Street youth, strain theory, and crime

Journal of Criminal Justice 34 (2006) 209 – 223

Street youth, strain theory, and crime Stephen W. Baron ⁎ Department of Sociology, Queen's University, Kingston, Ontario, Canada K7L 3N6

Abstract Utilizing a sample of homeless street youth, the study examined a more complete model of the classic strain perspective whereby relative deprivation, monetary dissatisfaction, monetary goals, and objective structural factors lead to crime. It also explored the interactions between these factors and the conditioning effects of peers, beliefs, and attributions. The results revealed that relative deprivation, monetary dissatisfaction, monetary goals, homelessness, and unemployment were related to crime. Further, monetary dissatisfaction and relative deprivation were conditioned by objective economic situations in their relationship with a number of illegal behaviors and interactions between monetary goals and monetary expectations and achievements were associated with crime. The results are discussed in light of the classic strain theories and suggestions are offered for future research. © 2006 Elsevier Ltd. All rights reserved.

Introduction The classic strain theories of Merton (1968) and Cloward and Ohlin (1960) outlined that crime occurs as a result of the failure to reach monetary goals through legitimate avenues. Merton (1968) argued that monetary goals were culturally sanctioned for all in North American society. He suggested, however, that socially structured class differences limited the accessibility of legitimate opportunities to achieve these goals. Individuals in lower class positions were said to be more likely to experience strain manifested as frustration which motivated individuals to seek alternative means to achieve these goals, including illegal means. While strain theory served to stimulate research, it generally produced weak results. Strain in much of this work was measured as the discrepancy between occupational or educational aspirations and expectations for success in these domains (Agnew, 1985; Burton & ⁎ Tel.: +1 613 533 2170; fax: +1 613 533 2871. E-mail address: [email protected]. 0047-2352/$ - see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.jcrimjus.2006.01.001

Cullen, 1992; Farnworth & Leiber, 1989; Hoffman & Ireland, 1995). The findings from this research routinely showed that delinquency was most likely when both aspirations and expectations were low (Agnew, 1985; Burton & Cullen, 1992) results which tended to offer support consistent with control theory. Research utilizing alternative measures of strain, such as perceived blocked opportunities (Burton & Cullen, 1992; Burton, Cullen, Evans, & Dunaway, 1994) or the disjunction between economic goals and educational means (Farnworth & Leiber, 1989) were more supportive of the perspective (although see Jensen, 1995), though results were weakened when competing theories were included in the analysis. The theory's position was further undermined by data showing a mixed relationship between stratification measures including education, income, and unemployment and crime (Agnew, 1994; Hagan, 1992; Tittle & Meier, 1990; although see Elliott & Ageton, 1980; Hindelang, Hirschi, & Weiss, 1979; Mosher, Miethe, & Phillips, 2002). Utilized as measures of access to success through legitimate means, or the achievement

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of success, these mixed findings provided additional evidence to dismiss the classic strain perspective (Agnew, Cullen, Burton, Evans, & Dunaway, 1996). The weak empirical support for strain theory led a number of scholars to focus on problems inherent in previous research (see Agnew, 1992, 1995; Bernard, 1984; Burton & Cullen, 1992; Burton et al., 1994; Menard, 1995). First, many of these scholars argued that the concept of strain was inadequately or improperly measured in prior research. They suggested that support for strain theory might depend on the use of more appropriate measures (see Agnew, 1992, 1995; Bernard, 1984; Burton & Cullen, 1992; Burton et al., 1994; Menard, 1995). Second, critics observed that the research that failed to support the classic strain theories tended to utilize high school students or representative juvenile samples (Agnew, 1995; Burton & Cullen, 1992; Cernkovich, Giordano, & Rudolph, 2000). Observers suggested that classic strain theory might be more relevant to those not in school, to whom money was more of a concern, and to the urban poor, who experienced larger barriers to achieving their goals (Agnew, 1995; Cernkovich et al., 2000; Hagan & McCarthy, 1997a). Limited research on adult samples (see Agnew et al., 1996; Cernkovich et al., 2000) had been somewhat more supportive (although see Burton et al., 1994). Third, most research focused on minor offending and low rate offenders (Bernard, 1984; Burton & Cullen, 1992; although see Cernkovich et al., 2000; Jensen, 1995). In contrast, work in other areas that incorporated more serious measures of crime that were not truncated or restricted in terms of frequency, and included high rate offenders in the sample, tended to uncover a relationship between socioeconomic position and crime (Elliott & Ageton, 1980; Hindelang et al., 1979; Mosher et al., 2002). In this study, a model including measures of strain overlooked in past research was examined utilizing a sample of homeless street youths. Researchers had argued that “some of the most serious and persistent problems of crime and economic adversity are found among” street youths (Hagan & McCarthy, 1997a, p. 128; see also Baron & Hartnagel, 1997; Hagan & McCarthy, 1997b; Whitbeck & Hoyt, 1999). Characterized by features of extreme deprivation, street youth lack shelter, employment, money, and food and have been shown to be “more criminally involved” when compared to school populations (Hagan & McCarthy, 1997b, p. 68; see also McCarthy & Hagan, 1992). Street youth have high rates of participation in serious property offending, violent offending, and drug dealing (Baron & Hartnagel, 1997, 1998, 2002; Hagan &

McCarthy, 1997b; McCarthy & Hagan, 1992; Whitbeck & Hoyt, 1999). Researchers had suggested that street youth crime was often the result of “situational adversity” and linked to objective measures of poverty including homelessness, unemployment, and a lack of income (Hagan & McCarthy, 1997b, p. 92; see also Baron, 2003, 2004; Baron & Hartnagel, 1997, 1998; McCarthy & Hagan, 1991; 1992; Whitbeck & Hoyt, 1999). Researchers had also pointed out, however, that many street youths did not become heavily involved in street crime (Hagan & McCarthy, 1997a). In light of this, Hagan and McCarthy (1997a) argued that exploring why some street youths offended while others did not could significantly advance theoretical understandings of crime. Bernard (1984, p. 368) suggested that strain theories were centered on understanding the actions of “seriously delinquent youth” who were pressured by “primarily structural sources” to engage in crime. The harsh socioeconomic realities of street youth, in tandem with the variation in offending and the inclusion of serious high rate offenders, may, with more discrete measurement, address the critics' concerns and allow the relationships outlined in strain theory to be borne out. Theoretical issues Burton and Cullen (1992) argued that testing the theoretical propositions of the classic strain theories presents the critical problem of how to measure key constructs. Empirical researchers had tended to view individual level strain as the disjuncture between aspirations and expectations. The failure to find empirical support for this type of measurement led to a number of critiques and suggestions for new measures of strain. Several scholars suggested that “Merton's paradigm might be conceived as arguing crime is rooted in ‘relative deprivation’” (Burton et al., 1994, p. 216; see also Blau & Blau, 1982; Currie, 1985; Messner, 1988; Passas, 1995, 1997; Rosenfeld, 1989; Thio, 1975). For example, Burton et al. (1994, p. 217) argued that relative deprivation captured “the essence” of classic strain theory and might be the form of strain closest in kind to that depicted in the “Mertonian” tradition (see also Box, 1987; Burton & Cullen, 1992; Messner, 1988; Passas, 1995, 1997). Here scholars argued that strain would be more likely when individuals believed that they were worse off monetarily than others with whom they compared themselves (see Agnew et al., 1996; Burton & Cullen, 1992; Burton et al., 1994; Burton & Dunaway, 1994; Cohen, 1965; Passas, 1995, 1997). Strain is not only the result of the failure to achieve, but also a

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function of the achievements of those in an individual's comparative reference group(s). “Individuals do not determine whether they are strained or frustrated in isolation; rather, they compare themselves with one another, and such comparisons have a major impact on determining their level of strain” (Agnew, 1997, p. 41). Passas (1997) noted that in North American society there was a significant weight placed on individuals to choose nonmembership reference groups. He argued that the egalitarian ideology and “American Dream,” often led individuals to evaluate themselves with reference to those higher in the stratification system (see also Agnew, 1997) leaving those lower in the stratification system feeling relatively deprived and more at risk for criminal behavior. Relative deprivation is said to lead to both utilitarian and non-utilitarian offenses. While people may engage in property offenses to gain money in an attempt to decrease these feelings, relative deprivation is also thought to be linked to violence because “people are angered by their failure to share in the pronounced wealth that seductively surrounds them but remains beyond reach” (Burton & Cullen, 1992, p. 21). Relative deprivation is thought to generate feelings of resentment and hostility, which in turn may stimulate impulses that are ultimately expressed as violent crime (Baron & Hartnagel, 1998; Blau & Blau, 1982; Braithwaite, 1979; Messner & Tardiff, 1986). Past research on classic strain theory had tended to ignore the importance of relative deprivation and the minimal empirical work provided uneven support. Burton and Dunaway (1994) had a middle-class student sample compare their homes, clothes, and money to “other students” and found relative deprivation to predict general crime, drug use, and a scale combining more serious violent and property offenses. Agnew et al. (1996) exploring a general population sample used a measure that focused on “others” having more money, nicer cars, and nicer homes than the respondents. They found relative deprivation predicted drug use, but not property crime. Burton et al. (1994) also drew on a general population sample and used a similar measure focusing on “people” having more money, nicer homes, and nicer cars. They found that once measures for other perspectives were introduced, relative deprivation predicted neither utilitarian crime nor a combined measure of violent offenses, impaired driving, and public disorder behaviors. Thus, the findings had been somewhat split and too sparse to suggest a pattern. While informative, this research only addressed the critics' concerns regarding measurement. It failed, however, to address their concerns regarding the need to

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examine impoverished populations containing “serious” offenders. Moreover, despite being specifically outlined in theoretical work, none of the recent research had examined the link between relative deprivation and stand-alone measures of violent crime. Agnew et al. (1996) had also critiqued the use of the aspirations/expectations measure. They noted that this type of measure failed to directly tap into individual level strain and incorporated ideal goals that were not likely to be taken seriously by individuals (see also Agnew, 1992). They observed that a careful reading of the classic strain theorists suggested that a more direct measure of strain would be an individual's dissatisfaction or frustration with their monetary status. In fact, Agnew et al. (1996, p. 683) argued that economic dissatisfaction or frustration was “the central variable in micro-level strain theory.” The unhappiness with one's current financial situation was seen as key because it was linked to the “reality of the moment,” not an ideal or future situation suggested in other measures, and this dissatisfaction was more likely to pressure or force people into crime (see Cernkovich et al., 2000, p. 145). Further, Agnew et al. (1996) noted that dissatisfaction or frustration was what distinguished strain theory from theoretical explanations that focused on learning and the freedom to engage in crime. Despite this, they concluded that previous research had all but ignored this measure of strain. The limited work on classic strain theory that had examined monetary dissatisfaction was mixed. Agnew et al. (1996) using a general household sample found a measure incorporating respondents' dissatisfaction with how much money they currently lived on, expected to live on in the future, and an attributional component of blame for monetary problems predicted both drug use and income generating crime. Using a combined household and institutional sample, Cernkovich et al. (2000) tapped into dissatisfaction across a number of domains including employment, educational achievements, material possessions, financial situations, and personal achievements. They revealed that economic dissatisfaction explained the income generating crime of Whites, but not for Blacks whose behavior was better explained by prior crime and incarceration. Wright, Cullen, Agnew, and Brezina (2001) focusing on satisfaction with pay amongst an adolescent sample found no evidence that monetary dissatisfaction led to crime. Thus, the findings appeared supportive in adult populations, but it was unclear if they were related to the behavior of more “at risk” populations and none had examined the effect of monetary dissatisfaction on violent offending.

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The critiques suggested that monetary dissatisfaction and relative deprivation should have direct effects on crime. Agnew et al. (1996) noted, however, that strain theorists had tended to stress the interaction between various factors as leading to crime. Hoffman and Ireland (1995, p. 264) suggested that “it is arguable whether any strain theorists actually develop a direct model” and stressed that examining only direct effects “fails to do justice” to the strain models. Specifically, the theorists had called attention to the combination of high goals and low achievement. In response researchers had operationalized strain as the gap between educational or occupational aspirations and expectations with poor empirical results (see Burton & Cullen, 1992; Burton et al., 1994). Critics argued that these weak results could be explained by researchers failing to incorporate the goal of monetary success into their analysis. Bernard (1984), for example, took exception to past research on strain theory for focusing on the desire for a high education or a prestigious job, instead of the desire for monetary success. Agnew (1994) argued monetary success was central to both Merton's (1968) and Cloward and Ohlin's (1960) strain theory (see Bernard, 1984; Burton & Cullen, 1992; Cernkovich et al., 2000; Farnworth & Leiber, 1989; Hoffman & Ireland, 1995). In fact, Cloward and Ohlin suggested that adolescents prone to delinquency had little concern for occupational or educational success; they simply want money. Greenberg (1977) also argued that adolescents had an immediate desire for money so that they could finance their social activities and purchase a wide range of consumer goods. Thus, while empirical support for the direct effect of aspiration/expectation interactions had been sparse, past research had not used measures that included monetary goals and monetary expectations (although see Burton et al., 1994). Past research had also been criticized for relying heavily on perceived life prospects failing to incorporate objective opportunities and life circumstances (Burton & Cullen, 1992; Cernkovich et al., 2000). Thus, researchers failed to explore interactions that included people's position in the stratification system and their goals (although see Cernkovich et al., 2000). Burton and Cullen (1992, pp. 17–18) stressed that it was essential for researchers “to explore how criminal involvement is linked to not only perceptions but also to the objective and multidimensional opportunity structure in which people are enmeshed.” Thus, as Agnew (1997) argued, the potential for strain increases when individuals have high monetary goals, lack monetary resources, are limited in legitimate avenues for monetary success, and believe they will not be able to reach the monetary goals

through legitimate means (see also Agnew et al., 1996). Strain may also increase when people have high monetary goals and feel relatively deprived and are monetarily dissatisfied (see Agnew et al., 1996; Cernkovich et al., 2000). In one of the few attempts to incorporate both monetary goals and measures of economic attainment, Cernkovich et al. (2000) found several of these interactions were significant predictors of crime, but only for Whites. No work, however, had examined how relative deprivation conditions the direct effect of monetary goals on crime. In a similar vein, Passas (1997) argued that there should be a link between structural location and subjective feelings (see also Messner, 1988). He suggested, for example, that the link between position in the stratification system and relative deprivation and their influence on crime should be explored (see also Agnew et al., 1996). He noted that people's attitudes were “influenced and constrained” by structural sources (Passas, 1997, p. 80). He implied that in societies where social mobility was high, and the adoption of referents beyond one's membership group more common, inequalities were more likely to lead to relative deprivation. Passas (1997) suggested that people with poorer opportunities, or who were not equipped with the means to achieve the cultural goal of success, were more likely to feel relatively deprived. More specifically, he indicated that the “subjectively experienced gravity of these discrepancies” depends on one's position in the social structure (Passas, 1997, p. 65). Relative deprivation then, should have a greater impact on crime the larger the structural barriers that one faces. Messner (1988) suggested that Merton was making a similar argument. He observed that in a social system characterized by universal goals, those individuals with minimal or restricted opportunity were likely to experience greater feelings of relative deprivation. He noted that “because relative deprivation tends to generate deviant motivations, social positions with restricted opportunities and severe relative deprivation should exhibit high rates of deviant behavior” (Messner, 1988, p. 39). This type of argument could be extended to dissatisfaction with monetary status. There may be interactions between monetary dissatisfaction and one's objective economic situation that influences criminal behavior. This suggests that, rather than having a strong direct effect on crime, relative deprivation and monetary dissatisfaction may be conditioned by objective economic measures to impact on crime. To date, no one outside of Agnew et al. (1996) had explored these types of interactions and they failed to test for their direct effects on crime. The lack of empirical support for the

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strain perspective may be related to the failure to incorporate these particular types of measures. Finally, critics noted that research on strain theory failed to incorporate the conditioning influences outlined by the theorists (Agnew, 1995; Agnew et al., 1996). For example, Merton (1968, pp. 191, 201–203) argued that strain was more likely to lead to crime when individuals blamed the social order for their failure to achieve success goals (see also Cloward & Ohlin, 1960, p. 111; Hoffman & Ireland, 1995; Passas, 1997). Those who believe that their employment difficulties or poverty are the result of personal flaws or inadequacies are less likely to react with criminal behavior. In contrast, crime is more likely when people experiencing economic difficulties and poverty believe the system is at fault. Merton (1968), Cohen (1955), and Cloward and Ohlin (1960) also all contended that strain was more likely to lead to crime when an individual's commitment to institutional norms was weak. Hoffman and Ireland (1995, p. 250) noted that in Cloward and Ohlin's version, strain could lead individuals to “withdraw legitimacy from conventional social norms” particularly if they had made external attributions. “Once free of allegiance to the existing sets of rules, such persons may devise or adopt delinquent means of achieving success” (Cloward & Ohlin, 1960, p. 109). With the belief that lawbreaking is wrong weakened, strained individuals will engage in crime. Finally, Cohen (1955), Cloward and Ohlin (1960), and Merton (1968) all argued that criminal peers could have a strong influence on whether strained individuals turn to crime. Cloward and Ohlin (1960, p. 109) noted that youths externalizing blame might seek or develop collective solutions to help them overcome their financial frustrations. Hoffman and Ireland (1995) argued that peer groups might affect perceptions of strain, reinforcing the notion of failure among their fellow peers. Further, peers can provide an environment where the dominant meritocratic ideology is rejected and criminal behavior supported (Cloward & Ohlin, 1960, p. 109). While recent research exploring the broader general strain theory incorporated these conditioning effects with uneven results (see Agnew, 2001; Baron, 2004), these types of interactions had all been but ignored in research examining the classic strain perspective. In the only work to explore for these, Agnew et al. (1996) found a composite variable of criminal peers and beliefs conditioned the impact of monetary dissatisfaction on drug use and income generating crime. Thus, no work on the classic perspective had examined the effect of criminal peers and criminal values separately nor explored for the conditioning effect of attributions. Further, no work had

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examined the conditioning influences of these variables on relative deprivation and its impact on crime. The past work on street youth consistently showed homelessness to be associated with various types of offenses in this population (Baron, 2003, 2004; Baron & Hartnagel, 1997, 1998; Hagan & McCarthy, 1997a, 1997b; McCarthy & Hagan, 1991, 1992; Tyler, Hoyt, & Whitbeck, 2000; Tyler, Hoyt, Whitbeck, & Cauce, 2001; Whitbeck & Hoyt, 1999; Whitbeck, Hoyt, & Yoder, 1999; Whitbeck & Simons, 1990) and there was some evidence of a direct effect of unemployment (see Hagan & McCarthy, 1997b; McCarthy & Hagan, 1992; but see Baron, 2003, 2004; Baron & Hartnagel, 1997, 1998) and a lack of income on crime (Baron & Hartnagel, 1997, 1998). Thus, unlike research on more conventional populations, there appeared to be some relationship between objective measures of poverty and crime. There had been little research, however, focusing on the effects of the subjective facets of deprivation on criminal participation in this population and like the research on other populations, the results were inconsistent. Work exploring monetary dissatisfaction showed the effect to be uneven across offenses (Baron, 2003, 2004) and the direct effect of relative deprivation was either not significant (Baron, 2004) or limited to violent crime (see Baron, 2003). None of this research, however, had explored for the role monetary goals play in the generation of crime. Further, no research on this population had explored the interaction effects between monetary goals and expectations argued to be so central to the classic strain perspective. There had been no work that examined the way objective economic situations condition the impact of monetary goals nor had there been any research that considered the way the alternative subjective measures of strain might interact with monetary goals. Prior research also lacked any examination of how objective situations condition the impact of the alternative subjective measures of strain on crime. The recent critiques suggested that all of these types of interactions might be vital components in fully testing the classic strain perspective. The critiques above suggested a model where objective socioeconomic circumstances (unemployment and homelessness) should have a positive weak to moderate effect on crime. In contrast, subjective interpretations of socioeconomic circumstances (relative deprivation and monetary dissatisfaction) should have a stronger positive effect on crime. The work above also suggested that three types of interactions should impact on crime. First, it is expected that monetary goals interact with low achievement, expectations

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of low achievement, and perceptions of low achievement to predict crime. In particular, high monetary goals will have a greater impact on crime at lower levels of monetary expectations, and at higher levels of unemployment, homelessness, relative deprivation, and monetary dissatisfaction. Second, it is expected that objective economic situations condition the impact of subjective interpretations. In particular, the impact of relative deprivation and monetary dissatisfaction on crime will be greater at higher levels of unemployment and homelessness. Finally, it is expected that the effects of strain on crime, in particular, monetary dissatisfaction and relative deprivation, will be conditioned by external attributions of blame, deviant peers, and deviant beliefs. Methods Critics had noted that past research on the classic strain perspectives focused on high school populations or representative samples of juveniles (see Agnew, 1995; Burton & Cullen, 1992; Cernkovich et al., 2000). They suggested that this focus was a weakness since the theories might be most relevant to explaining the behavior of the urban poor outside of school who face greater barriers to goal achievement (Agnew, 1995; Bernard, 1984; Cernkovich et al., 2000; Hagan & McCarthy, 1997a; Jensen, 1995). Bernard (1984) noted that strain theories were centered on understanding the conduct of “seriously delinquent youth.” He argued (p. 368) that empirical studies that focused on representative juvenile samples “employ weak measures of delinquency and relatively broad definitions of social class.” He noted that youth heavily involved in crime and more serious offenses within such populations would be statistically insignificant. Bernard speculated that for these reasons, research had failed to find a relationship between crime and strain. Homeless street youth have been identified as a population who face great barriers to goal achievement (Hagan & McCarthy, 1997a). It is also a population that has been identified to be more heavily involved in criminal activity than youth from conventional populations (Hagan & McCarthy, 1997b; McCarthy & Hagan, 1992) and are participants in serious offending (Baron & Hartnagel, 1997, 1998, 2002; Hagan & McCarthy, 1997b; Whitbeck & Hoyt, 1999). Thus, they potentially provide for a sufficient number of the relatively rare individuals—high rate serious offenders—that Thornberry and Krohn (2000) argued were often missing in research on crime (see also Mosher et al., 2002). It was these types of offenders that Elliott and Ageton (1980) argued best revealed the significant relationship be-

tween social class and crime. Yet despite their economic marginality, not all homeless street youths are involved in crime (Hagan & McCarthy, 1997a). Thus, while providing the required high rate offenders, the population also potentially provides the variation that would allow one to distinguish the effects of strain on crime. Four hundred respondents (265 male, 135 female) were identified based on four sampling criteria: (1) participants must be aged twenty-four and under; (2) they must have left or finished school; (3) they must be currently unemployed; (4) they have spent time without a fixed address or living in a shelter in the previous twelve months. The rationales for these criteria were (1) to cover the age range of those described as street youth (Baron & Hartnagel, 1997); (2) to exclude those in school and eliminate those not eligible for full-time employment; and (3) to obtain a sample of “serious” “at risk” youth. Data collection The data were collected between May 2000 and August 2001 in a large Canadian city. The study took place in and around the downtown business core of the city in an area that bordered the local skid row and “inner city.” Potential respondents were alerted to the study and screened for eligibility. Those determined to be eligible were provided additional information and invited to participate. Participants were given consent forms that outlined their rights within the interview and summarized the goals of the research. Interviews were conducted in a range of locations including the street, parks, bus shelters, in front of store front social services, and fast food restaurants and averaged seventy minutes in length. Subsequent to the completion of the interview, the respondents were awarded $20 in food coupons at a popular fast food restaurant for their participation. The four hundred youths who were interviewed had an average age of almost twenty years (0 = 19.90). The racial makeup of the sample was predominantly Caucasian (83 percent). Aboriginal youth made up the majority of the other respondents (12 percent).1 The average length of homelessness in the previous twelve months was close to seven months (0 = 6.83). Measuring crime Information on a number of measures of criminal involvement and drug use was obtained via self-reports. Critics noted that research incorporating a wide range of behaviors, including serious offenses, that asks

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respondents to report on actual, not the relative number of times they have engaged in these behaviors, is more likely to uncover the conditions under which socioeconomic status is related to crime (Elliott & Ageton, 1980; Hindelang et al., 1979; Mosher et al., 2002). The respondents were asked how many times in the past year they had done the following: broken into a car, broken into a building, taken something worth less than $50, taken something worth more than $50, broken into a structure to sleep, stolen food, taken a car without permission of the owner, sold marijuana or other nonprescription drugs, used physical force to get money or things from another person, attacked someone with a weapon or fists injuring them so badly they probably needed a doctor, got into a fight, and taken part in a group fight. The raw scores of individual offenses were aggregated across the range of offenses to create a measure of total crime, while those similarly defined by the Canadian Criminal Code were aggregated to create indices of property crime and violent crime. Drug distribution was left as a stand-alone measure. An analysis of the raw frequency distributions for the crime indices suggested a significant amount of variation as well as a high degree of skewness in the measures. While there were some youth not involved in a great deal of crime, there were also a significant number of the high rate offenders. For example, 12 percent had engaged in no property crime, while a quarter of the sample committed three or fewer property offenses. In contrast, about 30 percent engaged in more than one hundred property offenses. Similarly a quarter of the sample reported no violent crime in the prior twelve months,

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while a quarter also reported ten or more violent offenses. About 30 percent of the sample had not sold drugs in the time period examined, but about 40 percent reported five hundred or more transactions over the year. To reduce the skewness in the measures, the index values were logged (see Table 1). To guard against outliers, a sensitivity analysis was conducted during the multivariate analysis and those cases beyond three standard deviations were eliminated. Independent variables Respondents were asked a number of questions having to do with their monetary goals, expectations for future financial success, monetary dissatisfaction, and relative deprivation. Monetary goals were determined by asking the respondents to agree or disagree with the statement, “I would like to make a lot of money in my life” (1 = strongly disagree; 4 = strongly agree). While this measure might suffer from an “unrealistic” aspect criticized in past measures of educational and occupational aspirations, this had been the measure used in the recent research on classic strain theory that had examined monetary goals (see Burton et al., 1994; Wright et al., 2001) and thus provided a comparative component. Monetary expectations were measured by asking the respondents to agree or disagree with the statement, “My chance of making a lot of money in life are not good” (Agnew et al., 1996). To measure respondents' monetary dissatisfaction they were asked to agree or disagree with the statement, “Right now I'm satisfied with how much

Table 1 Means, standard deviations, and ranges for dependent and lower order independent variables Mean Age Gender Monetary dissatisfaction Relative deprivation Monetary goals Monetary expectations Unemployment Homelessness Deviant peers Deviant values External attribution Total crime Property crime Violent crime Drug dealing a b

a

19.90 1.34 2.91 6.98 3.10 2.76 9.80 6.83 3.88 2.70 2.72 5.46 (4640.59)b 3.26 (422.78) 1.56 (25.10) 4.28 (4192.72)

Std. Dev.

Min.

Max.

2.61 .47 .78 2.36 .83 .77 3.01 3.80 1.11 1.22 .74 3.10 (13243.89) 2.26 (2188.99) 1.40 (223.35) 3.78 (13015.20)

13 (− 2.6) 1 (− .7) 1 (− 2.4) 1 (− 2.5) 1 (− 2.5) 1 (− 2.3) 1 (− 2.9) 1 (− 1.5) 1 (− 2.6) 1 (− 1.4) 1 (− 2.3) 0 (0) 0 (0) 0 (0) 0 (0)

24 (1.6) 2 (1.4) 4 (1.4) 10 (1.3) 4 (1.1) 4 (1.6) 12 (.7) 12 (1.4) 5 (1.0) 5 (1.9) 4 (1.7) 12.17 (192014) 10.17 (26206) 8.39 (4400) 12.17 (192000)

The mean for the standardized variables is 0 with a standard deviation of 1. Ranges for standardized variables are in brackets. The numbers inside of the parentheses are raw scores. The numbers outside of parentheses are the logged values of the raw scores.

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money I have to live on” (1 = strongly agree; 4 = strongly disagree) (Agnew et al., 1996). Cantril's (1965) “commonly used” self anchoring striving scale utilized by Walker and Mann (1987, p. 277; see also Cantril, 1965) to measure relative deprivation was used here. As an egoistic measure of relative social rank, Walker and Mann argued that this measure could be important in determining individual level behavior and attitudes. In particular, their findings in a sample of unemployed suggested that this measure tapped the individual stress symptoms that helped explain the actions and beliefs of deprived individuals. In light of the argument that relative deprivation is said to lead to crime through the hostility and resentment that it creates (Baron & Hartnagel, 1998; Blau & Blau, 1982; Braithwaite, 1979; Messner & Tardiff, 1986) respondents were asked, “On a scale from 1 to 10 where 1 is the worst possible rank in Canadian society and 10 is the best possible rank in Canadian society, where do you stand right now?” The lower the nominated position on the ladder, the greater the deprivation. This was then reverse coded so that higher scores reflected greater perceptions of deprivation. Respondents were also asked a number of questions having to do with their economic situations. To determine the length of homelessness, respondents were asked, “How many months in the last year (anchor) did you live in a shelter or have no fixed address?” Length of unemployment was determined by asking the respondents how many months during the past year that they were out of work. Finally, the respondents were also asked about the variables thought to condition some of the other measures. Deviant values were determined by asking respondents, “How wrong do you think it is to break the law?” (very wrong = 1; not wrong at all = 5). To determine the number of deviant peers, youths were asked, “How many of your current friends have been picked up by the police?” (1 = none; 5 = all). To determine external attributions of goal blockage, respondents were asked to agree or disagree with the statement; “Every time I try to get ahead, something or someone stops me” (1 = strongly disagree; 4 = strongly agree) (see Burton et al., 1994). The classic strain theories call for a number of interaction effects (Agnew, 1995; Agnew et al., 1996; Cernkovich et al., 2000). First, the theories emphasize that monetary goals interact with low achievement or expectations of low achievement. Strain should be greatest when individuals place an emphasis on monetary goals while at the same time lacking the legitimate means for obtaining money, have low future

monetary expectations, view themselves as relatively deprived, and monetarily dissatisfied (Agnew et al., 1996; Cernkovich et al., 2000). To explore this, interactions were created between monetary goals and (1) unemployment, (2) homelessness, (3) monetary expectations, (4) relative deprivation, and (5) monetary dissatisfaction. Second, scholars stress the importance of objective economic situations conditioning the impact of subjective feelings (see Agnew et al., 1996; Burton & Cullen, 1992; Passas, 1997). To explore for this, two interactions were created between relative deprivation and (1) unemployment, and (2) homelessness. Two more interactions were created between monetary dissatisfaction and (1) unemployment, and (2) homelessness. Finally, scholars had also noted that strain would be conditioned by deviant peers, deviant attitudes, and external attributions (Agnew et al., 1996; Hoffman & Ireland, 1995). To examine this, interaction terms were created between relative deprivation and (1) deviant peers, (2) deviant attitudes, and (3) external attributions as well as between monetary dissatisfaction and (1) deviant peers, (2) deviant attitudes, and (3) external attributions. Aiken and West (1991) outlined that interaction terms in multiple regression produce large standard errors in the lower-order independent variables. Further, they produce multicollinearity between the interaction terms and the lower order variables from which they were created. Both of these issues can lead to potential problems in computation. To address these issues, they recommended standardizing all of the lower-order variables and developing the interaction terms by multiplying the standardized scores of the relevant variables. Following their procedure, interaction terms were created by first standardizing the lower order independent variables by transforming them into zscores and then multiplying the relevant standardized variables together2 (see Table 1). The analysis proceeded with each of the four dependent variables (total crime, property crime, violent crime, and drug dealing) regressed on the set of lowerorder predictor variables. Following the lead of Cernkovich et al. (2000; see also Paternoster & Mazerolle, 1994), the interaction terms were then entered singly into the equations with the standardized lower-order variables and tested for their explanatory contribution. One-tailed tests are used where the direction of the relationships between the independent and dependent variables have been predicted and twotailed tests for nonhypothesized ones, including any relationship whose direction is opposite to expectation.

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Results Table 2 presents the results of the main effects without the interaction terms. An examination of Table 2 reveals that the strain measures, monetary dissatisfaction and relative deprivation, are related to crime. First, those who reported greater monetary dissatisfaction were more likely to be involved in property crime. Second, those who indicated that they felt relatively deprived were more likely to report greater property offending, violent offending, and total offending. Table 2 also reveals the objective economic circumstances to be predictors of crime. Unemployment was significantly related to total crime while homelessness was related to property crime. The results also showed that street youths with strong monetary goals were more involved in violent crime, drug dealing, and total crime. Deviant peers and deviant attitudes were related to all four offenses. Respondents who made external attributions for their strain also engaged in more violent offending. Expectations of future financial success, however, were not related to offending behavior. An examination of the interaction effects measuring high aspirations and low expectations and achievements suggested that one interaction term was consistently related to crime (see Table 3). The monetary goals/ monetary expectation interaction term was related to three of the four dependent variables: violent crime, drug dealing, and total crime. When monetary expectations were lower (e.g., one standard deviation below the mean), the relationship between monetary goals with the various types of crime was strong and positive (see Aiken & West, 1991 for post hoc probing of interac-

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tions). The results also revealed that the interaction term between monetary goals and homelessness was related to drug dealing. Further, the interaction term between monetary goals and unemployment was related to total crime. The other interaction terms in this set were not significantly related to crime. Table 4 summarizes the set of interaction effects where the objective economic circumstances condition the two measures of strain: relative deprivation and monetary dissatisfaction. The results revealed a general pattern where objective economic circumstances increased the impact of strain on crime. First, the relative deprivation/homelessness interaction was related to all four of the dependent variables. Second, the monetary dissatisfaction/unemployment interaction was significantly related to violent crime, drug crime, and total crime. Finally, the monetary dissatisfaction/homelessness interaction was significantly related to all four offenses. The third set of interaction effects where deviant peers, deviant values, and external attributions conditioned the two strain measures revealed only a handful of the interactions to significantly predict crime (results not shown). First, deviant peers conditioned the impact of relative deprivation on violent crime (Beta = .101; sig .05). The more deviant peers street youth had the greater the effect of relative deprivation on violent offending. Deviant values interacted with relative deprivation to predict drug dealing (Beta = − .097; sig .05). The effect of this interaction, however, was in an unexpected direction. Probing revealed that at levels of deviant values one standard deviation below the mean, relative deprivation had a strong positive relationship with drug

Table 2 OLS regression, total crime, property crime, violent crime, and drug dealing (standardized effects shown with unstandardized effects in parentheses)

Age Gender Monetary dissatisfaction Relative deprivation Monetary goals Monetary expectations Unemployment Homelessness Deviant peers Deviant values External attribution Adjusted R2 N ⁎ sig .05 one-tailed test. ⁎⁎ sig .01 one-tailed test. + sig .05 two-tailed test. ++ sig .01 two-tailed test.

Total crime

Property crime

Violent crime

Drug dealing

.048 (.148) − .072 (− .224) .029 (.089) .080 (.246) ⁎ .136 (.419)++ .069 (.211) .091 (.281) ⁎ .016 (.049) .198 (.609) ⁎⁎ .269 (.828) ⁎⁎ .052 (.161) .165 396

− .020 (−.044) .040 (.086) .082 (.177) ⁎ .081 (.175) ⁎ .065 (.139) .015 (.033) .032 (.068) .194 (.385) ⁎⁎ .197 (.430) ⁎⁎ .302 (.657) ⁎⁎ − .024 (−.052) .210 392

−.137 (− .175) −.169 (− .216)++ −.020 (− .026) .093 (.154) ⁎ .158 (.201)++ .009 (.012) −.029 (− .037) .078 (.100) .164 (.211) ⁎⁎ .235 (.301) ⁎⁎ .148 (.190) ⁎⁎ .182 391 ++

.125 (.470) − .034 (−.129) .021 (.078) .057 (.215) .122 (.460)+ .050 (.189) .075 (.286) − .015 (−.055) .161 (.607) ⁎⁎ .254 (.961) ⁎⁎ .079 (.297) .134 396

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Table 3 OLS regression interaction terms for monetary goals conditioned by expectations/achievements (standardized effects shown with unstandardized effects in parentheses)

Monetary goals × monetary expectations Monetary goals × unemployment Monetary goals × homelessness Monetary goals × relative deprivation Monetary goals × monetary dissatisfaction

Total crime

Property crime

Violent crime

Drug dealing

− .077 (−.187) ⁎ .078 (.258) ⁎ .059 (.181) − .029 (−.077) − .006 (−.016)

− .066 (−.122) .016 (.037) .037 (.080) − .006 (−.011) .012 (.021)

−.109 (− .110) ⁎⁎ .028 (.037) −.027 (− .034) −.044 (− .048) .063 (.067)

− .097 (− .288) ⁎ .061 (.245) .079 (.297) ⁎ − .078 (− .253) .011 (.034)

⁎ sig .05 one-tailed test. ⁎⁎ sig .01 one-tailed test.

dealing. Finally, external attributions interacted with monetary dissatisfaction to predict drug dealing (Beta = .081; sig .05). The influence of monetary dissatisfaction on drug dealing was greater when respondents blamed others for their predicament. Discussion This article set out to examine classic strain theory by incorporating measures of strain neglected in past research and applying them to a marginal population “at risk” for crime. The findings showed that measures of strain such as monetary dissatisfaction, and more consistently relative deprivation, were significant predictors of crime. Further, the effects of these measures were consistently increased when they were conditioned by poor objective economic circumstances. This supported Passas's (1997) argument regarding the link between subjective feelings, structural location, and crime (see also Messner, 1988) and illustrated the weakness of past research that had failed to include these types of measures and these types of interactions. The findings also lent some support for the measure of strain where the discrepancy between monetary goals and expectations for financial success was associated with criminal behavior. Further, there was evidence that a discrepancy between monetary goals and actual achievements was associated with criminal behavior although these were not generalizable across offenses.

These findings supported the arguments of Bernard (1984) and Agnew (1994) who criticized past research for not focusing on monetary goals despite their centrality in the strain perspective (see also Cernkovich et al., 2000; Hoffman & Ireland, 1995). Less supportive, however, were findings that revealed the interactions terms between goals and perceptions of achievement (relative deprivation and monetary dissatisfaction), were not predictive of crime. Compared to the other types of interactions explored, support for the impact of strain when conditioned by external attributions, deviant peers and deviant values was more limited. There was some evidence that those who perceived relative deprivation and who interacted with greater numbers of deviant peers were more likely to engage in crime as were those who were monetarily dissatisfied and blamed others for their situation. This supported the traditional strain argument (Cloward & Ohlin, 1960) as well as more recent revisions of the perspective (see Hoffman & Ireland, 1995). This type of interaction also produced an unexpected finding: at lower levels of support for deviant activities, those with perceptions of relative deprivation engaged in more drug dealing. These youths' sense of injustice appears so great that they will engage in activities they believe to be morally wrong to right this sense of injustice. Overall, the conditioning effects of deviant peers, deviant values, and external attributions were more specific than general.

Table 4 OLS regression interaction terms for regression interaction terms for relative deprivation and monetary dissatisfaction conditioned by homelessness/ unemployment (standardized effects shown with unstandardized effects in parentheses)

Relative deprivation × unemployment Relative deprivation × homelessness Monetary dissatisfaction × unemployment Monetary dissatisfaction × homelessness ⁎ sig .05 one-tailed test. ⁎⁎ sig .01 one-tailed test.

Total crime

Property crime

Violent crime

Drug crime

.033 (.101) .118 (.362) ⁎⁎ .110 (.361) ⁎⁎ .113 (.369) ⁎⁎

− .002 (−.004) .091 (.195) ⁎ .038 (.087) .076 (.173) ⁎

.074 (.093) .096 (.121) ⁎ .114 (.154) ⁎⁎ .083 (.112) ⁎

.038 (.144) .095 (.355) ⁎ .103 (.416) ⁎ .090 (.361) ⁎

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The current findings suggested that objective measures of deprivation were not strong consistent predictors of crime. While the findings showed that objective measures of deprivation, in particular homelessness and unemployment, can be related to crime, it appeared that most of their influence emerged when they conditioned perceptual measures of deprivation. As Tittle (1995) observed in his critique of strain theory, whether people conform or not depends on the accuracy with which they perceive reality rather than objective deprivation. The findings also suggested that placing a strong emphasis on economic success is associated with criminal behavior. This seems to support the “anomie” portion of Merton's theory (Messner, 1988; Wright et al., 2001). According to Merton (1968) the “extreme cultural emphasis” on monetary success can foster criminal conduct by decreasing normative regulation. As Durkheim (1951, p. 284) argued, unlimited and unattainable goals lead to negative feelings that drive individuals into crime and suicide. Messner and Rosenfeld argued that the “intense cultural pressure for monetary success” decreases controls and motivates individuals to pursue success through the “most expedient means” (Messner & Rosenfeld, 1994, p. 85). Thus, having economic goals does not act as a buffer to crime, as would be expected from a control perspective, instead they appear to be criminogenic in this population and as alluded to above, their effects are enhanced by expectations that they will not be reached. Some of the variables thought to condition the subjective deprivation variables had a direct relationship with crime (Agnew, 1997; Agnew et al., 1996; Cloward & Ohlin, 1960; Cohen, 1955; Merton, 1968). Deviant attitudes and peers were associated with all of the offenses examined. This suggested that other factors beyond strain might be operating to produce crime pointing to the need to consider other theoretical perspectives in tandem with strain theory. The findings both support and raise questions about the classic strain perspective and some of its extensions. First, it appears that the main effect of one of the alternative measures of strain, relative deprivation, is a more consistent predictor of crime in this population than is monetary dissatisfaction. Both of these measures, however, are quite successful at predicting crime when they are conditioned by objective socioeconomic circumstances suggesting that these are the types of interactions that need to be explored further in future work on strain theory. The findings also help one understand the continued failure of aspiration/expectation measures utilized in past research. Substituting

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monetary goals and expectations for educational and occupational measures appears to be a more appropriate route (see Cernkovich et al., 2000). Further, the results suggest that including interactions between monetary goals and actual achievements, while uneven here, may be a fruitful avenue for future exploration. In contrast, similar to work on general strain theory (see Agnew, 2001), there appears to be more limited support for the expected conditioning effects of peers, values, and attributions. This leaves open for question the importance of these types of interactions. The results also point to the need to examine monetary goals in the direct generation of crime. Anomie theory has been applied mainly to macro-level research (although see Brezina, Piquero, & Mazerolle, 2001), but may have individuallevel implications. The significant interactions uncovered in this research were important because it could be argued that the perspective could not be adequately assessed without their inclusion (see Agnew et al., 1996; Hoffman & Ireland, 1995). Further, the results suggested that certain types of interactions were strong predictors across a number of types of crime, others predictive capacity was somewhat more limited, or restricted, and yet others appeared to be poor predictors of crime. It might be argued that the sheer number of interactions proposed by the theorists might lead to some emerging as significant by chance. McClelland and Judd (1993) had pointed out that it was difficult in field research to detect interaction effects. This was particularly the case for interaction effects that explain an appreciable proportion of the variation in the dependent variable. In light of the fact that the method utilized here to detect interaction effects was quite conservative (see Agnew, Brezina, Wright, & Cullen, 2002; Mazerolle & Maahs, 2000), the findings here were impressive. In total, 32 percent of the interactions tested (nineteen out of sixty) had direct effects on various types of crime. More important, the significant interactions provided a pattern that suggested their importance within strain theory. The discrepancy between monetary goals and monetary expectations was a consistent predictor as were interactions between relative deprivation and unemployment, monetary dissatisfaction and unemployment, and monetary dissatisfaction and homelessness. The first of these interactions had only rarely been tested and its direct effect was not significant (Burton et al., 1994) or not tested (Agnew et al., 1996). In contrast, the three interactions involving perceptions of deprivation and objective economic circumstances had never been tested in prior research. Together these four interactions were

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significant in fourteen out of their sixteen tests suggesting that they were a key component of strain theory. A limitation of this research like other recent research on classic strain theory (see Agnew et al., 1996; Burton et al., 1994; Burton & Dunaway, 1994; Cernkovich et al., 2000) was that the data were cross-sectional, meaning that current perceptions of dissatisfaction and deprivation were being correlated with past criminal behavior. It may be the case that participation in criminal activities serves to heighten perceptions of deprivation and increase levels of monetary dissatisfaction as well as adopt deviant values and associate with deviant peers. Thus, one cannot draw direct causal inferences regarding the temporal order of the variables. Burton and Cullen (1992, p. 8) noted that it was unclear if strain theory was processual or static. “If the theory is conceived as being static—that is, the social state of strain and its effects are constant across time and space —then a methodology that employed a ‘snap shot' of a person's life would be adequate.” They observed that researchers had assumed the theory was static, making the cross-sectional self-report survey consistent with this assumption. Some support for this can be found in longitudinal work. Agnew (1989, p. 383) for example, discovered in his longitudinal analysis of revised strain theory that adversity was “a relatively stable variable.” Thus, asking about current strain rather than strain over a prior period of time might be sufficient. Further, research incorporating panel studies revealed that “selfreport delinquency measures yield stable and consistent results from one time period to another” (Mosher et al., 2002, p. 123). This suggested that the current measures of strain should be related to future crime to at least some degree in the short term. If the theory were processual, however, the goal would be to examine, over time, how the various social situations outlined in the theory alienate people from the conventional society and make them more vulnerable to crime. It would also allow for the exploration of the effects of prior social and criminal experiences on current situations as well as the time order link between objective conditions, perceptions, and crime (see Burton & Cullen, 1992; Hoffman & Ireland, 1995). Caution should also be taken in interpreting the findings since a number of the key measures were drawn from single items. The strain items were drawn from previous research on classic strain theory (see Agnew et al., 1996; Burton et al., 1994; Wright et al., 2001) or work on other impoverished populations (Walker & Mann, 1987), so they should have some validity and reliability (see Hagan & McCarthy, 1997b). Further, a

growing body of research suggested that homeless respondents did provide valid and reliable data when participating in surveys (see Calysyn, Allen, Morse, Smith, & Tempelhoff, 1993; Hagan & McCarthy, 1997b). In terms of the dependent variables, studies of more serious drug/crime participants consistently found that respondent's self-reports were “surprisingly truthful and accurate” (Inciardi, Horowitz, & Pottieger, 1993, p. 66). While this type of population was likely to produce crime data less reliable than that from conventional populations (Braithwaite, 1981), research on self-reports (see Hindelang, Hirschi, & Weiss, 1981) suggested that it was sufficiently reliable to rank offenders and determine etiological relationships. Further, research had determined that studies that asked questions about serious offenses, did not restrict response categories, did not request information beyond a one-year period, and used face-to-face interviews provided the best and most complete data on serious offenders (Huizinga & Elliott, 1986). Despite potential limitations, this work was important because unlike past research it included both objective and perceptual factors, and it tested for the interactive properties. The findings were also important because, compared to the previous research on strain theory, they were derived from a difficult to reach sample of higher crime-risk youth using measures of more serious offenses (although see Cernkovich et al., 2000; Hagan & McCarthy, 1997b). The type of sample was important because classic strain theories might be best applied to understand the behavior in this type of population (Agnew, 1995; Bernard, 1984; Cernkovich et al., 2000). As Thornberry and Krohn (2000, p. 40; see also Mosher et al., 2002, p. 123) noted, one of the rarely met challenges of self-report data is to have a sample that contains an adequate number of the rather uncommon “high-rate serious offenders most likely to come to the attention of authorities.” Saying this, the results reveal, even in this population, that crime is highly skewed. This may help to explain the failure of past research to uncover a relationship between socioeconomic status and crime. If high rate offenders are rare, even in lower socioeconomic locations, then they may become lost in the data, obfuscating the relationship between class and crime. It is also the case that this study had only examined the effects of strain at the lower end of the socioeconomic spectrum. It might be that by restricting the sample to this population the variation had been compressed, limiting the results. The non-probability sampling techniques utilized can also be seen to limit the generalizability of the

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findings. Street youth are not a population amenable to traditional social science sampling techniques. One method adopted to combat this issue was to draw a large sample that would provide some population variability as well as a reduction in the sampling error that might result from these techniques (Baron & Hartnagel, 1998). Hagan and McCarthy (1997b) noted that there was a growing body of literature showing that this population could be accessed utilizing survey research. Further, since there was variation in their experiences, research that focused “exclusively” on street youth could be used to determine the causal processes linked to their criminal behavior (Hagan & McCarthy, 1997a, 1997b). While recognizing the need for caution, they suggested that findings derived from these types of samples could then be utilized to determine whether further research should be undertaken to re-explore and verify certain relationships. These findings, however, were not generalizable to the broader youth population. Hagan and McCarthy (1997b) noted that neither conventional nor street youth samples alone would be able to provide the full information required to understand crime. Thus, future work should strive to incorporate broader or comparative samples to provide greater variation that would allow for the exploration of the effects discovered here across different types of populations. It may be that some of the effects are important regardless of position in the social structure while others are more strongly linked to class position. Finally, some caution may need to be exercised because Merton focused his argument on the United States and the data here were Canadian. Research comparing the national characters of the two countries, however, suggested that the “argument for the existence of distinct national characters requires extensive rethinking (Baer, Grabb, & Johnston, 1993, p. 27; see also Baer, Grabb, & Johnston, 1990). Findings by Baer et al. (1990, 1993) showed few important divisions or significant national differences in values based on political boundaries. They noted that these similarities might be explained not only by geographical proximity, but also by (except Quebec) language and exposure to the same (predominantly American) media and popular culture (Baer et al., 1993, p. 29). Macionis and Gerber (2002, p. 281) noted that “Canadians share, to some extent, the belief that those who apply themselves can ‘get ahead’” and that “there is equality of opportunity and widespread upward mobility” (Macionis & Gerber, 2002, p. 269). Scott, Swartz, and Vanderplaat (2000, p. 233) noted that in Canada, the myth of opportunity for all to advance through effort is fostered,

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reinforced, and promoted throughout the media and popular culture. Children learn from family, peers, school, and the media to value and pursue material success, wealth, and the status that comes from it (Gartner & Dawson, 2004, p. 501; Teevan & Harman, 2001, p. 115). Thus it would seem that these data were applicable to the American case to at least some degree. While one might expect some differences, the evidence on the links between other factors, including objective measures of poverty, and crime in the street youth population in the two countries had generally produced similar results (see Baron, 2003, 2004; Baron & Hartnagel, 1997, 1998; Hagan & McCarthy, 1997a, 1997b; McCarthy & Hagan, 1991, 1992; Tyler et al., 2000; Tyler et al., 2001; Whitbeck & Hoyt, 1999; Whitbeck et al., 1999; Whitbeck & Simons, 1990). Future work would do well to continue in both countries to uncover the generalizability between the stress on economic success and crime.

Acknowledgements The author would like to acknowledge the financial assistance of the Social Sciences and Humanities Research Council of Canada and the Queen's University Chancellor's Research Award. The author would also like to thank the anonymous reviewers for their comments. Thanks to Kelli Phythian and Jennifer Robinson for research assistance. A version of this article was presented at the Canadian Conference on Homelessness, Toronto, 2005. Notes 1. Aboriginals were drastically overrepresented in the sample. According to Peters and Murphy (1993), only about 1 percent of the youths in the city schools were native. 2. A correlation matrix of the interactions and the lower order variables from which they were created was examined. This table is available from the author upon request. It revealed that there were no zero order correlations above .24 and an examination of the variance inflation factor scores suggested that any existing collinearity between variables would not degrade their estimates.

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