Determinants of fear of crime in Brazil: the effect of social cohesion

Determinantes del miedo al crimen en Brasil: el efecto de la cohesión social

Determinantes do medo do crime no Brasil: o efeito da coesão social

Abstract:

While some studies suggest that the nature of one's interactions with the community influences one's perceived risk of criminal victimization, only a few pieces of research have tested this association in Brazil. Using four previously existing Brazilian victimization surveys, we conducted logistic models to examine whether social ties and social cohesion are associated with perceived risk and fear of crime. The results showed that only in some contexts did social cohesion manifest an association with fear of crime. Specifically, two components of social cohesion may be relevant for this purpose: trusting neighbours and getting help; and the ability to distinguish neighbours from strangers in the street.

Keywords:
Fear of crime; Social cohesion; Victimization; Crime; Feeling of insecurity

Resumen:

Aunque algunos estudios sugieren que la naturaleza de las interacciones comunitarias influye en el riesgo percibido de victimización criminal, solo unos pocos estudios han probado esta asociación en Brasil. Utilizando cuatro encuestas brasileñas de victimización, realizamos modelos logísticos para examinar si los lazos sociales y la cohesión social están asociados con el riesgo percibido y el miedo al crimen. Los resultados mostraron que solo en algunos contextos se asociaba la cohesión social con el miedo al crimen. Específicamente, dos componentes de la cohesión social pueden ser relevantes para este propósito: confiar en los vecinos y obtener ayuda; y la capacidad de distinguir vecinos de extraños en las calles.

Palabras clave:
Miedo al crimen; Cohesión social; Victimización; Crimen; Sensación de inseguridad

Resumo:

Embora alguns estudos sugiram que a natureza das interações com a comunidade influencie o risco percebido de vitimização criminal, apenas algumas pesquisas têm testado essa associação no Brasil. Utilizando quatro pesquisas brasileiras de vitimização, realizamos modelos logísticos para examinar se os laços sociais e a coesão social estão associados à percepção de risco e medo do crime. Os resultados mostraram que apenas em alguns contextos a coesão social manifestou associação com o medo do crime. Especificamente, dois componentes da coesão social podem ser relevantes para esse fim: confiar nos vizinhos e obter ajuda; e a capacidade de distinguir vizinhos de estranhos nas ruas.

Palavras-chave:
Medo do crime; Coesão social; Vitimização; Crime; Sentimento de insegurança

Theoretical links between fear of crime and social cohesion

Perceiving that one is at risk of being the victim of a crime deteriorates one's quality of life. Violence and crime provoke changes in people's lives through feelings such as fear of crime, which in turn deepen social distance and social isolation (Soares 2006). Thus, fear of crime encourages many people to stay at home.

Also, fear and insecurity are thought to promote the corrosion of social capital (Gibson et al. 2002; Gainey Alper and Chappell 2011). Caldeira (2003), states that the sense of security in Sao Paulo depended not so much on the presence of crime, but on social distance, which leads to the abandonment of public space in two different ways. The first refers to the tendency of citizens to flee to private spaces. The second deals with a loss of confidence in democracy and an acceptance of authoritarian patterns of social control.

The term “fear of crime” emerged in the US as an object of scientific research in a context of growing interest by governments (Lee 1999, 2001). Since then, fear of crime has become an important policy issue in many countries and is widely recognized as a major concern for citizens (Ferraro 1995; Hale 1996; Soares 2006; van Kesteren, Mayhew and Nieuwbeetra 2000).

Recently, the debate on the conceptualization and measurement of fear of crime has received considerable attention in the literature. However, few studies specified the type of fear and the meaning that the feeling may take depending on the form of measurement. In general, they do not specify how “fear of crime” is similar or different from perceived risk of victimisation (Miethe and Lee 1984). Indeed, Yin (1980) points out that “fear of crime” is often not defined, rather it is measured by the individual's perception of the likelihood of being a victim of crime.

Ferraro and Lagrange (1987) discussed the range of meanings that “fear of crime” can take, from a cognitive perception of insecurity to emotional and psychological reactions to being victimized. On the other hand, fear itself can also be expressed by various reactions (Bilsky and Wetzels 1997).

In Latin America, research has focused on feelings of insecurity (Dammert and Arias 2007), which may incorporate other emotions beyond fear, such as anger or impotence. Kessler (2009, 2011) argues that a central feature of insecurity is the perceived randomness of danger and that insecurity does not refer equally to all violent crimes. Another focus of concern has been the management of perceived insecurity (Dammert and Malone 2003; Kessler 2011). The concept of insecurity has been often used in Latin America as a result of two factors: high crime rates and the way the media presents the phenomenon. Indeed, concern about insecurity is more intense and experience with crime closer in Latin America than in Europe or North America.

Thus, for the purpose of this article ‘feeling of insecurity’ will be considered a way to measure ‘fear of crime’ and both concepts will be used almost interchangeably, beyond the controversies that exist in the literature.

Researchers have attempted to establish the characteristics of individuals and the environment that may influence fear of crime. In this work, we focus on social cohesion. The central question we would like to answer is whether social cohesion can indeed reduce feelings of insecurity and fear of crime in Brazil.

Social Capital has been used both as a possible determinant of fear no crime and as a potential resource at the community level in order to improve feelings of security (Bursik 1988). Although there is no consensual definition of social capital, the central idea is that associations and social interactions among people empower individuals and facilitate cooperation for mutual benefit. In other words, social capital refers to networks of social support, local institutions, shared norms of trust and reciprocity, and collective activities among members of the community in search of a common good (Putnam 1993).

Even though social networks are considered to promote positive outcomes and greater welfare, the evidence of their influence on the reduction of anxiety and fear of crime is less clear. Agnew (1985) argues that social support can improve access to information and material resources, which may reduce the incidence of criminal victimisation.

Social Capital theory states that social support networks may improve general welfare, leading to higher levels of satisfaction and collective efficacy. High levels of social support are also considered to foster violence prevention, based on the assumption that individuals embedded in support networks will be more likely to undertake behaviour to protect themselves and others. Despite the apparent ambiguity of these theoretical links, the hypothesis that high levels of social support can reduce fear of crime has had an important role in the literature.

Collective Efficacy refers to shared expectations and mutual civic engagement by community members in local social control, with an emphasis on the combined capacity of residents to act together to generate solutions to local problems (Sampson 2004). Examples of community initiatives based on principles of collective efficacy include Neighbourhood Watch and public fora where community issues are discussed and solutions are agreed. As such, collective efficacy can help prevent crime through a variety of mechanisms. However, empirical evidence on the relationship between collective efficacy and fear of crime is not unanimous. While some studies show the effectiveness of programs such as Neighbourhood Watch in reducing fear of crime, others conclude that vigilance groups may inadvertently increase it (Rosenbaum 1987).

Social Integration is related to the individual's perception of belonging to his or her local environment, as well as one's connection to the community (Kasarda and Janowitz 1974). Specifically, social integration can be defined as personal investment in social ties with neighbours, emotional attachment to the community, participation in formal organizations, involvement in neighbourhood activities, information sharing within the neighbourhood, perception of similarities between residents and the presence of friends or family who live in the neighbourhood (Bursik and Grasmick 1993; Kanan and Pruitt 2002). The mains relevant hypothesis here is that those who are socially integrated within their neighbourhoods experience lower levels of fear of crime (Rountree and Land 1996). Empirical studies have produced mixed results, although substantial evidence seems to suggest an inverse relationship between levels of social integration and fear of crime (Kanan and Pruitt 2002; Rountree and Land 1996). According to Bursik and Grasmick (1993) and Gibson et al. (2002), measures of social integration sometimes lack methodological consistency. Hence, when researchers employ different measures of social integration and reach different conclusions about the effect on fear of crime, it is not readily apparent whether these differences are attributable to different methodologies or are indeed real differences due to the various components of social integration.

Formal and informal social control can foster a feeling of security. When there is no social control or it is not noticed, people tend to become insecure. It has been argued that fear of crime is not directly caused by the characteristics of the urban environment, since these characteristics may be a symbol of the community's capacity to exercise informal social control.

Ferraro (1995) applied symbolic interactionism to the interpretation of incivility and to the perception of the structural aspects of a community, both of which can provide information that later will form subjective estimates of the odds of victimisation. The author states that the relevant aspects of a community include physical location, people's activities, prevalence of crime, the physical environment and experience of victimisation. The individual defines risk through judgments and interpretations which depend, in turn, on how he or she defines the situation based on information that is obtained through social interactions. Thus, incivilities provide ecological information that shape perceptions of victimisation. In addition, a reputation for high incidence of crime or poverty are treated as signs of potential danger. For the author, fear is a response to perceived danger.

The importance of the ability of residents to regulate their neighbourhood has been frequently quoted in the literature as a correlate of low crime (Bursik 1988; Bursik and Grasmick 1993; Sampson and Raudenbush 1999). Jacobs (1961, 31-32) argues that “the public peace […] is not kept primarily by the police […] It is kept primarily by the intricate, almost unconscious, network of voluntary controls and standards among the people”.

Smith (1986) writes (1986, 128) that “fear is greatest among people who perceive their communities to be in decline when they are powerless to intervene” and adds that these feelings of lack of control are partly due to “…the uncertainties generated by the wide range of other urban events” (1986, 10) and, as such, represent displaced anxieties (Furstenburg 1971, 1972). These anxieties would be displaced from sources such as dissatisfaction with urban life through the deterioration of community life, poor quality services and social isolation. She concludes that this anxiety is primarily a feature of the neighbourhood, and not of the social groups within it (Smith 1986).

Farrall, Gray and Jackson (2007) argue that high levels of community efficacy and social cohesion, with low levels of distrust and anonymity, can inhibit fear of crime. Jackson (2004) found that the perception of social cohesion and informal social control predict risk perception in the sense that the greater the community confidence and the efficacy, the lower the perception of risk.

However, Villareal and Silva (2006) conducted a study on neighbourhoods in Belo Horizonte (Brazil) and found that social cohesion was associated to a high level of fear. They argue that high levels of social cohesion in the neighbourhood meant greater exchange of information on crime. Caldeira (2003) found in her research in São Paulo (Brazil) that “talk of crime” is an important factor influencing fear of crime. Covington and Taylor (1991) also concluded that the social bond increases fear while Kanan and Pruitt (2002) point out that the social bond has no effect on fear or on the perception of risk. Skogan (1986) also suggests that the exchange of information on neighbourhoods or areas where there was crime or antisocial behaviour affects the level of fear and perceived risk of victimisation.

Hence, even though social cohesion appears to be a relevant concept for the prediction of fear, research results are not consistent. While most of the literature seems to support this thesis, some studies question it or point in an opposite direction, i.e. high levels of social cohesion might be associated, in some contexts, to higher levels of fear.

In this study we will analyse the relationship between social cohesion and fear of crime considering two models of response of the community to fear of crime: fear-decline and fear-solidarity.

According to the fear-decline model, fear of crime encourages people to leave community life, as it inhibits social interaction, promoting the removal of life in the neighbourhood (Hale 1996; Skogan 1986; Hawdon et al. 2013). This model posits that physical and social disorder that triggers people's fear, which in turn leads to social isolation, weakening bonds, cohesion, trust in people, informal social control and reducing levels of collective efficacy, which consequently increases fear and criminality (Markowitz et al. 2001; Wyant 2008; Hawdon et al. 2013). Brunton-Smith (2011) argue that disorder probably increases fear more than the opposite, but both are related.

Conversely, the fear-solidarity model (Hawdon et al. 2013) holds that fear leads to greater solidarity in the community. The concept used here is Durkheim's “mechanical solidarity”, that is, the social integration of members of the community is based on similar values and beliefs, which Durkheim refers to as a “collective conscience” (Durkheim 1977). Some studies have already shown that fear of crime promotes solidarity, such as that developed by Oh and Kim (2009) who found that fear of crime among elderly residents increases interactions with neighbours and its perceived level of social cohesion. Even so, the overwhelming majority of studies that investigate the relationship between fear of crime and solidarity, conclude that fear reduces solidarity (Liska and Warner 1991).

In any case, neither model discards the possibility of reciprocal causality, since fear may not only be the cause, but also the consequence of increasing or declining social solidarity. For instance, trust in one's neighbours may help dispel fear. On the other hand, frequent conversations among neighbours over incidents of local crime may foster fear in comparisons with areas where people do not hear about them.

An empirical test of the relation between perceived insecurity and social cohesion

As explained above, feelings of insecurity can deteriorate public confidence and social cohesion. Indeed, Brazil has high crime rates and insecurity is considered one of the main problems of the country (Borges 2011). However, the relationship between insecurity and social cohesion is probably one of reciprocal causality, as previously argued, because the decline in social cohesion could also promote insecurity.

The empirical analysis will include victimisation surveys applied in several regions of Brazil by different institutions in different moments of time. Victimisation surveys can estimate the total number of crimes and also the degree to which people report them to the police.

First, we conducted a search of victimisation surveys in Brazil over the last few years to select those that contained, besides perception of insecurity, some questions that could be interpreted as social cohesion. Obviously, the possibility of getting access to microdata was an essential requisite for our study. We started by carrying out a search in the literature and by contacting specialists. After identifying surveys and checking the possibility of obtaining the respective databases, their questionnaires were analysed to see if they contained any question related to the relevant constructs.

We identified 8 victimisation surveys conducted in Brazil, but only four of them satisfied all the requirements: (1) ‘Survey of Living Conditions and Victimisation in the Metropolitan Area of Rio de Janeiro’ - Metropolitan Region of Rio de Janeiro (carried out by DataUFF in 2008); (2) ‘Victimisation Survey in the State of Mato Grosso’ - State of Mato Grosso (carried out by DataUFF in 2010); (3) ‘Survey on Urban Violence in the State of Goiás’ - Metropolitan Region of Goiania (carried out by the Faculty of Social Sciences of the Federal University of Goiás – UFG in 2007); and (4) ‘Victimisation Survey in Belo Horizonte’ - City of Belo Horizonte (carried out by the Federal University of Minas Gerais - Crisp/Ufmg in 2002).

Dependent variable

The core dependent variable is ‘feeling of insecurity’, one of the classical operationalisations of the concept of ‘fear of crime’. In Brazil, most victimisation surveys ask about the perception of safety while walking the streets in a given area (Borges 2011). In this work, we use two questions, one for the day and the other for the night. Thus, interviewees were asked how safe they felt when walking the streets of their neighbourhoods, either during the day or at night. The response options were: 1) very safe, 2) safe, 3) unsafe, 4) very unsafe. From these we created dichotomous variables (1: unsafe or very unsafe; 0: safe or very safe).

Figure 1 shows that the feeling of insecurity is always higher at night than during the day. The highest level was found in the city of Belo Horizonte, followed by Goiania. However, in Belo Horizonte the question is slightly broader: it refers to the feeling of insecurity when the person leaves the house, not just while waking in the neighbourhood.

Figure 1
Percentage of respondents who felt unsafe or very unsafe while walking the streets during the day and at night: Metropolitan Region of Rio de Janeiro, state of Mato Grosso, Metropolitan Region of Goiania and city of Belo Horizonte

Independent variables

As control socio-demographic variables, we included the respondents’ sex, age, education and how long they had lived in the neighbourhood.

Social cohesion is a construct that can be associated with different variables. Given that each of the four surveys used a different questionnaire, there was no single operationalisation for many concepts. A variable related to social cohesion in one of the studies is the “ability to recognize people who are not from the neighbourhood” when interviewees are walking in the street. Another relevant question was whether respondents speak to or receive visits from other residents of the neighbourhood. A third group of variables assesses whether people exchange pleasantries or favours with each other in the neighbourhood. A fourth variable connected to both social cohesion and collective efficacy is trust, measured through a direct question on whether the interviewee could trust his or her neighbours.

Finally, social cohesion was also measured by two indexes: a) degree in which neighbours believe they can count on each other for help, b) degree to which neighbours have already made requests for help in the past. In order to calculate these indexes, we use, respectively, the following questions: a) “can you count on your neighbours for the following things…?”; b) “do your neighbours usually ask for help in the following situations”. Both questions are applied to nine situations: aid in case of sickness, borrowing money, borrowing food, taking care of children or the elderly, borrowing objects, making purchases with your credit card, taking care of the car or of the house, and helping to resolve conflicts. In the case of the index that measured the degree in which neighbours can be counted on, possible answers are limited to ‘yes’ and ‘no’, so the index simply adds the positive answers in each of the nine above mentioned situations. The index ranges from 0 to 9, and a higher value indicates higher trust on one's neighbours.

As for the index that measured the degree in which neighbours actually ask for help in those same 9 situations, possible answers for each item were as follows: ‘frequently’, ‘rarely’, ‘never asked for help’ or ‘never appeared to need help’. We recoded those answers into dichotomous items: 0 - ‘never asked or never needed’; 1 – asked for help at least once, i.e. adding up the answers of ‘frequently’ and ‘rarely’. The final index is a final sum of those situations and also varies from 0 to 9.

Statistical models

Using logistic regression to model the feeling of insecurity in the neighbourhood during the day and at night, we evaluate the odds ratio (OR) of a person feeling insecure as a function of the explanatory factors. Table 1 reveals the results of several models: one for each of the 4 regions and, within the same region, one for daytime and another for night-time. The only exception was Goiania, where the question was only formulated for the night. In total we have 7 different models.

Table 1
Logistic Regression Models to estimate feeling of insecurity (Dependent variable= 0- ‘safe’ or ‘very safe’ or 1 – ‘unsafe’ or ‘very unsafe’)

	Metropolitan Region of Rio de Janeiro										State of Mato Grosso										Metropolitan Region of Goiania					City of Belo Horizonte
	During the day					During the night					During the day					During the night					During the night					During the day					During the night
	Descriptive Analysis (% or Average)			Odds Ratio		Descriptive Analysis (% or Average)			Odds Ratio		Descriptive Analysis (% or Average)			Odds Ratio		Descriptive Analysis (% or Average)			Odds Ratio		Descriptive Analysis (% or Average)			Odds Ratio		Descriptive Analysis (% or Average)			Odds Ratio		Descriptive Analysis (% or Average)			Odds Ratio
	Safe	Unsafe	Total			Safe	Unsafe	Total			Safe	Unsafe	Total			Safe	Unsafe	Total			Safe	Unsafe	Total			Safe	Unsafe	Total			Safe	Unsafe	Total
(Intercept)				0,17	***				1,03					0,1	***				0,26	***				5,08	**				0,45					1,65
Female	74,2%	25,8%	100,0%	1,28	***	44,9%	55,1%	100,0%	1,45	***	84,2%	15,8%	100,0%	1,36	**	66,4%	33,6%	100,0%	1,52	***	20,7%	79,3%	100,0%	2,74	***	43,6%	56,4%	100,0%	1,82	***	10,6%	89,4%	100,0%	2,51	***
Male	77,3%	22,7%	100,0%	1		50,9%	49,1%	100,0%	1		88,6%	11,4%	100,0%	1		76,8%	23,2%	100,0%	1		39,9%	60,1%	100,0%	1		57,7%	42,3%	100,0%	1		22,3%	77,7%	100,0%	1
Age	43,2	43,7	43,3	1		42,1	41,6	41,8	1		47,2	49,3	47,5	1		47,4	47,4	47,4	1		38,6	40,3	39,8	1,01	***	39,5	39,9	39,7	1,01	**	39,3	39,8	39,8	1
Complete higher education	64,6%	35,4%	100,0%	2,13	***	36,6%	63,4%	100,0%	1,88	***	87,8%	12,2%	100,0%	0,71		68,6%	31,4%	100,0%	0,98		32,8%	67,2%	100,0%	1,05		51,1%	48,9%	100,0%	1,3		12,2%	87,8%	100,0%	2,68	***
Complete high school	75,1%	24,9%	100,0%	1,75	***	43,8%	56,2%	100,0%	1,55	***	85,1%	14,9%	100,0%	0,91		70,1%	29,9%	100,0%	0,99		30,8%	69,3%	100,0%	1,22		48,0%	52,0%	100,0%	1,51		14,8%	85,2%	100,0%	2,19	**
Complete elementary school	78,4%	21,6%	100,0%	1,53	*	49,5%	50,5%	100,0%	1,11		86,9%	13,1%	100,0%	0,74		70,6%	29,4%	100,0%	1,02		31,0%	69,0%	100,0%	1,25		50,5%	49,5%	100,0%	1,42		15,5%	84,5%	100,0%	2,12	**
Incomplete elementary school	74,7%	25,3%	100,0%	1,61	**	52,3%	47,7%	100,0%	1,05		86,3%	13,7%	100,0%	0,76		71,1%	28,9%	100,0%	0,99		25,0%	75,0%	100,0%	1,61		50,8%	49,2%	100,0%	1,33		17,3%	82,7%	100,0%	1,76	*
Illiterate	85,3%	14,7%	100,0%	1		55,8%	44,2%	100,0%	1		84,1%	15,9%	100,0%	1		73,1%	26,9%	100,0%	1		27,9%	72,1%	100,0%	1		55,2%	44,8%	100,0%	1		24,1%	75,9%	100,0%	1
Victimised	71,5%	28,5%	100,0%	1,33	***	38,3%	61,7%	100,0%	1,55	***	81,7%	18,3%	100,0%	1,63	***	61,4%	38,6%	100,0%	1,78	***	28,0%	72,0%	100,0%	1,1		37,2%	47,9%	85,2%	1,34	***	13,0%	87,0%	100,0%	1,34	**
Not Victimised	78,1%	21,9%	100,0%	1		53,3%	46,7%	100,0%	1		87,5%	12,5%	100,0%	1		73,9%	26,1%	100,0%	1		30,0%	70,0%	100,0%	1		46,5%	42,6%	89,1%	1		17,1%	82,9%	100,0%	1
Does not attend street parties/events organized by neighbours	75,5%	24,5%	100,0%	1,14		47,5%	52,5%	100,0%	1,1
Attends street parties/events organized by neighbours	76,0%	24,0%	100,0%	1		48,1%	51,9%	100,0%	1
Does not attend religious activities other than mass/cult Attends religious activities other than mass/cult	75,0%	25,0%	100,0%	1,03		47,9%	52,1%	100,0%	1
Attends religious activities other than mass/cult	77,1%	22,9%	100,0%	1		47,2%	52,8%	100,0%	1
Does not attend meetings of associations, political parties or unions	75,5%	24,5%	100,0%	0,99		50,6%	55,0%	105,5%	1,04
Attends meetings of associations, political parties or unions	77,2%	22,8%	100,0%	1		44,8%	53,5%	98,4%	1
Does not participate in community activities to build houses, clean streets, etc.	75,6%	24,4%	100,0%	0,76	*	47,7%	52,3%	100,0%	0,75	*
Participates in community activities to build houses, clean streets, etc.	76,5%	23,5%	100,0%	1		47,7%	52,3%	100,0%	1
Does not meet friends in bars, clubs, cafes and soccer fields	75,4%	24,6%	100,0%	1,19		49,0%	51,0%	100,0%	1,01
Meets friends in bars, clubs, cafes and soccer fields	76,1%	23,9%	100,0%	1		45,9%	54,1%	100,0%	1
Does not talk with neighbours/acquaintances in the streets	75,3%	24,7%	100,0%	0,96		46,8%	53,2%	100,0%	0,93
Talks with neighbours/acquaintances in the streets	75,8%	24,2%	100,0%	1		47,9%	52,1%	100,0%	1
Has lived over 3 years in the neighbourhood	75,1%	24,9%	100,0%	1,09		48,0%	52,0%	100,0%	0,8		86,2%	13,8%	100,0%	1,22		71,3%	28,7%	100,0%	0,95		30,1%	69,9%	100,0%	0,64	*	51,8%	48,2%	100,0%	0,87		15,8%	84,2%	100,0%	1,02
Has lived 1-3 years in the neighbourhood	76,5%	23,5%	100,0%	1,14		45,3%	54,7%	100,0%	1,04		85,0%	15,0%	100,0%	1,14		70,5%	29,5%	100,0%	0,91		29,5%	70,5%	100,0%	0,75		52,2%	47,8%	100,0%	0,88		18,8%	81,2%	100,0%	0,79	*
Has lived less than 1 year in the neighbourhood	79,3%	20,7%	100,0%	1		46,8%	53,2%	100,0%	1		86,1%	13,9%	100,0%	1		68,4%	31,6%	100,0%	1		25,5%	74,5%	100,0%	1		47,7%	52,3%	100,0%	1		13,7%	86,3%	100,0%	1
Very rarely talks to neighbours (less than once a week)																										48,6%	51,4%	100,0%	1,06		14,1%	85,9%	100,0%	1,11
Regularly talks to neighbours (at least once a week)																										51,1%	48,9%	100,0%	1		17,2%	82,8%	100,0%	1
Never talks to neighbours																					27,3%	72,7%	100,0%	1,22
Talks to neighbours (“daily’, “frequently’ or ‘rarely’)																					29,8%	70,2%	100,0%	1
Very rarely exchanges pleasantries with neighbours (less than once a week)																										50,3%	49,7%	100,0%	0,87		14,9%	85,1%	100,0%	1,22
Regularly exchanges pleasantries with neighbours (less than once a week)																										49,4%	50,6%	100,0%	1		17,9%	82,1%	100,0%	1
Neighbours seldom quarrel with one another (rarely’ or ‘never’)																										50,2%	49,8%	100,0%	0,83		16,2%	83,8%	100,0%	0,84
Neighbours often quarrel with one another (‘frequently’ or ‘sometimes’)																										51,3%	48,7%	100,0%	1		16,9%	83,1%	100,0%	1
Cannot distinguish neighbours from nonneighbours in the street																										46,1%	53,9%	100,0%	1,2		13,0%	87,0%	100,0%	1,22
Can distinguish neighbours from non-neighbours in the street																										51,9%	48,1%	100,0%	1		17,4%	82,6%	100,0%	1
Does not trust any neighbour	73,7%	26,3%	100,0%	1,2		41,8%	58,2%	100,0%	1,2		80,3%	19,7%	100,0%	1,69		65,3%	34,7%	100,0%	1,3	*
Trusts at least some neighbours (‘some’ or ‘most’)	75,8%	24,2%	100,0%	1		49,1%	50,9%	100,0%	1		87,6%	12,4%	100,0%	1		72,0%	28,0%	100,0%	1
Index - Degree in which can count on neighbours for	4,5	4,0	4,4	0,94	***	4,7	4,0	4,3	0,91	***	4,4	4,0	4,4	0,99		4,5	4,2	4,4	0,97
Index - Degree in which neighbours actually ask for help	3,0	3,0	3,0	1,04	*	3,0	3,0	3,0	1,06	***	2,7	2,6	2,7	1,01		2,7	2,8	2,7	1,04	*
There are no strangers walking in the neighbourhood																					36,3%	63,7%	100,0%	0,69	**
There are strangers walking in the neighbourhood																					26,1%	73,9%	100,0%	1
People never fight or insult each other on the streets of your neighbourhood																					34,6%	65,4%	100,0%	0,68	*
your neighbourhood People fight or insult each other on the streets of your neighbourhood (‘frequently’ or ‘rarely’)																					23,9%	76,1%	100,0%	1
There are never rude/uncivilised people in your neighbourhood																					33,3%	66,7%	100,0%	0,85
There are rude/uncivilised people in your neighbourhood (‘frequently’ or ‘rarely’)																					25,2%	74,8%	100,0%	1
There is never trouble between people at bus-stops in your neighbourhood																					32,3%	67,7%	100,0%	0,78	*
There is trouble between people at bus-stops in your neighbourhood (‘frequently’ or ‘rarely’)																					24,2%	75,8%	100,0%	1
There is never excessive noise on the streets of your neighbourhood																					34,1%	65,9%	100,0%	0,79	*
There is excessive noise on the streets of your neighbourhood (‘frequently’ or ‘rarely’)																					26,3%	73,7%	100,0%	1

• ^***
  P-vaLor <0.001;
• ^**
  P-vaLor <0.010;
• ^*
  P-vaLor < 0.050
Source:

With regard to gender, we confirm the results found in other studies (Warr 1984; Stafford and Galle 1984): women feel more insecure than men. In Goiania the chances of a woman feeling insecure were 2.74 times higher than those of a man. In Belo Horizonte the corresponding figure was 2.51 higher for women than for men (at night).

Age was significant only in Goiania for insecurity at night and in Belo Horizonte for insecurity during the day. In both models, older people feel more unsafe, similar to what has been found in the literature (Warr 1994; Borges 2011).

Socioeconomic status is also widely used to explain feelings of insecurity. According to Maxfield (1987), people with lower socioeconomic status feel less secure. Davis and Peixoto (2003), on the other hand, found opposite results in the Metropolitan Region of Belo Horizonte, i.e., people with higher socioeconomic status had a higher perceived risk of victimisation. Indeed, criminological research in Brazil has typically found that people of higher socioeconomic status tend to be victimised more by property crimes and less by ‘crimes against the person’. In the models developed in this paper, the variable representing socioeconomic status (education) was significant in Rio de Janeiro (at night and during the day) and in Belo Horizonte (only at night). Thus, people with a higher level of schooling tended to feel more insecure in both cities. In Rio de Janeiro, previous studies showed that people with more schooling were more likely to feel insecure because they perceived themselves as attractive targets for crimes (Borges 2011).

Having been a victim of crime is another relevant variable in the literature, though there is controversy about the type of effect that it may have on perception of insecurity (Borges 2011). In our data, an experience of victimisation is strongly associated to perceived insecurity in all but one model (Goiania).

In Goiania we tested variables which reflect physical and social disorder in the neighbourhood: people cursing or fighting, ‘trouble’ at the bus stop, excessive noise and having strangers walking in the neighbourhood were all significant in the direction that any such disorder is positively associated to feelings of insecurity.

As for variables that measure whether people talk to neighbours and mutual help, we found a few interesting results even though most of them were not significant. In Rio de Janeiro, only the variable “participates in effort to build homes or street cleaning, etc.” was significant. Indeed, our hypothesis was that involvement in collective tasks would help reduce the feeling of insecurity. However, results were contrary to this, for people who participated in such efforts tended to feel more insecure. A possible alternative hypothesis for this result is the exchange of information about the crime or the “talk of crime”² (Caldeira 2003). It could also be argued that in areas where people feel more threatened by violence, they could decide to invest more in these community actions, as argued by the fear-solidarity model. In other words, fear of crime could act as a trigger to increase community solidarity and motivate residents to come together, responding collectively to common threats.

It is also possible that poor communities, where social ties are more intense and people tend to help each other out of necessity or cultural norms, are also more violent and therefore fear is more prevalent for local residents. If this is the case, there would not be a necessary theoretical link between cohesion and fear since both would be explained by other phenomena.

Another behaviour related to social cohesion is “talking to neighbours.” In Belo Horizonte the questionnaire asked whether respondents talk to their neighbours. However, this variable was not significant, so that talking to one's neighbours does not seem to reduce feelings of insecurity.

Living for a longer time in the neighbourhood reduces perceived insecurity at night in Goiania. The theory here is that familiarity with the surroundings would lead to less uncertainty and fear. However, the effect is not significant during the day.

In Belo Horizonte, at night, the result is even more intriguing since those who feel safer belong to the intermediate category (have lived between 1 and 3 years in the neighbourhood).

Indeed, in Belo Horizonte the only variables related to social cohesion that yielded significant results were: a) exchanging pleasantries with neighbours is associated to lower insecurity but only at night; b) quarrels among neighbours appear to correlate insecurity, only during the day; c) the ability to distinguish neighbours from non-neighbours (an index of familiarity with one's surroundings) seems to be linked to perception of insecurity, but just during the day. These results go in the direction of the fear-decline model in which declining social cohesion is associated to more fear.

Trusting one's neighbours is connected to a higher perception of security in Mato Grosso (both day and night), but the effect is not significant for Rio de Janeiro and Goiania.

The index that measures whether neighbours can be counted on is, in fact, associated with lower levels of insecurity in Rio de Janeiro (both day and night) which shows that the greater the social integration, the lower the fear levels, but not in Mato Grosso. As for the index of actual demand for help between neighbours, this demand is, contrary to the hypothesis, linked to feelings of insecurity, both in Rio (day and night) and in Mato Grosso (only during the night). For some reason, people feel unsafe in areas where neighbours tend to ask favours from each other. This last result seems to go in the direction of the fear-solidarity mode, which might be mean, for example, that expression of solidarity becomes more effective after people have been collective targets of criminal events, such as shootings (Hawdon et al. 2013).

Final considerations

The seven statistical models applied to four different victimisation surveys in Brazil show weak empirical evidence in favour of a link between social cohesion and fear of crime. Indeed, most items yielded non-significant results. Of those that did show significance, most, though not all, correlated in the hypothesized direction, i.e. higher levels of social cohesion associated to lower levels of fear, supporting the fear-decline model.

Effects on perceived insecurity were not always consistent during the day and at night, thus questioning their robustness. In addition, results were not always consistent between cities or states, whereas theory would predict similar results in different contexts.

In Goiania, a systematic association between signs of physical and social disorder and perception of insecurity was found. The presence of fights, insults, rowdy behaviour or excessive noise in the neighbourhood were linked to insecurity, as predicted. Unfortunately, these items were absent in the other questionnaires. In any case, these events could be construed as measuring insecurity itself in an indirect manner as much as measuring social cohesion, considering that some of them are episodes that directly threaten the physical integrity. Hence, one might argue that there is some endogeneity or circularity in this result.

Also in Goiania, the presence of strangers in the neighbourhood is linked to fear, which appears to confirms that familiarity with people or with territories breeds perception of security. A related item, only present in Belo Horizonte, demanded whether respondents could distinguish neighbours from non-neighbours in the street. As predicted, the ability to recognise your neighbours, another sign of familiarity, was associated to less fear, but only during the day.

Another item related to familiarity and to attachment to the territory would be the amount of time the respondent had lived in the neighbourhood. The hypothesis was that the longer the person had spent in that area, the safer he or she would feel. This was tested in all four surveys, but the effect was confirmed only in Mato Grosso and yet only during the night.

Relationships with one's neighbours seemed to be relevant, though not always as predicted. Those who trusted their neighbours felt less unsafe in Mato Grosso but not in Rio de Janeiro or in Goiania. In Belo Horizonte, where the question was different, people who never had quarrels with their neighbours or who exchanged pleasantries with them felt safer, but the first effect was present only during the day and the second only at night. Talking to one's neighbours appeared to have no impact in Belo Horizonte.

The index that measured whether neighbours could be counted on for help under different circumstances showed, as expected, a negative association with fear, but only in Rio and not in Mato Grosso. On the other hand, the index that tapped actual demands for help from neighbours in the same circumstances yielded a surprising positive association in Rio de Janeiro (both day and night) and in Mato Grosso (only during the night). In other words, areas where neighbours do ask each other for help are those areas where people tend to feel unsafe, in line with the fear-solidarity model. These contradictory results underline the complex relationships between social bonds and perception of security.

The survey in Rio de Janeiro had a unique set of questions on participation in social activities and associations such as: street parties, religious activities, meetings of associations and political parties, community action to build houses or clean streets, and social gatherings in bars or clubs. From all of these, the only significant result contradicted our hypothesis: those who did not participate in community actions to build houses or clean streets felt safer. The areas where such activities exist might be poorer and more subjected to violence in the first place, but it is still a surprising result for collective social action is supposed to inhibit fear.

In short, our data seem to lend mild support to the hypothesis that, in some circumstances and in some areas, signs of social cohesion may be associated to feelings of security. Within the concept of social cohesion, two dimensions appear to be particularly relevant for this association: the first one is trusting one's neighbours and their willingness to help each other; the second one is the ability to distinguish neighbours from strangers in the street, which is closely connected to the notion of familiarity. However, even these effects appear not to be universal and robust in Brazil.

As such, these results seem to indicate that the possible link between fear and social cohesion is much more tenuous in countries in the global South, such as Brazil, than it appears in the literature from North American or European countries.

• 2
  The “talk of crime” refers to conversations, stories, comments or jokes that have crime as a theme (Caldeira 2003).
• Os textos deste artigo foram conferidos pela Poá Comunicação.

Referências

• Agnew, Robert S. 1985. Neutralizing the impact of crime. Criminal justice and behavior 12 (2): 221-239. https://doi.org/10.1177/0093854885012002005
  » https://doi.org/10.1177/0093854885012002005
• Bilsky, Wolfgang and Peter Wetzels. 1997. On the relationship between criminal victimisation and fear of crime. Psychology, Crime and Law 3 (4): 309-318. https://doi.org/10.1080/10683169708410826
  » https://doi.org/10.1080/10683169708410826
• Borges, Doriam. 2011. O medo do crime na cidade do Rio de Janeiro: uma análise sob a perspectiva das crenças de perigo Curitiba: Editora Appris.
• Brunton-Smith, Ian. 2011. Untangling the relationship between fear of crime and perceptions of disorder: evidence from a longitudinal study of young people in England and Wales. The British Journal of Criminology 51 (6): 885-899. https://doi.org/10.1093/bjc/azr064
  » https://doi.org/10.1093/bjc/azr064
• Bursik, Robert. 1988. Social disorganization theories of crime and delinquency: problems and prospects. Criminology (26): 519-551. https://doi.org/10.1111/j.1745-9125.1988.tb00854.x
  » https://doi.org/10.1111/j.1745-9125.1988.tb00854.x
• Bursik, Robert and Harold Grasmick. 1993. Neighbourhoods and crime: the dimensions of effective community control New York: Lexington Books.
• Caldeira, Tereza. 2003. Cidade de muros: crime, segregação e cidadania em São Paulo São Paulo: Edusp.
• Convigton, Jeanette and Ralph Taylor. 1991. Fear of crime in urban residential neighbourhoods: implications of between – and within – neighbourhood sources for current models. The Sociological Quarterly 32 (2): 231-249. https://doi.org/10.1111/j.1533-8525.1991.tb00355.x
  » https://doi.org/10.1111/j.1533-8525.1991.tb00355.x
• Dammert, Lucía and Patricia Arias. 2007. Construcción de una sociedad temerosa: crimen y castigo en Chile. In En los márgenes de la ley. Inseguridad y violencia en el Cono Sur, edited by Patricia Arias, 177-208. Buenos Aires: Paidós.
• Dammert, Lucía and Mary Malone. 2003. Fear of crime or fear of life? Public insecurities in Chile. Bulletin of Latin American Research 1 (22): 79-101. https://doi.org/10.1111/1470-9856.00065
  » https://doi.org/10.1111/1470-9856.00065
• Davis, Corinne and Betania Peixoto. 2003. Medo e espaço urbano: uma análise da percepção do risco de vitimização local e não local. Congresso Brasileiro de Sociologia(11): 2-26.
• Durkheim, Émile. 1977. A divisão do trabalho social Lisboa: Presença.
• Farrall, Stephen, Emily Gray and Jonathan Jackson. 2007. Theorising the fear of crime: the cultural and social significance of insecurities about crime. Experience & expression in the fear of crime working paper (5): 1-35. http://dx.doi.org/10.2139/ssrn.1012393
  » http://dx.doi.org/10.2139/ssrn.1012393
• Ferraro, Kenneth. 1995. Fear of crime: interpreting victimisation risk Albany: State University of New York Press.
• Ferraro, Kenneth and Randy Lagrange. 1987. The measurement of fear of crime. Sociological Inquiry 57 (1): 70-101. https://doi.org/10.1111/j.1475-682X.1987.tb01181.x
  » https://doi.org/10.1111/j.1475-682X.1987.tb01181.x
• Furstenberg, Frank. 1971. Public reaction to crime in the streets. The American Scholar 40 (4): 601-610.
• Furstenberg, Frank. 1972. Fear of crime and its effects on citizen behavior. In Crime and Justice: a symposium, edited by Albert Biderman, 601-610. New York: Nailberg.
• Gainey, Randy, Mariel Alper and Allison Chappell. 2011. Fear of crime revisited: examining the direct and indirect effects of disorder, risk perception, and social capital. American Journal of Criminal Justice 36 (2): 120-137. https://doi.org/10.1007/s12103-010-9089-8
  » https://doi.org/10.1007/s12103-010-9089-8
• Gibson, Chris; Jihong Zaho; Nicholas Lovrinc, Michael Gaffney. 2002. Social integration, individual perceptions of collective efficacy, and fear of crime in three cities. Justice Quarterly 19 (3): 537-564. https://doi.org/10.1080/07418820200095341
  » https://doi.org/10.1080/07418820200095341
• Hale, Chris. 1996. Fear of crime: a review of the literature. International Review of Victimology (4): 79-150. https://doi.org/10.1177/026975809600400201
  » https://doi.org/10.1177/026975809600400201
• Hawdon, James, Pekka Rasanen, Atte Oksanen and Miika Vuori. 2013. Social responses to collective crime: assessing the relationship between crime-related fears and collective sentiments. European Journal of Criminology 11 (1): 39-56. https://doi.org/10.1177/1477370813485516
  » https://doi.org/10.1177/1477370813485516
• Jackson, Jonathan. 2004. Experience and expression: social and cultural significance in the fear of crime. British Journal of Criminology 44 (6): 946-966. https://doi.org/10.1093/bjc/azh048
  » https://doi.org/10.1093/bjc/azh048
• Jacobs, Jane. 1961. The death and life of great american cities New York: Random House.
• Liska, Allen E. and Barbara D. Warner. 1991. Functions of crime: a paradoxical process. American Journal of Sociology 96 (6): 1441-1463. https://doi.org/10.1086/229692
  » https://doi.org/10.1086/229692
• Kanan, James and Matthew Pruitt. 2002. Modeling fear of crime and perceived victimisation risk: the (in)significance of neighbourhood integration. Sociological Inquiry 72 (4): 527-548. https://doi.org/10.1111/1475-682X.00033
  » https://doi.org/10.1111/1475-682X.00033
• Kasarda, John and Morris Janowitz. 1974. Community attachment in mass society. American Sociological Review 39 (3): 328-339. https://doi.org/10.2307/2094293
  » https://doi.org/10.2307/2094293
• Kessler, Gabriel. 2009. El sentimiento de inseguridad. Sociología del temor al delito Buenos Aires: Siglo XXI.
• Kessler, Gabriel. 2011. La extensión del sentimiento de inseguridad en América Latina: relatos, acciones y políticas en el caso argentino. Revista de Sociología e Política 19 (40): 83-97. https://doi.org/10.1590/S0104-44782011000300007
  » https://doi.org/10.1590/S0104-44782011000300007
• Lee, Murray. 1999. The fear of crime and self-governance: towards a genealogy. The Australian and New Zealand Journal of Criminology 32 (3): 227-246. https://doi.org/10.1177/000486589903200303
  » https://doi.org/10.1177/000486589903200303
• Lee, Murray. 2001. The genesis of fear of crime. Theoretical Criminology 5 (4): 467-485. https://doi.org/10.1177/1362480601005004004
  » https://doi.org/10.1177/1362480601005004004
• Markowitz, Fred, Paul Bellair, Allen Liska and Jianhong Liu. 2001. Extending social disorganization theory: modeling the relationships between cohesion, disorder, and fear. Criminology 39 (2): 293-319. https://doi.org/10.1111/j.1745-9125.2001.tb00924.x
  » https://doi.org/10.1111/j.1745-9125.2001.tb00924.x
• Maxfield, Michael. 1987. Explaining the fear of crime: evidence from the 1984 British crime survey. Home Office Research Study (41). London: Home Office.
• Miethe, Terance and Gary Lee. 1984. Fear of crime among older people: a reassessment of crime-related factors. The Sociological Quarterly 25 (3): 397-415. https://doi.org/10.1111/j.1533-8525.1984.tb00199.x
  » https://doi.org/10.1111/j.1533-8525.1984.tb00199.x
• Oh, Joong‐Hwan and Sangmoon Kim. 2009. Aging, neighborhood attachment, and fear of crime: testing reciprocal effects. Journal of Community Psychology 37 (1): 21-40. https://doi.org/10.1002/jcop.20269
  » https://doi.org/10.1002/jcop.20269
• Putnam, Robert. 1993. Comunidade e democracia: a experiência da Itália Moderna Rio de Janeiro: Editora da Fundação Getúlio Vargas.
• Rosenbaum, Dennis. 1987. The theory and research behind neighborhood watch: is it a sound fear and crime reduction strategy? Crime & Delinquency 33 (1): 103-134. https://doi.org/10.1177/0011128787033001007
  » https://doi.org/10.1177/0011128787033001007
• Rountree, Pamela and Kenneth Land. 1996. Perceived risk versus fear of crime: Empirical evidence of conceptually distinct reactions in survey data. Social Forces 74 (4): 1353-1376. https://doi.org/10.1093/sf/74.4.1353
  » https://doi.org/10.1093/sf/74.4.1353
• Sacco, Vincent. 1993. Social support and the fear of crime. Canadian J. Criminology (35): 187-196. https://doi.org/10.3138/cjcrim.35.2.187
  » https://doi.org/10.3138/cjcrim.35.2.187
• Sampson, Robert. 2004. Neighbourhood and community: collective efficacy and community safety. New Economy (11): 106-113. https://doi.org/10.1111/j.1468-0041.2004.00346.x
  » https://doi.org/10.1111/j.1468-0041.2004.00346.x
• Sampson, Robert and Stephen Raudenbush. 1999. Systematic social observation of public spaces: a new look at disorder in urban neighbourhoods. American Journal of Sociology 105 (3): 603-651. https://doi.org/10.1086/210356
  » https://doi.org/10.1086/210356
• Skogan, Wesley. 1986. Fear of crime and neighbourhood change. Crime and Justice (8): 203-229. https://doi.org/10.1086/449123
  » https://doi.org/10.1086/449123
• Smith, Susan. 1986. Crime, space and society Cambridge: Cambridge University Press.
• Soares, Luiz Eduardo. 2006. Legalidade libertária Rio de Janeiro: Editora Lumen Juris.
• Stafford, Mark and Omer Galle. 1984. Victimisation rates, exposure to risk, and fear of crime. Criminology 22 (2): 173-185. https://doi.org/10.1111/j.1745-9125.1984.tb00295.x
  » https://doi.org/10.1111/j.1745-9125.1984.tb00295.x
• Thompson, Estina and Neal Krause. 1998. Living alone and neighborhood characteristics as predictors of social support in late life. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 53 (6): 354-364. https://doi.org/10.1093/geronb/53B.6.S354
  » https://doi.org/10.1093/geronb/53B.6.S354
• Van Kesteren, Johannes, Pat Mayhew and Paul Nieuwbeetra. 2000. Criminal Victimisation in 17 Industrialised Countries NSCR Report 187. Haia: Wodc.
• Villareal, Andrés, Braulio Silva. 2006. Social cohesion, criminal victimisation and perceived risk of crime in brazilian neighbourhood. Social Forces 84 (3): 1725-1753. https://doi.org/10.1353/sof.2006.0073
  » https://doi.org/10.1353/sof.2006.0073
• Warr, Mark. 1984. Fear of victimisation: why are women and the elderly more afraid? Social Science Quarterly 65 (3): 681-702.
• Warr, Mark. 1994. Public perceptions and reactions to violent offending and victimization. Understanding and preventing violence (4): 1-66.
• Wyant, Brian R. 2008. Multilevel impacts of perceived incivilities and perceptions of crime risk on fear of crime: isolating endogenous impacts. Journal of research in crime and delinquency 45 (1): 39-64. https://doi.org/10.1177/0022427807309440
  » https://doi.org/10.1177/0022427807309440
• Yin, Peter. 1980. Fear of crime among the elderly: some issues and suggestions. Social Problems 27 (4): 492-504. https://doi.org/10.2307/800177
  » https://doi.org/10.2307/800177

Publication Dates

• Publication in this collection
  10 Jan 2022
• Date of issue
  Sep-Dec 2021

History

• Received
  20 Nov 2019
• Accepted
  25 Mar 2021
• Published
  08 Nov 2021