‘African gangs’ in Australia: Perceptions of race and crime in urban neighbourhoods

Abstract

In 2016, Melbourne experienced what was referred to in the media as the Moomba ‘riot’. This event led to a racialised political and media campaign regarding the problem of ‘African gangs’. Despite no evidence of actual gang activity, the backlash against black migrants in Melbourne was consequential with increases in reported racism and institutionalised forms of discrimination. In this study, we examine the neighbourhood context of exclusion against African Australians following the Moomba ‘riot’. Using census and crime data integrated with survey data from 2400 residents living in 150 urban neighbourhoods, we interrogate the relationship between sentiments (measured as anger) towards Africans and perceptions of neighbourhood crime and disorder. We further consider whether quality contact with Africans and neighbourhood cohesion mediates this relationship. We conclude with reflections on the significant and deleterious effects of the ‘black and criminal’ association on understandings of ‘Africanness’ in Australia.

Keywords

African community problems discrimination immigration racism

Introduction

In 2007, Liep Gony, a young South Sudanese man, was murdered in Melbourne. At this time, the South Sudanese community was criticised by the Federal Minister for Immigration and Citizenship for failing to integrate into Australian society as the incident was deemed to be gang related (Baak, 2018; Wright, 2007). Despite it later being revealed that two white men were responsible for the murder, the politician refused to apologise for the comments and much of the media surrounding the incident depicted the South Sudanese community as a ‘problem’ group rather than being the victim (Windle, 2008).

Nearly a decade later, the 2016 Moomba ‘riot’ again brought South Sudanese Australians into the media and political spotlight. Media attention around young African Australians in the aftermath of the ‘Moomba riot’ conveyed negative stereotypes of the group. This was due to the visibility of youth in the disorder which unfolded in Melbourne’s Federation Square on the Saturday night of the 2016 Moomba Festival: primarily young people of South Sudanese and Pacific Islander backgrounds who engaged in acts of public disorder and vandalism (see Travers, 2016). The images that circulated in the media the following morning captured the moment as police officers deployed capsicum spray to disperse a crowd of young people in Federation Square. In the days and weeks that followed, a dominant media narrative emerged in several Australian media outlets that located responsibility for this disorder and a recent ‘surge in crime rates’ (Mills & Willingham, 2016) with the so-called Apex gang, the members of which were reported to be ‘predominantly of South Sudanese descent’ (Cowie et al., 2016). Since the events of Moomba, there has been an intense and consistent political and media focus on African (primarily South Sudanese) young people in Victoria and in other parts of Australia. While only a small number of offenders of African descent were officially known to police for their offending, the labelling of people from Africa as ‘criminal’ had dire consequences on the sense of identity and belonging for many in the community. Many instances of youth disorder committed by someone of colour were related to ‘African gangs’ and this led to increased discrimination and overt expressions of hostility levelled towards people of African appearance (Benier et al., 2018; Macaulay & Deppeler, 2020; Majavu, 2020).

In Australia and elsewhere, crimes committed by newly arrived immigrants or minorities are often attributed to the failure of particular groups to ‘settle’ into Australian life (Collins & Reid, 2009). An emerging theme from the international literature on the criminalisation of immigrant minorities in western countries is that problematic social constructions of ethnic criminality are linked to the fear of the stranger or ‘other’ (Bowling & Phillips, 2002; James, 2002; Webster, 1997). This then leads to anti-immigrant sentiment towards these groups. In a study conducted in Australia in 2015, 77% of South Sudanese people who participated in this research (n = 166) reported that they had experienced discrimination in the past 12 months (Markus, 2016a, p. 60). Similar patterns were also reported by those from Zimbabwe, Kenya, Ethiopia, as well as Indigenous Australians. These findings highlight the impact of visible difference of skin colour on the prevalence of prejudice.

Scholars argue that people consciously or unconsciously behave in discriminatory ways (Chugh, 2004; Rudman, 2004). These actions are largely driven by erroneous assumptions or stereotypes that associate particular groups with social problems. Some studies find a strong association between the mere presence of ethnic minority groups in the neighbourhood and how people ‘see’ or understand disorder (Sampson & Raudenbush, 2004; Wickes et al., 2013). For example, Sampson and Raudenbush (2004, p. 336) find that reports of disorder are largely predicted by the racial/ethnic composition of a neighbourhood as residents ‘supplement their knowledge with prior beliefs informed by [the] racial stigmatization’.

This study focuses on the racial stigmatisation and the social exclusion of African Australians in Melbourne – one of the most diverse cities in the world. We explicitly examine the relationship between an individual’s sentiments towards African Australians and whether feeling anger towards this group influences how they perceive and understand problems in their neighbourhood. Given the unique context of the situation in Melbourne, we enhance the existing literature on prejudice in Melbourne by considering whether this relationship is mediated by both the level of contact with African Australians and the level of social cohesion in the neighbourhood. The aim of this paper is to examine the neighbourhood context of exclusion of African Australians following the Moomba ‘riot’ and media attention. Specifically, we hypothesise that residents who have higher anger towards Africans will report greater levels of crime and disorder in their neighbourhood. This relationship will be mediated by quality contact with Africans and neighbourhood cohesion. Here, we draw on Allport’s (1954) ‘contact hypothesis’, noting the findings by previous studies that intergroup contact decreases prejudice and intergroup bias (Pettigrew & Tropp, 2006; Pettigrew et al., 2011; Zhou et al., 2019). In the context of developing socially cohesive neighbourhoods, we further hypothesise that social contact may mitigate harmful attitudes towards ethnic communities, in this case – African migrants in Australia.

Literature review

A long-standing racist narrative that synonymises Blackness with criminality is widespread in the empirical literature, in both Australia and internationally (Dixon & Maddox, 2005; Majavu, 2020; Phillips & Bowling, 2012). Across the global Black Diaspora, Eurocentric narratives may demonise darker skinned populations as both a social problem and a burden on Western societies (Majavu, 2020). Scholars argue that these racialised narratives underpin enduring anti-Black stereotypes that position Blacks as ‘dangerous outsiders’ (Fleury-Steiner et al., 2009; Majavu, 2020). This portrayal exists in Australia for both Indigenous Australians¹ and African migrants. Aboriginal populations have consistently faced high rates of prejudice and have a disproportionate presence in the Australian criminal justice system (Cunneen & Tauri, 2016). For example, Indigenous Australians represent 27% of the Australian prison population, despite making up less than 3% of the Australian population (Australian Law Reform Commission, 2018). Comparably, Sudanese and South Sudanese youth account for 1% of the state’s alleged criminal offenders while making up 0.1% of Victoria’s population (Crime Statistics Agency, 2018). Reports have drawn attention to the significance of the ‘age-crime curve’, noting that 42% of the South Sudanese population in Victoria are under the age of 25 (RMIT ABC Fact Check, 2018; Shepherd et al., 2018; Shepherd & Spivak, 2020). Like Indigenous Australians, African men are also more likely to be overpoliced with Gordon (2012) finding that African men living in the Melbourne suburbs of Flemington and North Melbourne were 2.5 times more likely to have their actions recorded by the police than the rest of the population.

African migration and identity in Australia

Before Australia’s Federation in 1900, there were a small number of Black Africans who had migrated to Australia, either as escaped slaves from the United States or as convicts sent by the British (Pybus, 2006). Although small in number, Africans were specifically mentioned in debates about immigration restrictions in the first years of the Commonwealth (Jakubowicz, 2010). This added to the underlying fear of non-whites and the eventual passing of the Immigration Restriction Act 1901 (Rivett, 1975). This act, which later came to be colloquially referred to as the ‘White Australia Policy’, restricted any legal non-white immigration, limiting Black African migration to Australia. This policy had limited impact on white South African migration to Australia, which increased steadily throughout the 1900s (Wasserman, 2018). By 1947, Australia was a white-majority nation with only 2.7% of the Australian population born outside Australia, Ireland or the United Kingdom (Inglis, 2004). During this time, non-whites were targets of xenophobia and were persecuted as aliens or deported (Udah, 2018). Following the abolishment of the White Australia Policy in the 1970s, Australia had an influx of migrants. Black African immigration to Australia was relatively recent, flourishing in the 1990s. Population data from the 2016 Australian census indicate that African-born residents equate to approximately 1.6% of the Australian population, with the majority originating in Southern and Eastern African countries (Australian Bureau of Statistics, 2017).

Despite the ethnic diversification that has occurred over the last several decades, scholarship continues to demonstrate that being Black in Australia complicates social acceptance (Ndhlovu, 2013) and can be a disadvantaging social factor (Colic-Peisker & Tilbury, 2008). The African diaspora in Australia constitutes a group of heterogeneous people, however, uniformly they are grouped because of their blackness. In this sense, ‘Africanness’ is perceived in the essentialised context of ‘Blackness’ (Gebrekidan, 2018) and ‘to speak of one is to invoke the other’ (Mbembe, 2017, p. 38). However, Africanness is more than just skin or phenotypic features; it is socially constructed in opposition to whiteness (Mapedzahama & Kwansah-Aidoo, 2017) and is ‘synonymous with negative things, from death to dirty, from foul to unholy … [it] is placed upon a whole group of people’ (Alabi, 2005, p.12). The idea of ‘Africa’ is tarnished by a ‘map of stereotypes’ in which all African migrants have been associated with an imagined place of disease, conflict, war, poverty and famine (Jakubowicz, 2010). Wearing (2012) notes that these constructions rely upon a history and social context of racist and discriminatory assumptions that are built into Australian culture and society (p. 26). Mapedzahama and Kwansah-Aidoo (2017) call this the ‘Burden of Blackness’ whereby African migrants are made responsible for things that they have no control over – their (Black) bodies, their race and their ancestors. They are forced to endure judgements that have historically been misrepresented in the Western world as part of the social imaginary (Ibrahim, 2004) that has been created and circulated for Black populations. Others refer to this process as stigmatising, whereby the distinction of human differences and the separation between ‘us’ and ‘them’ is linked to discrimination and the application of status loss (Phelan et al., 2008). This stigmatisation provides fertile ground for discourses that associate Black migrants with danger and crime (Majavu, 2017; Windle, 2008), as a ‘threat to social cohesion’ (Hobday, 2007), a ‘stranger to Australian society’ (Nunn, 2010), a ‘non-desired other’ (Ndhlovu, 2013) and belonging to ‘gangs’ (Ndhlovu, 2014) to flourish.

Portraying a ‘culture of violence’ and the exclusion of African migrants

In the media, Black populations are often constructed as being predisposed to criminality (Udah, 2018). Incidents of Melbourne youth crime were classified as ‘African gang’ crime, constituting a racialisation of these crimes by the media (Majavu, 2020). Windle (2008) analysed patterns of media reporting on African youth in Australia, finding that a common narrative amongst the media was to present violence as being ‘ethnic-related’ and ‘race-based’. For example, Windle describes an article in The Age which quotes Assistant Commissioner Paul Evans as claiming that ‘investigators were dealing with a tribe mentality among refugees who had come from a culture of boy soldiers and social violence’ (Evans, 2007, p. 3). This framing situates African youth as being inherently violent and prone to conflict based on their country (or rather, continent) of origin. African migrants’ alleged predisposition to violence is often coupled with narratives of poverty and tribal culture (Windle, 2008). According to Windle (2008), news reports often liken the violence being portrayed by African youth to African American gang rap culture. Sudanese youth are described as not displaying traditional Sudanese culture, instead they are ‘mimicking the African-American culture’ (Farouque & Cooke, 2007, p. 3). Here, the criminality of Black Africans in Australia is directly compared to Black Africans in America as a source of gang culture that is aspired to. These constructions of Black Africans as predisposed to criminality position the Black African migrant as a danger to ‘the Australian nation and the national identity’ (McMaster, 2002, p. 34).

Current literature has drawn attention to the largely negative experiences that Africans have in Australia, highlighting the racialised, criminalised and discriminatory experiences that shape the way they move through and interact with other Australians (for examples see: Baak, 2018; Gebrekidan, 2018; Kwansah-Aidoo & Mapedzahama, 2015, 2018a; 2018b; Macaulay & Deppler, 2020; Majavu, 2017, 2018, 2020; Mapedzahama & Kwansah-Aidoo, 2017; Ndhlovu, 2014). In particular, studies have drawn attention to the amplification of racial stigmatisation through the African gangs narrative that has created moral panics amongst the Australian community (Benier et al., 2018; Macaulay & Deppeler, 2020; Mapedzahama & Kwansah-Aidoo, 2017). Scholars have also noted that the media coverage that has sensationalised the African gangs narrative rarely features the voices of African young people themselves, rending them ‘invisible and inaudible’ (Nunn, 2010, p. 189). It is through these media representations that the public comes to ‘know’ African migrants, creating moral panics that place them outside the Australian community (Nunn, 2010).

It is clear from the literature that African migrants in Australia experience high levels of racial discrimination (Baak, 2018; Majavu, 2018, 2020; Udah, 2018). This has particularly been felt in and across neighbourhoods, with African migrants reporting that Australian neighbourhood life is unfriendly, unwelcoming and alienating (Majavu, 2017, p. 61). Evidence from the 2015–2016 Challenging Racism Project (Blair et al., 2017) demonstrates that sentiments towards Africans in Australia are hardly welcoming. This study found that 21% of 6001 respondents ‘agreed that African refugees increase crime in Australia’ and 16.1% felt ‘somewhat negative or very negative’ towards African Australians. We argue here that these negative sentiments are representative of the implicit biases towards Africans in Australia. Implicit bias is defined as ‘introspectively unidentified (or inaccurately identified) traces of past experiences that mediate favourable or unfavourable feeling, thought and action toward social objects’ (Greenwald & Banaji, 1995, p. 8). Unlike overt prejudice, implicit biases can operate without intention or conscious awareness (Rudman, 2004; Tate & Page, 2018) and as such are highly pervasive (Greenwald & Krieger, 2006). Implicit bias becomes as significant problem when individuals form associations, despite empirical evidence often reflecting otherwise, that lead to the discrimination of particular groups in society.

Two processes may prevent associations formed through implicit bias – both of which involve interpersonal contact. The first is creating meaningful opportunities for contact between those who may hold biases against particular groups with members of those groups. Second is the development of social cohesion across the community by promoting acceptance and trust of all members of society.

Allport’s (1954) ‘contact hypothesis’ proposes that under optimal conditions, contact between different racial/ethnic groups could reduce prejudice. It was initially proposed that four conditions must be met to facilitate positive intergroup contact: the equal status of intergroup participants, awareness of common goals, cooperation across groups and the availability of institutional support (Allport, 1954). While later research suggests that not all of these conditions are necessary, the core idea that bringing groups together in meaningful ways helps to reduce stereotypical attitudes, perceptions of threat and prejudice has been demonstrated to be empirically robust. A meta-analysis conducted by Pettigrew and Tropp (2006) found overwhelming support for the claim that increased intergroup contact decreases prejudice. The quality of contact also matters. Intergroup friendship has proven to be very effective in reducing intergroup bias (Pettigrew et al., 2011). As importantly, intergroup friendships have a contagion effect, such that people with secondary social relationships (through another in-group member) with out-group members enhance that individual’s attitudes towards the out-group (Zhou et al., 2019).

The context in which inter-ethnic contact takes place might also be important for reducing prejudice and harmful attitudes towards ethnic minorities. Social cohesion in communities provides a fertile soil for network development and group functioning (Coleman, 1988; Putnam, 2001). While there is no agreed definition of social cohesion, it is commonly understood as a pro-social good that represents a sense of belonging and attachment and brings about positive outcomes for the collective (Markus, 2016b). In essence, it symbolises a working trust and a general willingness of residents to work together (Sampson et al., 2002). Thus, a socially cohesive environment may provide the necessary levels of trust to encourage people from different backgrounds to connect and form meaningful relationships, which may in turn mediate the relationship between harmful sentiments towards particular groups and their association with neighbourhood problems. We investigate this premise in the analyses that follow.

Despite no evidence of actual gang activity in the aftermath of Moomba, the backlash against black migrants in Melbourne has been consequential with increases in reported racism and institutionalised forms of discrimination. The aim of this paper is to examine the neighbourhood context of the exclusion of African Australians following the Moomba ‘riot’ and subsequent media attention. Specifically, we test the hypothesis that residents who have higher anger towards Africans will have high perceptions of crime and disorder in their neighbourhood. We also assess whether contact with African migrants can mediate the relationship between negative sentiments towards Africans and perceptions of disorder, and further, if living in a socially cohesive neighbourhood offers a protective factor against the harmful association between negative sentiments and perceptions of disorder. Based on previous research, we hypothesise that quality contact with Africans and neighbourhood cohesion will reduce the strength of the relationship between anger towards Africans and disorder.

Methods

Research site

Melbourne is the second largest city in Australia, with 4.485 million residents of which 40.2% of whom were born overseas (Australian Bureau of Statistics, 2017). Melbourne is known for its diversity, with 38.0% of residents speaking a language other than English (LOTE) at home, and 64.6% of residents had one or both parents born overseas (Australian Bureau of Statistics, 2017). It is also home to the largest concentration of South Sudanese migrants with the 2016 census showing 8416 Sudanese and South Sudanese-born migrants live in Victoria, the majority of which reside in Melbourne (Australian Bureau of Statistics, 2017).

Australian Community Capacity Study

The Australian Community Capacity Study is a is a longitudinal study of community processes, crime and disorder in neighbourhoods in Melbourne and Brisbane. The multi-million-dollar project is funded by Australian Research Council and Victorian Department of Premier and Cabinet. This study uses the data from Wave 2 of the Melbourne study, collected in 2017. It includes 2525 randomly selected residents living across 151 suburbs in the Greater Melbourne Region. The survey was conducted via a mail out survey that could be returned by post or completed online. The survey was available in English and top five languages in Melbourne (Simplified and/or traditional Chinese, Greek, Italian, Arabic and Vietnamese). The overall response rate for the survey was 23%.

Analytic strategy

The analyses that follow employ multilevel mixed effects models in Stata 15. We use data from the Australian Community Capacity Study at the individual level, and neighbourhood level data from the 2016 Australian Bureau of Statistics Census and crime incident data from the Crime Statistics Agency, Victoria.

Dependent variable

The community problems scale measures ‘How much of a concern is <problem> in your neighbourhood?’. The question is repeated for drugs; public drinking; people loitering and hanging out; people being harassed because of their skin colour, ethnic origin or religion; people being attacked because of their skin colour, ethnic origin or religion; vandalism and/or graffiti; traffic problems like speeding or hooning²; young people getting into trouble; and young people from new immigrant groups getting into trouble. For each of these items, participants were asking to indicate whether they are ‘no problem’ (1), ‘somewhat of a problem’ (2) or ‘big problem’ (3). A scale was constructed with their average response. The values ranged from 1 to 3, with a mean of 1.719 (SD = 0.478). The scale has a high internal consistency at α = 0.90. All items loaded on one underlying factor (eigenvalue 4.64) with all factor loadings between 0.584 and 0.786. This scale, originally adapted from the General Household Study, is used extensively in the criminological literature (for example Oidjarv, 2018; Piquero, 1999; Taylor, 2000), including studies in Australia (for example Hipp & Wickes, 2018; Wickes et al., 2018; Wickes, Hipp, et al., 2017).

Independent variable

Our independent variable is anger towards African people. This item asked respondents to rate their anger towards African people on a scale from No Anger (1) to Anger (7). The mean was 2.740 (SD = 1.839).

Mediating variables

In the models, we employ two variables as mediators. The first is quality contact with African people, measured at the individual level as ‘How would you rate the quality of your experiences with African people?’ (No Contact/Negative Contact/Neutral Contact/Positive Contact). We also include a score of neighbourhood cohesion, which was calculated as a neighbourhood latent score from a previous wave of the study (Wickes et al., 2020). This was measured by people’s agreement to the following four statements – people in this community are willing to help their neighbours; this is a close-knit community; people in this community can be trusted; and people in this community do not share the same values (reverse coded).³ Descriptive statistics for all variables are provided in Table 1.

Table 1.

Summary statistics of variables employed.

	Binary
	Yes		No
Female	1555 (61.61%)		969 (38.39%)
Children	632 (24.76%)		1920 (75.24%)
Language other than English	385 (17.30%)		1840 (82.70%)
Born overseas	701 (27.85%)		1816 (72.15%)
	Categorical
Education	High school or belowTrade, tech cert or diplomaUniversity qualifications		609 (24.27%)560 (22.32%)1340 (53.41%)
Political affiliation	Liberal/National partyLabor partyGreensOther		614 (24.76%)595 (23.99%)314 (12.66%)957 (38.59%)
African contact	No contactNegative contactNeutral contactPositive contact		973 (38.86%)299 (11.94%)493 (19.69%)739 (29.51%)
	Continuous
	Mean	Std Dev		Min	Max
Community problems	1.718	0.478		1	3
Anger towards African	2.740	1.839		1	7
Age	56.824	16.069		18	95
Neighbourhood social cohesion	0.1366	0.225		–0.562	0.727
Neighbourhood crime rate (/100,000)	4772.023	3143.694		402.555	33,194.65
Neighbourhood proportion under 30% income (%)	23.248	7.051		12.902	49.549
Neighbourhood unemployment (%)	3.546	1.122		0.546	7.110
Neighbourhood mobility (%)	53.897	10.581		13.989	71.780
Neighbourhood LOTE (%)	10.878	9.270		0.831	51.020

Additional control variables

We also control for several individual characteristics. These include age, gender, children (yes/no), employment status (full time/part time/not in the labour force/pension or unemployed), education status (high school or below/trade, technical certificate or diploma/university qualifications), speaking a LOTE at home, being born overseas and political party preference (Liberal-National party/Labor party/Greens/other). We also controlled for the neighbourhood factors associated with social disorganisation, including the percentage of residents who speak a LOTE at home, percentage of residents who have moved in the last 5 years, percentage of unemployed residents who are seeking work, the percentage of households that fall in the lowest 30% of incomes in Melbourne and the total crime rate per 100,000 population over the 2015–2017 period. These neighbourhood variables were taken from the 2016 ABS census and the crime rate employed data from Victoria Police.

Models

The first analysis examines the baseline model using the individual control variables. Second, we include the neighbourhood control variables. We then include anger towards Africans. We add our mediator variables, contact with Africans and social cohesion within the neighbourhood, in subsequent models. All results are presented in Table 2.

Table 2.

Model results.

	Model 1	Model 2	Model 3	Model 4	Model 5
Age	B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)
Female	B = 0.050 (SE = 0.020)**	B = 0.053 (SE = 0.020)**	B = 0.062 (SE = 0.020)**	B = 0.007 (SE = 0.020)***	B = 0.071 (SE = 0.020)***
Children	B = 0.022 (SE = 0.025)	B = 0.031 (SE = 0.025)	B = 0.029 (SE = 0.025)	B = 0.028 (SE = 0.025)	B = 0.029 (SE = 0.025)
Employment	B = 0.007 (SE = 0.011)	B = 0.004 (SE = 0.011)	B = 0.004 (SE = 0.011)	B = 0.007 (SE = 0.011)	B = 0.003 (SE = 0.011)
Education	B = –0.024 (SE = 0.013)	B = –0.024 (SE = 0.013)	B = –0.007 (SE = 0.013)	B = –0.010 (SE = 0.013)	B = –0.007 (SE = 0.013)
LOTE	B = –0.017 (SE = 0.029)	B = –0.025 (SE = 0.029)	B = –0.029 (SE = 0.029)	B = –0.028 (SE = 0.029)	B = –0.026 (SE = 0.029)
Born OS	B = –0.044 (SE = 0.023)	B = –0.049 (SE = 0.024)*	B = –0.034 (SE = 0.024)	B = –0.032 (SE = 0.024)	B = –0.034 (SE = 0.029)
Political affiliation (ref: coalition)
Labor	B = –0.075 (SE = 0.027)**	B = –0.079 (SE = 0.027)**	B = –0.052 (SE = 0.027)	B = –0.058 (SE = 0.027)*	B = –0.057 (SE = 0.027)*
Greens	B = –0.102 (SE = 0.034)**	B = –0.111 (SE = 0.034)***	B = –0.083 (SE = 0.025)**	B = –0.078 (SE = 0.025)*	B = –0.067 (SE = 0.034)*
Other	B = 0.001 (SE = 0.025)	B = –0.001 (SE = 0.025)	B = –0.001 (SE = 0.025)	B = –0.002 (SE = 0.025)	B = –0.001 (SE = 0.025)
Crime rate (/100,000)		B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)	B = 0.001 (SE = 0.001)
% English at home		B = 0.002 (SE = 0.002)	B = 0.002 (SE = 0.002)	B = 0.002 (SE = 0.002)	B = 0.004 (SE = 0.002)*
% mobility		B = –0.003 (SE = 0.002)	B = –0.003 (SE = 0.002)	B = –0.003 (SE = 0.002)	B = –0.003 (SE = 0.002)
% unemployed		B = 0.090 (SE = 0.023)***	B = 0.085 (SE = 0.023)***	B = 0.085 (SE = 0.023)***	B = 0.066 (SE = 0.020)**
Household income		B = 0.008 (SE = 0.003)***	B = 0.009 (SE = 0.003)***	B = 0.009 (SE = 0.003)***	B = 0.005 (SE = 0.003)*
Anger Africans			B = 0.049 (SE = 0.006)***	B = 0.041 (SE = 0.006)***	B = 0.041 (SE = 0.006)***
African contact (ref: no contact)
Negative contact				B = 0.159 (SE = 0.032)***	B = 0.157 (SE = 0.033)***
Neutral contact				B = 0.038 (SE = 0.027)	B = 0.038 (SE = 0.027)
Positive contact				B = 0.036 (SE = 0.024)	B = 0.033 (SE = 0.024)
Social cohesion					B = –0.452 (SE = 0.083)***
AIC	2352.457	2297.000	2163.105	2140.819	2108.758

*p < 0.05.

**p < 0.01.

***p < 0.001.

Results

To investigate the spatial distribution of perceptions of community problems, we first ran a null model. This calculated an intra-class correlation coefficient of 0.214, suggesting that 21% of the variation in perceptions of community problems was attributable to the neighbourhood in which the respondent lives.

In Model 1, we examined the impact of the individual characteristics on perceptions of problems (Akaike Information Criterion [AIC] = 2352). The results of the models are presented in Table 2.⁴ The individual level variables are significantly associated with perceptions of community problems (Wald χ²(10) = 38.59, p < 0.001). In this model, increased perceptions of community problems were linked to gender (with females more likely to perceive increased problems; B = 0.05, p < 0.05) and political party with those who vote Labor (B = –0.074, p < 0.01) and the Greens (B = –0.102, p < 0.01) less likely to perceive problems than those who vote for the Liberal/National coalition. Other variables of age, employment and education status, born overseas and LOTE were non-significant.

Model 2 adds the suburb level control variables (AIC = 2297). Here, being female and political preference retain significance. Being born overseas was also significant, with those born overseas perceiving less community problems (B = –0.049, p < 0.05). At the neighbourhood level, the percentage of unemployed residents (B = 0.090, p < 0.001) and the percentage of low-income residents (B = 0.008, p < 0.01) were associated with the increased perceptions of problems within a neighbourhood. This aligns with a significant body of scholarship on perceptions of disorder (Franzini et al., 2008; Latkin et al., 2009; Sampson & Raudenbush, 2004; Wickes et al., 2013).

In Model 3, we add anger towards African residents (AIC = 2163). Anger towards Africans significantly increased the perceptions of community problems (B = 0.049, p < 0.001). This did not change the effect of other variables, with exception to political preference as those who favour the Labor party was no longer significant. Being female (B = 0.062, p < 0.01), voting for the Greens (B = –0.083, p < 0.01), neighbourhood unemployment (B = 0.085, p < 0.001) and percentage of residents with low income (B = 0.008, p < 0.001) retained significance.

Model 4 includes the use of contact with Africans as a mediating factor. In this model (AIC = 2140), those who had negative contact with Africans were significantly more likely to perceive community problems than those who with no contact (B = 0.159, p < 0.001). The addition of this variable did not change the significance with other variables, and anger towards Africans remained significantly associated with perceptions of community problems (B = 0.042, p < 0.001). Other control variables were still significant, including being female (B = 0.070, p < 0.001), preference for the Labor party (B = –0.058, p < 0.05) or the Greens (B = –0.078, p < 0.05), neighbourhood unemployment (B = 0.083, p < 0.001) and neighbourhood low income (B = 0.009, p < 0.001).

In the final model, we examine the impact of neighbourhood social cohesion and trust, in addition to contact with Africans, as a mediating factor on the relationship between anger towards Africans and perceptions of community problems (AIC = 2108). Social cohesion and trust within their suburb significantly reduced an individual’s perceptions of problems within their community (B = –0.452, p < 0.001). Contact with Africans remained significant for those who had negative contact (B = 0.157, p < 0.001). However, even with the significance of the mediator variables, anger towards Africans still remained highly significant with a z score of 6.98 (B = 0.041, p < 0.001). Other control variables remained significant, including being female (B = 0.071, p < 0.001), preference for Labor (B = –0.057, p < 0.05) or the Greens (B = –0.067, p < 0.05), neighbourhood unemployment (B = 0.066, p < 0.01) and neighbourhood low income (B = 0.005, p < 0.05). In this model, the percentage of residents in the neighbourhood who only speak English at home was also significant, with a greater proportion of English speakers associated with an increase in perceived community problems (B = 0.004, p < 0.01).

In a subsequent analysis of the final model, we also tested a cross-level interaction between contact with Africans and neighbourhood social cohesion. This was non-significant. This is an interesting finding as it illustrates that the overarching context of the neighbourhood in which the individual lives does not affect their perceptions in the same way that is true of other groups.⁵

Discussion

Recent research into the aftermath of the political and media spotlight surrounding the Moomba 2016 and subsequent ‘African gangs’ phenomenon has highlighted the detrimental nature of this attention for the African communities, particularly the South Sudanese community (Benier et al., 2018). Our research further highlights how the ‘African gangs’ media coverage may have led to development of anti-African sentiments in Melbourne post the Moomba incident. Our findings clearly demonstrate that both anger towards Africans (likely to be a result of media exposure⁶) and political preference are strongly linked to the perceptions of community problems. We also identified that negative contact with Africans was associated with increased perceptions of community problems, although neutral or positive contact did not alter people’s perceptions. The non-significance of positive contact is noteworthy here as it stands in contrast to a significant body of literature that shows the positive benefits of meaningful contact between in-groups and out-groups (Pettigrew & Tropp, 2006; Pettigrew et al., 2011; Zhou et al., 2019). This may be because there is already a deeply embedded bias in Australia that links being black with problems of crime and delinquency (Majavu, 2020; Mapedzahama & Kwansah-Aidoo, 2017). This ‘readiness’, combined with the extensive and harmful media and political rhetoric surrounding Liep Gony’s death and the Moomba riot, has likely impeded the benefits that usually follow from positive contact.

In the context of the ‘African gangs’ narrative, we argue that the mainstream media was responsible for increasing hostilities towards minority groups by consistently publicising stories that highlight racial difference, feeding people’s pre-existing insecurities and fear of the unknown. That is, the media appears to have used racism as part of their business models to attract profit. This intention is not novel – we have previously seen the media focusing on stereotyping of Black bodies in Australia with Indigenous Australians associated with perceptions of gang activity and violence (Cannon, 2018; Cunneen & Russell, 2017; Sercombe, 1995). It is only recently that we have seen this shift to migrant Africans, many of whom arrived between 2000 and 2008 (Munro, 2018). Similar to the stories that were conveyed about disadvantaged Indigenous Australians, many stories about South Sudanese Australians highlight their status as refugees who had been displaced by conflict and war. This continued association of dark skin tone with poverty and problems merely serves to reinforce the perceived racial hierarchy that exists in society (American Psychological Association, 2017; Steains, 2018).

The ‘othering’ created by a racial dichotomy of Blackness further distances the African community from white Australians who perceive the African migrant as a threat to the national homogeneity. This is associated with the work of George Yancy, who argues that white Americans, regardless of their intentions, benefit from racism and are often subvertly racist in ways they do not understand (Yancy, 2015). The hypervisibility of African Australians, in both everyday interactions in society, along with exaggerated media coverage, means that Africans receive a disproportionate amount of attention. Though our data do not allow us to state with certainty that media consumption is linked to an individual’s anger, a limitation of the study, we do argue that the positioning of Africans alongside criminality has allowed for the stigmatisation of an entire group of migrants, who come from diverse backgrounds, to be banded together under one label. It is disconcerting that this study illustrates that contact and neighbourhood social cohesion do little to ameliorate the association.

The importance of social cohesion to the maintenance of neighbourhood social order is supported by research undertaken in different cultural and social contexts (Gorman-Murray & Waitt, 2009; Steenbeek & Hipp, 2011). Studies find that social cohesion mediates structural characteristics, such as neighbourhood disadvantage or ethnic heterogeneity, on perceptions of crime and disorder (Morenoff et al., 2001; Wickes et al., 2013). We therefore hypothesised that neighbourhood social cohesion would mediate the relationship between our participants’ reports of anger towards Africans and their perceptions of disorder. While we did find that social cohesion provided a protective effect, whereby residents reported lower disorder when they lived in cohesive neighbourhoods, social cohesion did not mediate the effect of individual’s feelings of anger on their reports of disorder. Again, this social cohesion finding points to the durable and harmful effect of the continued positioning of blackness with crime. It also demonstrates that wider political, social and economic forces matter for how local problems are understood.

Another key finding in this study is evidence of a strong relationship between politics and perceptions of disorder. We argue that our findings demonstrate how the increasing politicisation of race and ethnicity in Australia erodes inclusion and encourages discrimination. In almost all models, a political preference for the Greens (a party for social justice and ecological sustainability) or Labor (the centre-left party) was significantly associated with a decreased perception of the prevalence of community problems. In Australia, as is the case internationally, the law and order campaigns promulgated by parties to the right have real consequences on how people may ‘see’ and engage with their social world. While political attention around immigration is arguably fairly consistent, Australia has recently seen an increased intensity around immigration politics, with several key party-leading politicians arguing that a rise in immigration is a threat to the Australian cultural identity. The presence of Africans in the community represents a visible minority group that are seen to pose a threat to this identity. Immigration was one of the key issues in the 2019 Federal election with the successful party announcing a lower migration cap as one of their key promises (Dalzell, 2019; Dobson, 2019). Our finding provides clear evidence that such policies are directly affecting the integration of migrants already residing in Melbourne communities.

Despite the advances noted herewith, a limitation of our research is that our data are cross sectional. This makes it impossible to assess the temporal ordering of this connection. Given the significant scholarship on the association between blackness and crime, we contend that long held biases are certainly a factor that prevents meaningful contact between groups in this country. It is possible that perceptions of local area crime drive perceptions of anger and that this is largely a mutually reinforcing relationship that plays out over time. Longitudinal research is needed to better understand these associations.

Conclusion

The aim of this research was to investigate the relationship between anger towards Africans and perceptions of neighbourhood crime and disorder. While we hypothesised that this relationship would be mediated by quality contact with Africans and neighbourhood cohesion, our findings portrayed a different story. As a result of the prolific media and political attention around the African communities in the aftermath of Moomba 2016, residents who reported anger towards Africans were more likely to perceive neighbourhood disorder. This was further increased by negative contact with Africans, despite positive contact having no impact. Understanding the difficulties experienced by the South Sudanese community, and African communities more broadly, is important to provide recognition of the challenges experienced by and the need for support for the plight of immigrants creating a new life in Australia. Equally important is the need to strengthen, through policy and evidenced based programs, initiatives that work to build inclusion and cultural understanding across all communities. However, for such programs to be successful, politicians must step away from promoting false dichotomies of ‘us’ and ‘them’. Public messaging strategies that seek to exclude or marginalise groups on the basis of their ethnicity, religion or culture only serve to heighten negative sentiments towards these groups. This in turn can have an enduring effect on a community’s social cohesion. In contrast messaging strategies that serve to bring communities together, to work inclusively to solve local problems, will reap far greater social benefits for society in both the short and long term.

Footnotes

Acknowledgements

The authors would like to thank the editors and the reviewers for their considered comments and suggestions.

Declaration of conflicting interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors thank the Victorian Government’s Social Cohesion Research Grants Program administered through the Department of Premier and Cabinet for funding the research.

Notes

ORCID iD

Kathryn Benier

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