Assessing gender and ethnic differences in developmental trajectories of offending
| Author | Anna M Ferrante |
| Date | 01 December 2013 |
| DOI | 10.1177/0004865813490948 |
| Published date | 01 December 2013 |
| Subject Matter | Articles |
Article
Australian & New Zealand
Journal of Criminology
46(3) 379–402
Assessing gender and ethnic
! The Author(s) 2013
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DOI: 10.1177/0004865813490948
trajectories of offending
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Anna M Ferrante
Centre for Data Linkage, Curtin University and Crime Research
Centre, University of Western Australia, Australia
Abstract
Research on diversity in offending patterns is crucial given ongoing polemical debates con-
cerning the relationship between gender, ethnicity and crime. Competing theoretical per-
spectives, limited supporting evidence and inconclusive or contradictory findings from prior
research point to the need for more empirically-grounded, generalizable research which
compares and contrasts offending patterns across and within gender and ethnic groups.
The current study applies a semi-parametric group-based modelling approach to a large,
longitudinal dataset of offenders to determine if, and how, offending trajectories vary
across gender and ethnic sub-groups. Findings suggest that some trajectory attributes (e.g.
number and shape) are shared across gender/ethnic groups, while other trajectory attributes
(height, peak age) are not. An exploratory investigation of the risk factors associated with
trajectory group membership finds that few of the available factors discriminate between
trajectories either within or across gender/ethnic offender groups. The findings fill a knowledge
gap, particularly in relation to offending patterns in Australia. Invariance in trajectory risk
factors present a challenge to taxonomic theories of offending.
Keywords
ethnicity, gender, Indigenous status, offending frequency, offending trajectories
Introduction
Despite the fact that gender and ethnic status (race) emerge as strong correlates of crime,
explanatory models and theories which account for gender and ethnic differences vary
widely. In terms of gender disparities, some scholars maintain that the processes leading
to male and female offending are equivalent and that gender differences are predomin-
antly due to differing levels of exposure to the same underlying factors. However, an
alternate line of reasoning maintains that female delinquency arises from some distinct-
ively different causes and follows uniquely ‘gendered’ pathways (Adler, 1975; Belknap
and Holsinger, 2006; Carrington, 2006; Chesney-Lind, 1997; Daly, 1994; Mann, 1984;
Corresponding author:
Anna M Ferrante, Centre for Data Linkage, Curtin University, GPO Box U1987, Perth 6845 Western Australia.
Email: a.ferrante@curtin.edu.au
380
Australian & New Zealand Journal of Criminology 46(3)
Smart, 1990; Steffensmeier and Allan, 1996). On-going debate between perspectives
underscores the need for more investigation of gender differences in offending
(Fitzgerald et al., 2012). Further trends in offending such as rising rates of violent
crime amongst women, add to the impetus to explore differences between and within
gender groups (Fitzgerald et al., 2012; Odgers et al., 2007).
Similarly, there is a need to explore racial/ethnic-based differences in offending.
US studies show that minority groups have increased rates of delinquency and dispro-
portionately high levels of involvement in the justice system (Kempf-Leonard, 2007). In
Australia, there is overwhelming evidence of Aboriginal over-representation in official
offending (Blagg et al., 2005; Ferrante and Loh, 2001; Harding et al., 1995; Luke and
Cunneen, 1995; Skrzypiec and Wundersitz, 2005). Despite this evidence, there are dif-
fering international and Australian perspectives regarding the causes of these ethnic
differences. Some scholars favour explanations based on traditional theories of crime;
others favour hypotheses which attribute cause to culturally-specific or other unique
factors (e.g. systemic bias; see Ferrante (2013) for a more complete discussion). Yet
others account for ethnic disparities through other mechanisms. Piquero, Moffitt and
Lawton (2005b), for example, argue that it is the ecological context that different ethnic
groups live in that gives rise to more pronounced anti-social behaviour in one group than
in another. They argue that ethnic difference in ‘ecological context’ refers also to differ-
ences in family structure, and community and neighbourhood context. A by-product of
different family structures across ethnic groups is reduced supervision and, ultimately,
failed socialization.
This ecological explanation of ethnic difference is consistent with that presented in a
number of developmental, group-based theories of offending (e.g. Moffitt, 1993;
Patterson, 1982). Moffitt (1993) argues that institutionalized racism and poverty select-
ively affect minority groups, particularly African Americans. Such factors have a nega-
tive effect on early life socialization and development (e.g. poor neurological health in
childhood) and on the quality of parenting, leading to difficulty in ‘attaining roles of
consequence and respect’. In other words, for ethnic minorities, adverse structural con-
ditions operate to restrict life chances over the life-course (e.g. less access to pre-natal
care, more exposure to environmental toxins, attenuated familial bonds due to socio-
economic stress, more exposure to disadvantaged schools, fewer employment opportu-
nities), making it more likely that individuals from these groups engage in life-course
persistent offending.
The range of alternative explanatory models for racial differences in offending empha-
sizes the need for further quantitative analyses of these issues. As Piquero and Brame
(2008: 395) maintain, ‘the relevant question is not whether race group differences can be
attributed solely to differential involvement or selection. Rather, the key analytic task is
to document the contribution of both mechanisms to the patterns observed in different
populations at different time points’.
Trajectory models
Researchers in the life-course/developmental domain have shown considerable interest
in exploring offending patterns ‘in different populations at different [life] time points’.
This interest has been spurred by statistical developments (i.e. the advent of trajectory
Ferrante
381
modelling techniques) and by the emergence of several taxonomic theories of offending
proposing different age-related patterns of development for different groups (e.g.
Moffitt, 1993; Patterson, 1982). An abundance of studies exploring offending over the
life-course have followed, many using a semi-parametric group-based trajectory method
(SPGM; Nagin and Land, 1993). Piquero (2008) recently reviewed more than eighty
offending trajectory studies undertaken between 1993 and 2005. Most of the studies were
located in the US (Eggleston et al., 2004; Laub and Sampson, 2003; Piquero et al., 2001,
2002); however, some were based elsewhere, for example England, the Netherlands
(Blokland, 2005; Francis et al., 2004). The studies employed a varied array of sampling
frames (offender-based/general population), data sources (self-report/official records)
and covered various periods of the life-course (childhood/adolescence/adulthood).
Although there were variations in the way that the trajectory models had been applied,
Piquero (2008) concluded that:
the use of group-based methods to estimate trajectories of criminal activity over the life-
course suggests that there is a fair degree of consistency among and across a wide range of
samples with respect to group number and shape but the length of follow-up and age range
may affect substantive conclusions regarding the shape of the trajectory (though this no
fault of the methodology per se). (Piquero, 2008: 48)1
Despite the surge in trajectory research, few studies have examined gender differences in
offending trajectories, and only a handful of studies have examined differences based on
race or ethnicity.
Gendered trajectories
There are few studies of female offending trajectories and results are mixed (D’Unger
et al., 2002). An early study by Silverthorn et al. (1999) posited that female offending
differed from male offending in that it followed a single (not dual) trajectory in which the
onset of offending was delayed until adolescence. Fergusson and Horwood (2002) fitted
five different trajectory groups to a general population sample and found that trajec-
tories were similar for males and females, as were the correlates associated with trajec-
tory membership. However, females offended at a lower rate than males and were more
likely to follow low offending risk and early adolescent-limited pathways. Males, on the
other hand, were more likely to follow later adolescent-limited or chronic offending
pathways. From the evidence, they concluded that the general developmental factors
associated with female offending were similar to the development and aetiology of male
offending.
Consistent with Fergusson and Horwood (2002), but in contrast to Silverthorn et al.
(1999), Eggleston and Laub (2002) found that the same trajectory groups existed for
boys and girls; however, the proportion of offenders following each of the distinct
trajectories varied across gender. A different set of findings emerged from a study by
D’Unger and colleagues (2002). Using data from the Second Philadelphia Cohort study
(3,000 females; 1,000 males), the researchers identified three offending trajectories that
were common to both boys and girls – non-offenders, high-rate adolescent-peak offen-
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