct and indirect victimization on participants’ level of conservatism between 2005 and 2006. Based on the literature [Langworthy & Whitehead, 1986; Sears et al., 1980; Stack, 2000; Unnever, Cullen, & Fisher, 2007], we
hypothesized direct and indirect victimization not to directly influence participants’ changes in conservatism (HP1). Moreover, building on Roccato et al. [submitted] and on Vieno et al.
[submitted], we expected the interaction between the size of participants’ area of residence (which, based on Sartori, 2003, we considered as a proxy for the social and physical disorder) on the one hand and direct and indirect victimization on the other hand to foster people’s level of conservatism (HP2).
METHOD Data Set and Analyses
We performed a secondary analysis on the data gathered by the Observatory of North-West, a research institute of the University of Turin, on a panel representative of the adult population living in Piemonte, a county located in North-Western Italy (see the www.nordovest.org website for details). The panel was surveyed twice, in January 2005 (T1, N = 2,417) and in January 2006 (T2, N = 2,453). Due to panel attrition and to the deletion of the 209 participants who did not express a voting intention in 2005 and/or in 2006, the resulting data set was composed of 799 people (55% men, mean age = 53.56, SD = 15.91). Table 1 shows the differences between our participants and the Piemonte population (data downloaded from www.regione.piemonte.it) on the main socio-demographic variables.
TABLE 1 ABOUT HERE
In both the waves we analyzed, a question on participants’ voting intention was available. However, this variable was measured on a nominal scale, and thus it did not allow any
quantification of participants’ position on the left-right axis. To achieve this quantification, we used the Itanes (2006: see the www.itanes.org website for details) data, in which a representative sample of the Italian population was interviewed about the position held by the main Italian parties on such axis. Like previously done by Lau and Redlawsk [1997], we considered the mean position given by the most politically expert participants of the Itanes sample as the parties’ “inter-subjective”
position.1 Table 2 shows the frequency and the political rates for the parties we could place: The higher the party’s score, the higher its degree of conservatism. We used as dependent variable the degree of conservatism of the voting intention of our participants at T2.
TABLE 2 ABOUT HERE
Three sets of independent variables, entered in subsequent steps in a moderated hierarchical regression, were used as predictors. In Step 1 we entered participants’ gender (0 = woman, 1 = man), age, education, income (in Euros), and width of the area of residence (0 = < 100,000 inhabitants, 1 = > 100,000 inhabitants), used as control variables. In Step 2 we tested our HP 1 by entering two indexes, respectively assessing the number of direct and indirect victimization experiences occurred to the participant him/herself and to his/her relatives or friends between January 2005 and January 2006. The offences taken into account were: (a) assault, (b) vandalism, (c) burglary in the participants’ home, (d) car theft, (e) pick-pocketing or bag-snatching, (f) robbery, and (g) fraud. In Step 3 we tested our HP2 adding the two interactions between direct and indirect victimization on the one hand and width of the participants’ area of residence on the other hand. The interactions were computed after centring the variables. To rule out a possible alternative explanation of the results, at Step 4 we added eight interactions between direct and indirect
victimization on the one hand and sex, age, education, and income (which we considered as proxy variables for participants’ vulnerability: We considered as vulnerable our participants of female gender, of young age, poorly educated, and with a low income) on the other hand. We used the
1 The political expertise of our sample was computed using the answers to five political knowledge questions, such as “Who is the Italian Prime Minister?” and “How many are the members of the Italian Chamber of Deputies?). We considered participants who correctly answered all the questions as the most politically experts (n = 490, i.e. the 24.4% of the whole sample).
significance of the improvement of our step’s F as criterion to decide if our hypotheses were verified.
RESULTS
Table 3 shows the results of our hierarchical regression. As it was predictable based on the low political and electoral mobility of the Italian population [De Sio, 2006], in all the steps the degree of conservatism of the voting intention our participants expressed in 2005 was the most efficient predictor of that they expressed in 2006. Among the others control variables, being a woman, a senior, and an educated person pushed participants to the left. Consistent with HP1, direct and indirect victimization did not foster our participants’ conservatism. Partially consistent with HP2, the interaction between indirect victimization and width of the area of residence significantly influenced our dependent variable. However, the interaction between direct victimization and width of area of residence did not.
TABLE 3 ABOUT HERE
A simple slope analysis showed that the link between indirect victimization and a positive trend in conservatism was significant among participants living in large towns, simple slope = .091, p < .001, but not among those living in smaller centers, simple slope = -.087, ns. Figure 1
graphically shows this moderation effect. This result did not depend on participants’ vulnerability: Indeed, none of the interaction between direct and indirect victimization on the one hand and the indicators of their vulnerability, we added in a subsequent step, statistically influenced our dependent variable.
FIGURE 1 ABOUT HERE
CONCLUSION
The main purpose of the study we presented in this chapter was to analyze the effect exerted by victimization experiences on the changes of conservatism of people’s voting intention. In line
with HP1 and with previous research results [Langworthy & Whitehead, 1986; Sears et al., 1980; Stack, 2000; Unnever, Cullen, & Fisher, 2007] we did not find any significant main effect of either direct or indirect victimization experiences on our dependent variable. More interestingly, we partially confirmed HP2 finding a significant (although not very strong) effect of the interaction between indirect victimization and the size of the area of residence participants lived in: Indirect victimization experiences led people living in large towns to shift their voting intention endorsing more conservative political parties, while no effect was found among people living in smaller centers.
Even though the “mugging thesis”, according to which “a conservative is a liberal who has been mugged” [King & Maruna, 2009], has been described as “the equivalent of conservative folklore” [Unnever et al., 2007, p. 311] and previous empirical data did not support it [Langworthy & Whitehead, 1986; Stack, 2000], our results—based on hypotheses never tested before this study — showed that the analysis of interaction effects among predictors may help understand the link between victimization experiences and conservatism. While we provided some empirical evidence supporting the core idea of the “mugging thesis”, our results pointed out some specifications that need to be discussed.
First of all, we found an interaction effect only for indirect victimization. This result was consistent with those gathered in the fear of crime research field: It has been shown that coping with indirect victimization may be somewhat harder than coping with direct criminal experience, as the former does not strongly encourage the use of effective coping strategies as much as the latter does [Hale, 1996]. In a recent study on the effects of repeat and multiple victimization, Russo and Roccato [2010] found that indirect, but not direct, victimization has a significant, cumulative effect on the trend in fear of crime. As these authors noticed, the result confirmed the neutralization technique perspective [Agnew, 1985], according to which people tend to cope with the negative effects of victimization, trying to neutralize them. However Russo and Roccato’s results highlighted that, compared to indirectly victimized people, directly victimized people have a paradoxically
easier task: Since the former do not feel the need to actively cope with victimization (e.g. resorting to territorial health services, or looking for help from primary care physicians) the effects of indirect victimization turned out to be more negative than those of direct victimization. Our results
suggested that these effects, beyond influencing people’s quality of life, can influence communities’ and societies’ political governance.
Secondly, only indirect victimized people living in large urban centers tended to shift toward more conservative political preferences. It has recently been shown that victimization consequences may be exacerbated by unfavorable contextual features, considered both at the perceived [Roccato et al., submitted] and the objective levels [Vieno et al., submitted]. As we considered living in large urban centers as a proxy for the spread of physical and social disorder in participants’ area of residence, we suggested that inspecting a disordered community led indirectly victimized people to shift toward conservative parties preference. An explicit test of this effect will be welcome.
From the psychosocial standpoint, consistent with the terror management theory [Greenberg, Pyszczynski, & Solomon, 1986; Stone, 2001] our results confirmed that conservatism may be a “consequence of worldview-enhancing cognitions motivated by the need to buffer with anxiety-inducing thoughts” [Jost et al., 2003, p. 249]. Indeed, our results pointed out that indirect
victimization may be an anxiety-inducing experience, leading people living in areas where social and physical disorders are highly spread to try to cope with it by endorsing conservative parties. Moreover, this interaction effect supported the ideas that the expression of conservative tendencies may vary by situation and that motives to overcome fear and threat are linked to increases in conservatism [Jost et al., 2003].
From the political standpoint, an interesting paradox seemed to emerge from our results: As concerns criminality, the political programs of conservative parties risk to favor their liberal opponents, and vice versa. Indeed, the programs of the former consistently support law and order policies aimed at combating people’s risk of being victimized, even though a large spread of indirect victimization would increase their electoral appeal, at least among urban dwellers. At the
same time, the programs of the latter are typically not centered on tackling the spread of criminality and thus people’s risk of victimization, moving potential voters living in urban areas to the political right.
Even if we have been able to present some new evidence partially supporting the “mugging thesis”, the study had two main limitations. First of all, our sample was not representative of the Italian population, but only tendentially representative of that living in Piemonte. Future research studying a wider representative sample would be very interesting. Secondly, we relied mainly on subjective variables and on a proxy variable for physical and social disorder. New research performed including more specific objective indicators of contextual features and based on a multilevel approach would definitely help to shed some new light on this topic.
Despite the limitations above, our research had two main points. From a theoretic point of view, we provided a first evidence supporting the idea that victimization may have broad political consequences in terms of supporting conservative parties. From a methodological point of view, the literature shows that the detection of interactive effects between predictors can give sophistication and maturity to the scientific literature [Aguinis, Boik, & Pierce, 2001; Judd, McClelland, & Culhane, 1995]. In this research we showed that moderation analysis actually helped us to better explain the complex links between victimization and political preferences. We believe that both these aspects should be considered as useful starting points to get a deeper understanding of the topic.
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Reviewed by Maria Giuseppina Pacilli (Department of Institutions and Society, University of Perugia, Italy)
Table 1.
Differences between the Piemonte Population and the Study Sample
Piemonte Population Study sample
Women 51.5% 45.5%
Mean age 44.31 53.56
(SD = 15.91) Living in towns of >100,000 inhabitants 23.1% 23.1%
Table 2.
Political placing on the left-right axis of the main Italian parties, 2006
Party Mean placing
(SD) Frequency 2005 (percentage) Frequency 2006 (percentage) Rifondazione Comunista 1.32 (1.78) 84 (10.5%) 70 (8.8%) Democratici di Sinistra 2.61 (1.23) 210 (26.3%) 194 (24.3%) Verdi 2.90 (1.48) 26 (3.2%) 32 (4.0%) Partito radicale 2.94 (1.42) 43 (5.4%) 28 (3.6%) Margherita 3.58 (1.44) 93 (11.6%) 101 (12.7%) Unione Democratica di Centro 6.37 (1.78) 23 (2.9%) 37 (4.6%) Forza Italia 8.14 (1.56) 164 (20.6%) 147 (18.4%) Lega Nord 8.46 (1.59) 69 (8.7%) 109 (13.6%) Alleanza Nazionale 8.96 (1.34) 86 (10.8%) 80 (10.1%) Total 799 (100.0%) 799 (100.0%)
Table 3.
Prediction of the changes in participants’ conservatism of the voting intention, 2005-2006
Step 1 (control variables) Step 2 (+ direct and indirect victimization) Step 3 (+ interactions between victimization and width of participants’ area of residence) Step 4 (+ interactions between victimization and participants’ vulnerability) B E. S. Bet a B E. S. Bet a B E. S. Bet a B E. S. Bet a Constant . 597** * . 08 7 . 671** * . 602** * . 09 7 . 562** * . 10 3 Sex -.143* ** . 04 1 -.0 50 -.151 *** . 04 1 -.0 53 -.159 *** . 04 1 -.0 55 -.157 *** . 04 2 -.0 54 Age -.005 . 00 3 -.0 29 -.006 . 00 3 -.0 32 -.006 . 00 3 -.0 34 -.006 . 00 3 -.0 35 Years of education -.024* . 01 2 -.0 10 -.024 * . 01 2 -.0 33 -.026 * . 01 2 -.0 36 -.027 * . 01 2 -.0 38 Income .000 . 00 0 . 00 1 -.000 . 00 0 -.0 03 -.000 . 00 0 . 00 5 -.000 . 00 0 -.0 06 Width of area of residence -.034 . 04 -.0 10 -.026 . 04 -.0 08 -.026 . 04 -.0 08 -.028 . 04 -.0 09
8 8 8 9 Political placement in 2005 . 908** * . 01 4 -.9 16 . 909** * . 01 4 . 91 7 . 906** * . 01 4 . 91 4 . 910** * . 01 4 . 91 8 Direct victimization -.080 . 06 6 -.0 17 -.053 . 07 6 -.0 11 -.019 . 10 0 -.0 04 Indirect victimization -.043 . 02 5 -.0 24 -.004 . 02 8 -.0 02 .002 . 03 4 . 00 1 Direct victimization*widt h of area of residence .064 . 07 7 . 01 4 .062 . 09 0 . 01 3 Indirect victimization*widt h of area of residence .087* . 02 8 . 05 0 . 089** . 02 8 . 05 1 Direct victimization*sex .062 . 09 0 . 01 3 Indirect victimization*sex .033 . 02 6 . 01 9 Direct victimization*age .002 . 00 6 . 00 8 Indirect victimization*age -.000 . 00 2 -.0 03 Direct .017 . .
victimization*educ ation 02 6 02 1 Indirect victimization*educ ation .003 . 00 8 . 00 8 Direct victimization*inco me -.000 . 00 0 -.0 01 Indirect victimization*inco me -.000 . 00 0 -.0 07 Adjusted R2 .843 .843 .846 .846 Improvement of the fit of the model
(2(2)) = .001, ns (2(2)) = 5.283, p < .01 (2(8)) = .468, ns Note. * p < .05, *** p < .001.
Figure caption. Figure 1.
Figure 1.
Note: The slope of the line representing participants living in large towns, but not that representing participants living in small centers, is significant.
