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SA Crime Quarterly

On-line version ISSN 2413-3108
Print version ISSN 1991-3877

SA crime q.  n.55 Pretoria Mar. 2016

http://dx.doi.org/10.17159/2413-3108/2016/v0n55a390 

RESEARCH ARTICLES

 

Pulling us apart? The association between fear of crime and social cohesion in South Africa

 

 

Benjamin RobertsI; Steven GordonII

ICoordinator of the South African Social Attitudes Survey and senior research manager in the Democracy, Governance & Service Delivery (DGSD) programme, Human Sciences Research Council (HSRC). broberts@hsrc.ac.za
IIDoctoral researcher in the DGSD research programme at the HSRC. sgordon@hsrc.ac.za

 

 


ABSTRACT

Fear of crime, like crime itself, is thought to be a factor that constrains efforts by government and non-state actors to promote socially cohesive communities and a caring society. As concerns have mounted over various aspects of the social fabric in South Africa, increasing policy attention has been directed at perceptions of safety and nation-building. In this study, we use nationally representative survey data to examine recent theoretical models on the link between fear of crime and social cohesion within communities. The results do not offer strong support for the hypothesis that higher fear of crime is associated with lower levels of social trust, neighbourhood ties and civic cohesion, although fear does have a moderate, adverse influence on attitudes towards law enforcement.


 

 

The concept of 'fear of crime' has been the subject of substantive international interest and debate since the 1960s.1 This attention was particularly motivated by the recognition that it is a salient social problem in its own right, with a notable share of citizens across many countries expressing worry about crime.2 It further reflects concern with the complex and detrimental effects that fear of criminal violence imparts on quality of life at individual, community and societal levels. As research evidence has amassed concerning the skewed spatial patterning of crime and the fear of crime across different localities both internationally and in South Africa,3 a growing academic emphasis on local environmental context as drivers of both these phenomena has emerged. Over the last three decades, therefore, renewed attention has been paid to ecological theories in understanding and explaining the relationship between social disorder, processes of change within neighbourhoods, and levels of crime.

Social disorganisation theory has been especially prominent, drawing on pioneering work in Chicago by Shaw and McKay.4 Simply put, social disorganisation refers to 'the inability of local communities to realize the common values of their residents or solve commonly experienced problems'.5 In its classic formulation, this theoretical perspective examined low socioeconomic status, high population turnover and ethnic heterogeneity as the dominant factors weakening the influence of social rules on the behaviour of residents in communities. However, new questions have gradually been posed and social disorganisation perspectives have expanded to include an additional range of structural measures and processes, such as social cohesion, informal control, social trust, social capital and collective efficacy.6 The attention devoted to social disorganisation theory has included the influential, though contested, 'broken windows theory', which maintains that minor signs of physical disorder serve as visual cues that lead to serious crime and mounting urban decay, as well as subsequent theoretical critiques arguing that other factors instrumentally influence crime rates and that the disorder-crime link is weakly associated.7

In this article, our intention within this broader theoretical framework is to provide some preliminary South African empirical evidence with regard to the association between fear of crime and social cohesion. While crime represents a central variable in social disorganisation theory and is referred to in places throughout this article, our research primarily focuses on fear of crime rather than the occurrence of crime in examining associations with social cohesion.

Specifically, we analyse nationally representative survey data to determine the existence and strength of the association between these social indicators. For the purposes of this article, analysis has been confined exclusively to 2013 South African Social Attitudes Survey (SASAS) data, as this is the most recent survey round that contains both the fear and social cohesion measures that we use, as described below. We begin by outlining theoretical approaches to examining fear of crime and social cohesion, as well as associated empirical evidence. We then describe the survey data used for analysis, including a discussion of the definitional and measurement debates on fear of crime, and present the distribution of our chosen fear indicator. We also examine the influence of fear on two aspects of our multidimensional conceptualisation of social cohesion, namely social trust and neighbourhood ties, as well as political legitimacy. We conclude by relating our findings to theoretical perspectives on the consequences of fear in communities, and reflecting on the implications for policy efforts aimed at addressing crime and fear of crime as the basis for greater cohesion and improved personal, community and national wellbeing.

 

Fear of crime and social cohesion in theory

One strand of the social disorganisation literature has focused on exploring the complex ways in which contextual mechanisms influence crime and perceptions of crime within localities. Neighbourhood characteristics, such as disadvantage, population stability or mobility, level of urbanisation, racial or ethnic diversity and prior crime levels are seen to shape collective efficacy (social cohesion, trust and informal social control) and social disorder, which inform beliefs and worries about crime and violence.8 One extension of the social disorganisation perspective recognises that a reciprocal relationship may exist between fear of crime and neighbourhood social cohesion. This implies that while the characteristics of neighbourhoods are likely to have consequences for levels of crime and fear of crime, it is also possible that fear of crime may have a bearing on neighbourhood trust, cohesion and attachment.

There are two dominant theoretical perspectives pertaining to community responses to fear of crime, termed by James Hawdon and colleagues as the 'fear-decline' and 'fear-solidarity' models.9 According to the fear-decline model, escalating fear of crime can weaken the ability of local communities to collectively address problems. This occurs because fear inhibits social interaction, which, in turn, may result in a decline in social cohesion and trust, erode the informal social control or collective efficacy that keeps crime and disorder in check, and foster a retreat from neighbourhood life.10 Consequently, this process of decline is thought to further provoke fear and a rise in crime. By contrast, the fear-solidarity model argues that fear of crime may actually serve to enhance community solidarity by motivating residents to come together, establish shared values and respond collectively to the common threat posed by crime.

 

Existing evidence on the fear-cohesion association

There have been a number of studies, mostly from North America and Europe, that have attempted to test the hypothesised effect of fear of crime on neighbourhood social ties and attachment. In an early Canadian study from the late 1970s, Timothy Hartnagel found that fear of victimisation was not inversely related to neighbourhood cohesion and social activity, but did have a significant effect on attachment to the community as a place of residence.11 Despite this finding, a number of other studies have tended to confirm the view that fear promotes decline and withdrawal rather than solidarity.

For instance, Allen Liska and Barbara Warner's 1991 study of United States (US) cities found that fear of crime constrains social interaction, which they contend is likely to have a damaging effect on social solidarity and attempts at building cohesiveness.12 Similarly, using British Crime Survey data, Markowitz and colleagues found in 2001 that declining neighbourhood cohesion increased crime and disorder, which resulted in escalating fear of crime and imposed further downward pressure on cohesion.13 A more recent example comes from a 2013 Finnish study, where Hawdon and colleagues suggest relatively strong support for the fear-decline perspective but not for the fear-solidarity model.14 In fact, very limited evidence exists favouring the solidarity model. One exception is the 2009 study of Chicago residents by Joong-Hwan Oh and Sangmoon Kim, who found that mounting fear of crime among the elderly promoted greater social interaction with their neighbours and created the basis for stronger social cohesion and interpersonal trust.15South African evidence on the fear-cohesion nexus is especially limited, particularly if one narrows the focus to quantitative studies. There have nonetheless been several articles in South Africa testing different aspects of social disorganisation theory.16

 

Methodology

This study employs quantitative data from the 2013 round of the South African Social Attitudes Survey (SASAS), a repeat cross-sectional survey series that has been conducted annually since 2003 by the Human Sciences Research Council (HSRC). Each SASAS round has been designed to yield a nationally representative sample of adults aged 16 and older living in private residence. Statistics South Africa's 2011 Population Census Small Area Layers (SALs) were used as primary sampling units (PSUs). For each round of SASAS, 500 PSUs were drawn, with probability proportional to size, from a sampling frame containing all of the 2011 SALs. The sampling frame is annually updated to coincide with StatsSA's midyear population estimates in respect of the following variables: province, gender, population group and age group. The sample excludes special institutions (such as hospitals, military camps, old age homes, school and university hostels), recreational areas, industrial areas, and vacant areas. It therefore focuses on dwelling units or visiting points as secondary sampling units (SSUs), which are separate (non-vacant) residential stands, addresses, structures, flats, homesteads and other similar structures. Three explicit stratification variables were used in selecting SALs, namely province, geographic type and majority population group.

In each of these drawn PSUs, 21 dwelling units were selected and systematically grouped into three subsamples of seven, each corresponding to the three SASAS questionnaire versions that are fielded. The questionnaire containing the relevant fear of crime and social cohesion was included in only one of the three instruments, and thus administered to seven visiting points in each PSU.17 The sample size of the study consisted of 2 885 interviews.

The English base version of the research instruments was translated into the country's major official languages and the surveys were administered in the preferred language of the respondent. This was to ensure that all respondents in different provinces understood the questionnaire and that it was culturally equivalent and consistent across all languages. Pilot testing was conducted in an attempt to ensure the validity of the research instrument. Interviews were conducted by means of face-to-face interviewing, using print questionnaires.18

Study limitations

Two particular limitations of the study need to be mentioned. The first relates to the availability of cross-sectional versus panel data. As previously mentioned, SASAS is a repeat, cross-sectional survey series. Therefore, while the series permits the analysis of trends in underlying beliefs and attitudes over time, it is not a longitudinal panel study that interviews the same individual respondents at regular intervals. The absence of repeated observations for the same sample of South African adults over a number of waves of interviewing means that the study is constrained in its ability to examine the observed relationships between crime, fear of crime and social cohesion among the same people. The implication is that our focus is instead confined to exploring the extent and nature of the association between these constructs.

The second limitation of the study is that, due to the sample design and characteristics, the SASAS dataset does not permit disaggregation down to the neighbourhood level. As a result, we are unable to examine how neighbourhood level characteristics may affect crime, fear and social cohesion patterns, or reflect on the consistency or variation in observed patterns within and between different localities at the small area level. While this does mean that we are drawing on neighbourhood-level theory to inform and guide the national-level analysis we perform, we believe that survey results will at least serve as a broad evidence of the fear-cohesion nexus that future neighbourhood-level, quantitative research could substantiate or refute.

Measuring fear of crime

The steady expansion of research on fear of crime in recent years has prompted significant methodological reflection on the survey-based measures traditionally used to examine this phenomenon. One of the most commonly used fear of crime questions asked of individuals includes variants on the following: 'How safe do you feel walking alone in this area after dark?' This is the primary indicator included in Statistics South Africa's Victims of Crime Survey series to capture fear of crime.19 This line of questioning is said to capture 'formless' fears that address a vague threat to personal security, and can be distinguished from measures aimed at identifying 'concrete' fears that refer to a particular crime (e.g. types of property crime or individual/personal crime).20 Criticisms levelled at the formless fear questions include:

The lack of explicit reference to crime

The imprecise geographical reference - the 'neighbourhood' or 'local area'

The reference to an activity that many may seldom undertake ('walking alone after dark'), either by choice or owing to physical limitation

The absence of a specific recall period and failure to capture frequency of fearful experiences (e.g. number of times in the past year that the person felt unsafe)21

Various refinements have been experimented with in response to such criticisms, ranging from basic phrasing changes to the inclusion of multiple items. Of particular relevance is recent research that suggests that fear of crime is both an expressive and an experiential phenomenon.22 The expressive component of fear refers to 'a more diffuse/ambient anxiety',23 which is essentially a general awareness of the likelihood or risk of victimisation. Alternatively, experiential fear can be described as 'an everyday worry', a set of tangible emotions deriving from a feeling that one's personal safety is being directly threatened. The conventional formless fear questions arguably tap into more general anxiety or the expressive element of fear. They may also overestimate fear of crime due to a focus on how afraid one is (intensity) without taking account of how often one is worried or fearful (frequency) or the impact of such worries on everyday life.24

As such, in this article we draw on measures originally developed for inclusion in the European Social Survey (ESS) to better capture experiential fear. These measures combine items on the frequency of worry about specific crime types with questions on the adverse impact of fear on quality of life. This narrows the focus to emotional experiences that adversely affect wellbeing, which may lead to more precise estimates of the everyday experience of the fear of crime.25 The specific form of these questions is as follows:

(1) 'How often, if at all, do you worry about your home being burgled?', with the response categories 'All or most of the time', 'Some of the time', 'Just occasionally' and 'Never'.

(2) (If the answer is other than 'Never'): 'Does this worry about your home being burgled have a serious effect on the quality of your life, some effect, or no real effect on the quality of your

life?'

(3) - (4) Two questions with similar phrasing, though 'your home being burgled' is substituted with 'becoming a victim of violent crime'.

These experiential fear measures have been included in each round of the SASAS series since 2008, alongside the more traditional indicators of fear, namely the perceived safety of walking alone in one's areas during the day and after dark.26 In Table 1, the frequency of responses to the worry about burglary and violent crime questions, as well as the follow-up items on the impact of such fear on personal quality of life, are presented for the 2013 survey round. Close to two-fifths (38%) of adult South Africans indicated that they never worried about their home being burgled or becoming a victim of violent crime, while a slightly higher share expressed worry either 'just occasionally' or 'some of the time' (46% for burglary; 50% for violent crime). For both types of crime, around a fifth of adults indicated that their worry was a constant presence in their lives (17% for burglary; 21% for violent crime).

 

 

A similar distribution of responses is evident in relation to the items addressing the impact of worry on one's quality of life. Of those that expressed some level of worry about the two crime types in 2013, only around a tenth (11-12%) felt it had 'no real effect', with a significant proportion (33% for burglary and violent crime) acknowledging at least 'some effect'.

In Table 2, the cross-tabulation of the frequency of worry and effect on quality of life items is presented. The results demonstrate a consistent and expected pattern, namely that the more frequently one worries about crime, the more inclined one is to report appreciable effects on quality of life. Those who indicated that they worried 'just occasionally' mostly reported that it had 'some effect' (52% for burglary; 47% for violent crime). Among those stating that they worried 'some of the time', a far greater share stated that it had 'some effect' on their quality of life (65% for burglary; 70% for violent crime). Finally, for those worrying 'all or most of the time', the dominant response was that this exerted a 'serious effect' on their wellbeing (59% for burglary; 69% for violent crime). These patterns have exhibited modest fluctuations between 2008 and 2014 (results not shown), but the overarching pattern is one of broadly consistent levels of worry which, for a sizable minority, has a serious impact on the quality of their lives.27

The responses to the four questions were combined into a single categorical measure of fear of crime, using an approach that Jackson and Kuha refer to as a 'model-supported method'.28 The scaling of this measure ranged from 1 (unworried) to 6 (most worried). The responses for 2013 are provided in Table 3.29 On average across the period, slightly more than a third (36%) of respondents were unworried, while 13% worried occasionally only about home burglary or only about violent crime. A quarter of the adult population (23%) displayed moderate levels of worry, 5% had a fairly high level, while 23% were classified as having very high levels of worry. Year-on-year estimates show a similar pattern, though with some differences at the tail ends of the distribution.

 

 

The experience of criminal victimisation has a clear bearing on levels of fear. In 2013, SASAS respondents were asked: 'Have you or a member of your household been the victim of a burglary or assault in the last five years?' Of those who answered affirmatively,30 almost two-fifths (37%) were found to be in class 6 (most worried) and only about one-seventh (15%) were in the first class (least worried). Further testing found that fear was lower among those who had not been victims of crime.31 A Pearson's chi-squared test identified that the observed differences between fear of crime and experience of crime were statistically significant, as did a one-way ANOVA test.32 This suggests that, in South Africa, an individual's fear of crime has a relationship with his or her experience of crime. Yet it is also possible for fear of crime to be disproportionate relative to the actual risk of criminal victimisation. For instance, the city of Barcelona (Spain) has a low and declining crime rate, but fear of crime in Barcelona remains high, indicating a mismatch between actual levels of victimisation and the fear of being victimised.33In such instances, fear may reflect a more generalised sense of risk.34 It must be considered, therefore, that the relationship between fear of crime and criminal victimisation can be complex and non-linear.

A multidimensional approach

Like fear of crime, social cohesion has received increased policy attention in South Africa over the last decade, especially following the widespread xenophobic violence of 2008. It has been promoted to address concerns related to the high levels of violent crime, but also to promote positive national identity in a multicultural, stratified society.35 The 1998 White Paper on Safety and Security identified the promotion of social cohesion as an important element underlying its social crime prevention efforts. More recently, the 2012 National Development Plan (NDP) included a chapter entitled 'Building safer communities', which among other things stressed that safety and security requires an environment that is conducive to 'strengthened social cohesion'. Even the 2015 draft White Paper on Security and Safety includes the need 'to improve the social fabric and cohesion within families' as one of six core objectives. Institutionally, a Chief Directorate of Social Cohesion has been established in the Department of Arts and Culture to coordinate social cohesion activities across government departments. Yet, despite this, social cohesion has been, and continues to be, the subject of considerable conceptual and measurement debate. There remains little agreement on what constitutes social cohesion and whether or how it can be measured.36

In this instance, we draw on research conducted by the HSRC on conceptualising and measuring social cohesion. This conceptual framework assumes that social cohesion is multidimensional in that it encompasses a number of domains of social life, involves both attitudinal and behavioural predispositions, and is an attribute of a group or society rather than individuals.37 The HSRC work identified three specific dimensions of cohesion:

Socio-cultural cohesion, which includes social capital, trust, tolerance and shared identities and is the core focus in much social cohesion literature

Economic cohesion, which addresses economic development as well as support for strategies to reduce poverty and inequality

Civic cohesion, which addresses political support and legitimacy as well as active political participation by citizens

A full examination of the association between fear of crime and social cohesion, using a range of measures to inform this particular conceptualisation, is beyond the scope of this short article. Instead, we focus on two key aspects of socio-cultural and civic cohesion, the first relating to interpersonal or social trust and neighbourliness, and the second focusing on key components of political support. Use will be made exclusively of the 2013 SASAS data, as this is the most recent round that contains both the fear and social cohesion measures.

 

Results

Does fear diminish social trust?

Despite common references to the 'rainbow nation' and the moral philosophy of ubuntu, national and comparative data on social trust suggest that South Africa is a society characterised by low levels of trust.38Given criticism concerning the reliability of single-item measures of generalised interpersonal trust, we make use of three items included in SASAS.39 The measures are phrased as follows: (1) 'Generally speaking, would you say that most people can be trusted, or that you cannot be too careful in dealing with people?'; (2) 'Do you think that most people would try to take advantage of you if they got the chance, or would they try to be fair?'; and (3) 'Would you say that most of the time people try to be helpful or that they are mostly looking out for themselves?'.40 Responses to these items are captured on an 11-point scale, where 0 represents the lowest level of trust and 10 the highest.41 Again, relatively low levels of trust are evident, with the mean scores ranging between 4.02 and 4.40 on the scale. The scores for the three items were subsequently averaged together and the resultant 0-10 score transformed into a 0-100 trust index, with higher values indicating greater trust in others.42

In Figure 1, mean social trust index scores are presented for each of the six categories in the experiential fear of crime measure. The results do not reveal a stark gradient of difference across the fear scale. A one-way ANOVA was conducted and revealed that fear of crime did exert a significant effect on social trust [M=42.2, SD=21.4, F(5,2817)=6.55, p < .001].43 However, post hoc comparisons using the Scheffé test show that only those in the most worried category are less trusting than those with lower levels of fear,44 while correlation analysis shows that there is only a weak, inverse relationship between fear and trust (r = -0.047, p = 0.0134).

 

 

These results suggest that fear of crime is inversely related to social trust, but it needs to be acknowledged that the levels of fear need to be relatively high in order for this association to be observed. Similar findings emerge when using measures of neighbourliness rather than social trust.45We also find that the conclusions do not alter if one substitutes the experiential fear variable for the conventional 'walking alone at night' fear measure.46Such findings indicate that fear of crime exerts a nominal negative influence over social trust and community ties, which is most evident at the upper margin of the fear scales. One might take this finding as evidence that South Africans are resilient and do not allow fear of crime to depress their levels of social trust or damage neighbourly bonds. However, given the low general trust scores, one could also argue that such trust and community ties may to some degree already have eroded and that expectations of a strong pattern of difference, based on such measures, are possibly misplaced.

The political consequences of fear

The process of democratic transformation and consolidation in the country has focused on progressively realising a united, cohesive society. The NDP emphasises political legitimacy and democratic participation as primary goals of the state and core indicators of social cohesion. The importance of civic cohesion derives from mounting international concern over the last two decades about an apparent erosion of the foundations of citizenship and democracy, or a 'crisis of democratic legitimacy'. Evidence of declining electoral turnout, falling confidence in government and mounting public discontent are often cited in support of this thesis.47 It has provoked wide-ranging initiatives aimed at building up citizen-state relations, including opening up opportunities for direct citizen engagement in decision-making processes and efforts at improving government transparency and accountability.

To examine the consequence of fear of crime on civic cohesion, we examine measures that allow us to discern patterns of political legitimacy and illegitimacy. We draw on a nested understanding of political support, ranging from diffuse measures of national identity and pride through to more specific evaluations of democratic performance, institutional trust, and approval of office-bearers.48 For the purposes of this article, we leave aside the political participation element of civic cohesion. Future studies will hopefully explore the impact of fear of crime on political behaviour in the country. National pride is assessed based on the level of agreement with the following statement: 'Generally speaking, South Africa is a better country than most other countries.' Two measures of democratic performance are used, namely satisfaction with the functioning of democracy as a whole and, more narrowly, satisfaction with the way that the government is handling crime reduction in one's neighbourhood. With regard to institutional trust, we focus on trust in the police and the courts, while the last measure we employ for our analysis is trust in current political leaders in the country. In all instances, a standard five-point Likert scale is used to capture responses.

Table 4 presents levels of pride, satisfaction and trust for each of these political support measures and how these attitudes vary by different levels of experiential fear. It is interesting to observe from the bottom row in the table that, after two decades of democracy, South Africans are resolutely proud of their country, but judge fairly harshly the general performance of the democratic system and the quality of political leadership. Citizens also lack confidence in the police and courts, while less than a fifth (18%) were content with government crime reduction efforts in their neighbourhood. Observed levels of discontent in 2013 in many instances reflect a general decline in political support over the 2008-2014 interval.49 Unfavourable evaluations of the performance of democracy and core political institutions could be interpreted as a sign of the emergence of a more critical citizen who is concerned with the accountability of institutions and office-bearers.

 

Does fear have a discernible impact on these measures?

The evidence presented in Table 4 shows that the results are rather mixed. An association between fear of crime and national pride is clearly not manifest. The same appears to be true of satisfaction with democratic performance and the country's current political leaders. As can be observed from the table and as one might intuitively expect, there is a slightly stronger but nonetheless moderate inverse association between fear and both trust in the police and satisfaction with crime reduction. Further examination, using single pairwise correlations, shows a negative association between fear of crime and confidence in the police and in crime-reduction efforts.50 In other words, as an individual becomes more fearful, his or her confidence in the criminal justice system declines. While worry about crime therefore has some association with more specific political support items, on the whole it is unlikely to be a primary driver of political legitimacy in the country, given the strength and nature of the observed association.

 

Conclusion

In South Africa, fear of crime continues to be reported by a significant share of the population, irrespective of whether expressive or experiential measures are employed. Reported fear of crime is no doubt informed by experiences of crime, and a significant segment of the adult population reported having been a victim of crime in last five years. While much concern has been voiced about the likely consequences such fear may bring to bear on local society, the study results offer fairly circumscribed support for a corrosive effect on the particular aspects of social cohesion that we examined. There is only a weak, negative association with social trust and neighbourhood ties. Greater fear is associated with more negative views of police effectiveness and overall police confidence. Yet it does not yield a consistent, adverse association with more diffuse measures of political support, such as satisfaction with democracy and national pride. Where such a relationship exists, it tends to be apparent only at the extreme, upper margins of the fear scale. Therefore these results certainly do not provide unequivocal evidence in favour of either fear-decline or fear-solidarity models of community responses to fear. At best, they show marginal and somewhat variable support for the fear-decline perspective.

Obviously, the study is constrained by the data available for analysis. Longitudinal data would allow us to better understand the direction of the relationship observed in this study. As Markowitz observes, the absence of such panel data has been a general impediment in social disorganisation research, which has mostly relied on cross-sectional data. Moreover, there is a need for data that would allow neighbourhood-level disaggregation, permitting researchers to test the paradigms of social disorganisation theory in South Africa, especially in teasing out the nature of the relationship between social cohesion, fear of crime, and crime.

Further work will need to be undertaken to determine the replicability of our findings, by experimenting with alternate measures of both fear and cohesion. Since we focused on national patterns, the consistency of our findings across different groups, geographies and individual and community attributes will need to be explored. If our findings are, however, replicated through other studies it would suggest that success in efforts at reducing crime and the fear of crime are unlikely to translate into immediate and substantive gains in terms of positive forms of neighbourhood cohesion.

Furthermore, the fact that low levels of social trust, trust in the police and courts, as well as satisfaction with democratic functioning are common to both the fearful and fearless raises fundamental questions about the nature of the social fabric and community in the country. Perhaps, as Suren Pillay contends, we are a nation where such attitudinal predispositions may have encouraged tendencies towards 'fragmentation rather than unification'.51 This is apparent in the proliferation of gated communities, the growing reliance on non-state forms of policing, calls for retributive justice, and the rise of forms of cohesion that target perceived external threats (such as foreign migrants) and nurture out-group hostility. While more needs to be done to ensure freedom from crime and the fear of crime, we must be careful in assuming that this would serve as a catalyst for more multicultural, bridging forms of cohesion as desired by the government's nation-building programme.

 

Acknowledgement

The analysis in this article was supported by a project grant (107365-001) received as part of the Safe and Inclusive Cities initiative established by Canada's International Development Research Centre (IDRC) and the United Kingdom's Department for International Development (DFID). In addition, we would like to acknowledge the assistance of the 'Tuscany: a Global Laboratory for Quality of Life' project funded by the Region of Tuscany and hosted by the Polo Lionello Bonfanti, for supporting Steven Gordon's participation in the Safe Cities study and for useful analytical suggestions. Points of view or opinions contained within this document are those of the authors and do not necessarily represent the official position or policies of any of these organisations.

 

Notes

1 Examples from across the decades, covering theoretical, methodological and empirical traditions, include James Garofalo and John Laub, The fear of crime: broadening our perspective, Victimology, 3:3-4, 1978, 242-253;         [ Links ] Timothy F Hartnagel, The perception and fear of crime: implications for neighborhood cohesion, social activity, and community affect, Social Forces, 58:1, 1979, 176-193;         [ Links ] Ralph B Taylor and Margaret Hale, Testing alternative models of fear of crime, The Journal of Criminal Law and Criminology, 77:1, 1986, 151-189;         [ Links ] Kenneth F Ferraro and Randy L Grange, The measurement of fear of crime, Sociological Inquiry, 57:1, 1987, 70-97;         [ Links ] Chris Hale, Fear of crime: a review of the literature, International Review of Victimology, 4:2, 1996, 79-150;         [ Links ] Rachel Pain, Place, social relations and the fear of crime: a review, Progress in Human Geography, 24:3, 2000, 365-387;         [ Links ] Jonathan Jackson, Experience and expression: social and cultural significance in the fear of crime, British Journal of Criminology, 44:6, 2004, 946-966;         [ Links ] and Ian Brunton-Smith and Patrick Sturgis, Do neighborhoods generate fear of crime? An empirical test using the British Crime Survey, Criminology, 49:2, 2011, 331-369.         [ Links ]

2 SD Farrall, JP Jackson and E Gray, Social order and the fear of crime in contemporary times, Oxford: Oxford University Press, 2009.         [ Links ]

3 On the spatial patterning of crime and fear of crime in South, see for example Gareth Newham et al., Murder and robbery: overview of the official statistics 2-14/15, ISS Fact Sheet, 2015;         [ Links ] Benjamin J Roberts, State of affliction: fear of crime and quality of life in South Africa, in Dave Webb and Eduardo Wills-Herrera (eds), Subjective well-being and security, vol. 46, Social Indicators Research Series, Dordrecht: Springer Netherlands, 2012, 149-175.         [ Links ] A recent example from the international literature is Gregory D Breetzke and Amber L Pearson, The fear factor: examining the spatial variability of recorded crime on the fear of crime, Applied Geography, 46, 2014, 45-52.         [ Links ]

4 CR Shaw and HD McKay, Juvenile delinquency and urban areas, Chicago: University of Chicago Press, 1942.         [ Links ]

5 Robert J Bursik, Social disorganisation and theories of crime and delinquency: problems and prospects, Criminology, 26:4, 1988, 521.         [ Links ]

6 Gerben J Bruinsma et al., Social disorganization, social capital, collective efficacy and the spatial distribution of crime and offenders, British Journal of Criminology, 53:5, 2014, 944.         [ Links ]

7 James Q Wilson and George L Kelling, Broken windows, Atlantic Monthly, 249:3,1982, 29-38;         [ Links ] Robert J Sampson and Stephen W Raudenbush, Seeing disorder: neighborhood stigma and the social construction of 'broken windows', Social Psychology Quarterly, 67:4, 2004, 319-342.         [ Links ]

8 Ian Brunton-Smith, Jonathan Jackson and Alex Sutherland, Bridging structure and perception on the neighbourhood ecology of beliefs and worries about violent crime, British Journal of Criminology, 54:4, 2014, 506.         [ Links ]

9 James Hawdon et al., Social responses to collective crime: assessing the relationship between crime-related fears and collective sentiments, European Journal of Criminology, 11:1, 2014, 39-56.         [ Links ] See also Allen E Liska and Barbara D Warner, Functions of crime: a paradoxical process, American Journal of Sociology, 1991, 1441-1463.         [ Links ]

10 Wesley Skogan, Fear of crime and neighbourhood change, Crime and Justice, 8, 1986, 203-229;         [ Links ] Liska and Warner, Functions of crime; Joong-Hwan Oh and Sangmoon Kim, Aging, neighbourhood attachment, and fear of crime: testing reciprocal effects, Journal of Community Psychology, 37:1, 2009, 21-40.         [ Links ]

11 Hartnagel, The perception and fear of crime.

12 Liska and Warner, Functions of crime, 1446, 1459.

13 Fred E Markowitz et al., Extending social disorganization theory: modeling the relationships between cohesion, disorder, and fear, Criminology, 39:2, 2001, 293-320.         [ Links ]

14 Hawdon et al., Social responses to collective crime.

15 Oh and Kim, Aging, neighbourhood attachment, and fear of crime, 37.

16 See, for example, Tony Emmett, Social disorganisation, social capital and violence prevention in South Africa, African Safety Promotion, 1:2, 2003, 4-18;         [ Links ] and Gregory D Breetzke, Modeling violent crime rates: a test of social disorganization in the city of Tshwane, South Africa, Journal of Criminal Justice, 38:4, 2010, 446-452.         [ Links ] A recent analysis of Afrobarometer data has also examined the association between victimisation, fear and indicators of democracy and governance; see Zenobia Ismail, Is crime dividing the rainbow nation? Fear of crime in South Africa, Afrobarometer, Briefing Paper, 96, 2010.

17 Interviewers called at each visiting point selected and listed all those eligible for inclusion in the sample in terms of age and residential status criteria. The interviewer then selected one respondent using a random selection procedure based on a Kish grid.

18 The HSRC's Research Ethics Committee granted ethical approval for the instrumentation and research protocols for each round.

19 The specific phrasing of the StatsSA measure is: 'If you had to walk, how safe would you feel walking alone in your area when it is dark?.' A similar item is included to capture daytime fear. These measures were included in the 2011, 2012 and 2013/14 survey rounds.

20 For a useful account of these distinctions, see Ferraro and LaGrange, The measurement of fear of crime.

21 Stephen Farrall and David Gadd, Evaluating crime fears: a research note on a pilot study to improve the measurement of the 'fear of crime' as a performance indicator, Evaluation, 10:4, 2004, 493-502;         [ Links ] Hale, Fear of crime; Ferraro and LaGrange, The measurement of fear of crime.

22 See Jonathan Jackson and Jouni Kuha, Worry about crime in a cross-national context: a model-supported method of measurement using the European Social Survey, Survey Research Methods, 8:2, 2014, 109-126.         [ Links ]

23 Jonathan Jackson and Emily Gray, Functional fear and public insecurities about crime, British Journal of Criminology, 50:1, 2010, 1-22.         [ Links ]

24 Farrall and Gadd, Evaluating crime fears; Jackson, Experience and expression; and Emily Gray, Jonathan Jackson and Stephen Farrall, Reassessing the fear of crime, European Journal of Criminology, 5:3, 2008, 363-380.         [ Links ]

25 This is discussed in greater detail in Jackson, Experience and expression.

26 Apart from the walking alone during the day and at night, a third indicator commonly employed by the Human Sciences Research Council (HSRC) in its national surveys since the early 1990s asks respondents to rate how safe they 'feel personally on most days'.

27 These results are consistent with what was found by Roberts, State of affliction.

28 This entails a combination of latent class modelling together with logical, pragmatic choices in deriving the final scale. For an in-depth examination of the particular steps and choices involved in deriving the six-class measure, based on the model-assisted scoring method and using the fear of crime questions, see Jackson and Kuha, Worry about crime in a cross-national context. The construction of the measure in the South African case was done with the assistance of Prof. Jonathan Jackson from the London School of Economics.

29 Weighted percentages have been estimated using sampling design weights that are benchmarked to Statistics South Africa's most recent mid-year estimates. Province, gender, population group and 5-year age group were used as benchmark variables, with the view to represent the South African population 16 years and older as closely as possible.

30 According to the South African Social Attitudes Survey (SASAS) data from 2013, more than one out of every four adult South Africans (27%) reported that they or another household member had been a victim of burglary or assault in the last five years.

31 The share reporting that they or another household member had been a victim of burglary or assault in the last five years ranged from 11% among the unworried to around half among those with frequent or persistent worry (50% and 49% respectively).

32 One-way analysis of variance (ANOVA) results between these measures of fear of crime and experience of crime are as follows: victim in the last five years had a fear of crime classification mean of 4.15 (Std. Dev. = 1.83, n=755); not a victim in the last five years had a classification mean of 2.74 (Std. Dev. =1.88, n =2085). The Prob > F statistic was 0.000.

33 Sergi Valera and Joan Guàrdia, Perceived insecurity and fear of crime in a city with low-crime rates, Journal of Environmental Psychology, 38, 2014, 195-205.         [ Links ]

34 Jackson, Experience and expression, and Farrall, Jackson and Gray, Social order and the fear of crime in contemporary times also provide a worthwhile discussion of this phenomenon.

35 Suren Pillay, Crime, community and the governance of violence in post-apartheid South Africa, Politikon, 35:2, 2008, 141-158.         [ Links ]

36 See, for example, Vanessa Barolsky, A better life for all': social cohesion and the governance of life in post-apartheid South Africa, Social Dynamics, 38:1, 2012, 134-151;         [ Links ] Vanessa Barolsky, The 'state' of social cohesion: re-stating the question of social cohesion and 'nation-building', in U Pillay et al., State of the nation: South Africa 2012-2013, Cape Town: HSRC Press, 2013;         [ Links ] and Ivor Chipkin and Bongani Ngqulunga, Friends and family: social cohesion in South Africa, Journal of Southern African Studies, 34:1, 2008, 61-76.         [ Links ]

37 This framework is discussed in Jarè Struwig et al., Towards a social cohesion barometer for South Africa, in Pillay et al., State of the nation: South Africa 2012-2013, 399-421.         [ Links ]This South African study drew on the work of Jane Jenson, Defining and measuring social cohesion, London: Commonwealth Secretariat and United Nations Research Institute for Social Development, 2010.

38 For example, the 2010-2014 round of the World Values Survey (WVS) includes a repeat dichotomous measure asking respondents whether they thought most people could be trusted or if you needed to be very careful. While only a small minority (23%) of South Africans believed that most people could be trusted, we are not exceptional in this regard. The low expression of social trust in South Africa approximates the average for the 60 countries included (25%) in the survey round and is notably higher than in countries such as the Philippines, Ghana, Brazil and Zimbabwe, where less than one-tenth are trusting towards others. See World Value Survey Online Analysis, http://www.worldvaluessurvey.org/WVSOnline.jsp. In only five countries did more than half the adult population exhibit broad trust in others, namely the Netherlands, China, Sweden, New Zealand and Australia. Also see Jan Delhey, Kenneth Newton and Christian Welzel, How general is trust in 'most people'? Solving the radius of trust problem, American Sociological Review, 76:5, 2011, 786-807.         [ Links ]

39 The three SASAS items derive from the European Social Survey; see Delhey et al., How general is trust in 'most people'?.

40 The first item is a classic social trust question that has been used for close to 70 years, while the other two items focus on fairness and altruism and are added to form a more reliable trust scale.

41 This rating scale represents a notable improvement on the dichotomous WVS measure. For a discussion of these variables, see Tim Reeskens and Marc Hooghe, Cross-cultural measurement equivalence of generalized trust: evidence from the European Social Survey (2002 and 2004), Social Indicators Research, 85:3, 2008, 515-532.         [ Links ]

42 The scale has a good reliability, with a Cronbach coefficient of 0.804 and the item-rest correlations showing that all three items fit well with the index scale. The distributional characteristics of the measure are as follows: mean = 4.22; median = 4.33; skewness = -0.012; kurtosis = 2.526.

43 In addition, the Kruskal-Wallis test was conducted as a nonparametric alternative to one-way ANOVA, thereby testing the null hypothesis of equal population medians. The test results (p = <0.001) agree with our one-way findings of significant differences in social trust by fear of crime.

44 Specifically, the means social trust score among the most worried category (class 6, M=3.82, SD=2.24) was significantly lower than fear of crime class 1 (M=4.20, SD=2.12, p = .019), class 2 (M=4.59, SD=2.49, p = .015), class 3 (M=4.47, SD=2.03, p = .019) and class 4 (M=4.36, SD=1.90, p = .001). The difference between the most worried category and class 5 (M=4.47, SD=2.39, p = .07) was not statistically significant at the p<0.05 level. All other group-based differences are also not significant.

45 We tested the relationship between fear of crime and attachment to those living in one's neighbourhood, level of comfort borrowing small items from neighbours (a cup of sugar, an amount of R20), as well as agreement that people treat each other respectfully in one's area of residence. The 2013 SASAS data show modest positive association with the first measure (r=+0.03, p = 0.0765), and modest negative associations with the other items (r=-0.04, p = 0.0247; r= -0.05, p = 0.0153; and r=-0.07, p = 0.0002 respectively). One-way ANOVA results between these measures of neighbourliness and fear of crime are as follows: attachment to one's neighbours: F(5,2813) = 3.29, p = 0.0058, n=2819; borrowing a cup of sugar from neighbours: F(5,2805) = 12.71, p < 0.001, n=2811; borrowing R20 from neighbours: F(5,2801) = 12.78, p < 0.001, n=2807; people treat each other respectfully in neighbourhood: F(5,2804) = 8.55, p < 0 .001, n= 2810.

46 The correlations between this fear measure and the social trust index is -0.11, while for the four neighbourliness items the correlation coefficients are -0.05, -0.12, -0.10 and -0.09 respectively.

47 See, for example, Russell J Dalton and Martin P Wattenberg (eds), Parties without partisans: politica change in advanced industrial democracies, Oxford: Oxford University Press, 2000;         [ Links ] John R Hibbing and Elizabeth Theiss-Morse (eds), What is it about government that Americans dislike?, Cambridge: Cambridge University Press, 2001;         [ Links ] Stephen Macedo, Democracy at risk: how politica choices undermine citizen participation, and what we can do about it, Washington DC: Brookings Institution Press, 2005;         [ Links ] Peter Mair and Ingrid van Biezen, Party membership in twenty European democracies 1980-2000, Party Politics, 7:1, 2001, 5-22;         [ Links ] Susan Pharr and Roberts Putnam (eds.), Disaffected democracies: what's troubling the trilatera countries?, Princeton: Princeton University Press, 2000;         [ Links ] Roberts D Putnam, Bowling alone: the collapse and revival of American community, New York: Simon and Schuster, 2000;         [ Links ] Mariano Torcal and José Ramón Montero, Political disaffection in contemporary democracies: social capital, institutions, and politics, London: Routledge, 2006;         [ Links ] and Jan W Van Deth, José Ramón Montero and Anders Westholm, Citizenship and involvement in European democracies: a comparative analysis, New York: Routledge, 2007.         [ Links ]

48 In conceptualising political support, we are indebted to the pioneering work of David Easton, A systems analysis of political life, Chicago: University of Chicago Press, 1979;         [ Links ] and Pippa Norris, Democratic deficit: critical citizens revisited, Cambridge: Cambridge University Press, 2011.         [ Links ]

49 Jarè Struwig, Benjamin J Roberts and Steven Gordon, Amandla awethu: public attitudes, South African democracy and political participation, in Daniel Plaatjies et al. (eds), State of the nation, South Africa 2015: who is in charge?, Cape Town: HSRC Press, 2016.         [ Links ]

50 The correlation coefficients are -0.15 and -0.18 respectively.

51 Pillay, Crime, community and the governance of violence in post-apartheid South Africa, 141.

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