Fear Of Crime And Western Criminology Criminology Essay

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Introduction

The last decades fear of crime is one of the most intensively and since some years critically discussed subject in international especially western criminology. Fear of crime became one of the most important topics in criminology. Lee (2001, p. 467) points out: "Since the late 1960s the 'fear of crime' has progressively become a profoundly engaging field of study for criminologists and other social researchers. More resently debates about what 'fear of crime' might be and how it might be measured have proliferated and intensified. This is particularly true of the field since the early 1980s". Hale (p. 480) traces back the interest in fear of crime to the political situation in the USA, but also the "increasing sophistication of statistical inquiry; criminological concern with new forms of crime statistics; the emergence of victim surveys; rising rates of recorded crime in the USA and new attempts to govern this; racialized concers about 'black rioting'; a particular form of populist political discourse; and a historical moment where the conditions of possibility were such that these seemingsly diffuse discourses cold converge - the debating and passing of The Omnibus Crime Control and Safe Streets Act 1968" (see also Beckett and Sasson 2004).

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The media get more and more interest on the issue of fear, on the background of a stronger competition between the increasing number of medias. They understood that crime is a topic dealing with fear and that news about increasing fear of crime rates, presented by polls and research sells. Crime and fear of crime was an important topic for the media to be reported. Nevertheless the media are not first interested in giving an overview of crime and crime development but reported "what sells", that is spectacular and severe crimes, having the effect that people could have the impression, this is "crime". This way of reporting crimes in the media also had influence on feelings of unsafety (Kerner and Feltes 1980; Roberts and Doob 1990; Beckett and Sasson 2004). In Germany and other western European countries a debate about fear of crime began especially in the beginning of the 1980s, also here on the background of crime and/or victimization surveys revealing a high rate of people feeling more or less "fear of crime" (see critically Boers 1991; Reuband 1995). The results of the numerous studies often showed different results with few international more or less stable outcomes, like that women feel more fears than men. If elderly people are more fearful than younger ones or people with experiences of victimization in comparison with those without victimization is for example discussed controversial (see the summary of findings by Hale 1996; Zarafonitou 2008).

The debate about an increasing "fear of crime" rate as measured in crime and victimization surveys increased especially on the background of increasing "fears" in society on the background of deep changes in society, like the more and more opening of the borders, especially to the countries of the former Sovjet Union, in Germany the reunification of both parts of Germany, on this background an increasing migration of people, especially from the poorer countries to the western, more affluent societies. The increasing numbers of "foreigners", the public discussion of more and more "problems" in society, like unemployment, environmental problems, like air pollution, increasing prices, more and more costs for the health system and an "increasing" crime rate resulted in a feeling in society that there are more and more risks, also risks that the government cannot really solve. The society was seen as a "risk-society" (see Beck 1986). On this background criminologists and social scientists measured more and more "fear of crime", methodologists understood the same time more and more that this "fears" are not only fear of crime but a mixture of different feelings of unsecurity, angers, about politics, worry and similar emotions (Skogan 1993; Sessar 2008). Unclear unsafeties can be reduced if we find the reason for it. Risks and fears became political constructions, used for establishing responsibilities (Sessar and Stangl 2007, S. 14). Hollway and Jefferson (1997, p. 263) point out that "fear of crime … is an unconscious displacement of other fears which are far more intractable". Methodologists showed more and more that the measurement of fear of crime is not very valid, the standard question used in a lot of surveys internationally, asking for feelings of fear walking alone in the evening in the neighbourhood was more and more critisized (Kreuter 2002). The same time methodologists showed the influence on data collecting, the questionnaires and the wording of questions on the results of surveys (see Kury and Wuerger 1993; Kury 1994). Sessar (2007, S. 149; 2006) who organized together with colleagues an international comparative empirical project about anxiety in big European cities from east and west (Amsterdam, Budapest, Hamburg, Krakov and Wienna) discusses the background of fears in big cities. To him the standard question asks for unsafety and only criminology has interpreted the results as fear of "crime".

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In western countries, also Germany, the discussion about an "increasing" crime rate and especially about "fear of crime" resulted in measures especially against fear like a movement in developing community crime prevention projects from the beginning of the 1990s until today (see Obergfell-Fuchs and Kury 1995; Obergfell-Fuchs 2001; Dölling et al. 2003; Bannenberg et al. 2005). Meanwile thousands of German cities have organized more and more sophisticated crime prevention projects and measures to reduce crime, especially "fear of crime" (see Bundeskriminalamt 2001).

More and more methodologist pointed out critically the way to measure fear of crime and showed that the results of most surveys don't not only show fear of crime but a mixture of different fears (Ferraro and LaGrange 1987; Kreuzer 2002; Kury and Ferdinand 1998; Kury 2008; Kury and Obergfell-Fuchs 2008). In England for example Farrall and his research group showed in excellent experiments that fear of crime measured with usual instruments like standardized questionnaires using the standard question is much lower than the results show (see Farrall et al. 1997; 2000). Kury and his group could show in comparative experimental research the same results for Germany (see Kury et al. 2004a; 2004b; 2004c; 2005; Kury and Obergfell-Fuchs 2008). In additional experimental surveys the authors could also show that the frequency of feelings of fear of crime is relatively seldom (see Farrall and Gadd 2004; Feistritzer and Stangl 2006). More and more scientists asked for a more sophisticated and differentiated measurement and discussion of fear of crime (see Hirtenlehner 2008a; 2008b; Kaal et al. 2008; Vanderveen 2006; 2008; Gray et al. 2008).

According to some studies fear of crime and the public discussion of it also had beside other changements in society the effect of an increasing punitiveness, of a society of more control (Garland 2001; Serrano-Maillo and Kury 2008). Fearful people are asking more for sharp reactions for offenders. On this background politicians not only in western countries sharpened the laws often with the effect of an increasing imprisonment rate and as consequence higher costs for punishing offenders. A lot of comparative research meanwhile shows that the effect of sharper reactions on crime rates is very questionable (see Kury and Ferdinand 2008; Kury et al. 2009). As a central problem also in measuring punitiveness very often is overseen that punitiveness is like fear of crime a very complex and under-theorized topic. The measurement of these complex constructs is in the beginning. Brown (2006, p. 288) points out for the USA that "generalizing and casting of blame for the rise of punitive policies on the abstract 'American public' has persisted despite evidence on the complexity and relative moderation of public views on crime control" (see also Cullen et al 2000; 2002) . Mathews (2005) critisizes correctly a missing clear conceptualization of punitiveness and on this background not clear results about punitive attitudes in society. Roberts and his colleagues could show in different studies for example a strong influence of the information about criminal cases on the attitudes about the punishment of the offenders (see Doob and Roberts 1983; Roberts 1992; Roberts and Hough 2002).

In Germany we had the last years a controversial discussion about the question if Punitivity really increased in the country or not. One problem in the discussion also here is a non-exact definition what is understood with "punitiveness". There is missing a clear definition of what punitiveness is (see above). Kury et al. (2004) differentiated in at least three different sections of punitiveness: - punitiveness on the level of attitudes to punishment of the public, - as reactions on the political level in form of new sharper laws and - as reactions on the level of the courts in form of sharper punishments. Punitivity can also seen for example on the level of reactions of the police to people on the streets like foreigners, homeless or offenders. Some authors argue that we have an increasing punitiveness also here but the problem is not yet seen by the criminologists (see Sack 2006). Other experts could show that the punitiveness in Germany is not really increasing, at least not if proofing the attitudes to punishment of the public or the sentencing of the courts (Reuband 2006). On the level of political decisions in form of sharper laws there can be seen also here an increasing Punitivity (see Kury et al. 2004; Kury and Ferdinand 2008; Kury 2008). These results were also found in international studies (see for example the articles in Kury 2008, especially Yoshida 2008; Serrano-Maillo and Kury 2008; Kury 2009)

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Methodological studies showed the last years more or less simila results to the fear of crime research: the results collected with the standardized questionnaires are not very valid. The complexity of the concept Punitivity cannot be measured by simple questions like the attitude to death penalty for example, especially in countries like Germany which abolished it decades ago (1949). Frost speaks about a "mismeasure of punishment", Kury (1995) asked how punitive the public really are and discusses the influence of different questions in standardized instruments on the results about Punitivity. In a comparable research project as that about methodological influences by research methodology on the results (see above) Kury and Obergfell-Fuchs (2008) could show similar results. If asking people more accurate and differentiated about their attitudes to punishment instead of using standardized questionnaires with the common questions about punitiveness the results show that the public is much less punitive that the common results of surveys show.

International Surveys including countries of the former Sovjet Union or far eastern countries like China or Japan show regularly that the public in these countries is more punitive than in Western European countries, but may be not in comparison to the USA. This clearly shows that the attitudes to punishment in the public are strongly influenced by the sanctioning praxis in these countries (see Kury 2004; Kury and Karimov 2006). Kury and Kapanadze (2004) for example could show in an empirical study in Georgia that the punitive attitudes are more tough in this country. The same could be shown by Kury et al. (2006) for Azerbaijan. They asked students in Baku and found out that the Punitivity is very high. Baku had the highest percentage of respondents voting for an imprisonment of a burglar who has stolen a colour TV in comparison with other (western) countries (Kury et al. 2006, p. 460). 64 % voted for death penalty for serious offenders (p. 461). The difference between male and female was small.

If this praxis of sharp punishments changes regularly also the attitudes to punishment change over time. In West Germany the death penalty was abolished 1949. At that time nearly three quarters of the population voted for death penalty in cases of severe crimes. Meanwhile only round about one third are voting for this severe punishment. People "learned" that death penalty is not necessary to control crime and especially they were informed by the media about alternatives to classical punishment. The same happened in the former German Democratic Republic after the reunification of both parts of Germany after 1989. At the beginning the east Germans ware much more punitiv than the west Germans. They were not informed about alternatives to punishment. Meanwhile the difference is much smaller (see Lugwig and Kräupl 2005; Reuband 2008).

Concerning fear of crime results of different surveys show that feelings of insecurity in eastern countries if there is no political change and strong control is relatively low. Kury et al. (2006, p. 427) could show that the fear of crime is relatively low in Baku/Azerbaijan, a big city but strongly controlled, in comparison with western cities. Ludwig and Kräupl (2005, p. 49) could show that in eastern Germany, the former German Democratic Republic, the rate of fear of crime decreased from 1991/92 (69,8 % very unsafe and unsafe walking alone in the evening in the neighbourhood) to 1995/96 (50 %) and to 2001/02 (42 %) significantly. People have more experience with the new living conditions and are more familiar with the "new" life.

Mesko et al. (2008) have presented interesting and new results from a survey about "social-demographic and social-psychological perspectives of fear of crime in Slovenia, Croatia and Bosnia". The following survey will bring more results about fear of crime in Ljubljana and Belgrade. These are first important steps of empirical research in important topics of criminology and social psychology. Fear of crime influences the living conditions of people, has influence on punitive attitudes and so on crime politics. So it is very important to study the development of fear of crime and the correlates of these feelings.

2. Data collection

In this study we used an interviewing method conducted in the households of the interviewees. The population consisted of the adult (18 years old and more) inhabitants of urban areas of Ljubljana and Belgrade. The exercised sampling procedure was a multi-stage random probability method. The selection process was carried out through the following stages:

Stage 1: Primary sampling units. During the first stage we defined the city areas (i.e. the wider neighbourhoods) in which the research would be conducted. Since in this study the population consisted of urban inhabitants, suburban and rural settlements, as well as industrial and business areas, were therefore excluded at this stage of designing the sample. For example, Belgrade comprises 17 municipalities, out of which 6 are completely urban, 4 are partly urban and 7 have the status of suburban municipalities. We picked urban municipalities and the urban parts of the mixed municipalities, excluding the suburban ones. When we obtained the map of primary sampling units, we defined the proportionate participation of each such segment in the whole sample.

Stage 2: Sampling Points. The second step in designing the sample consisted of precisely defining the sampling points i.e. the streets or parts of the streets inside the primary sampling units, defined in the first step, in which the polls would be conducted. Each sampling point was defined as a path with a specific starting point and given the direction of the pollsters movement. In that way, we obtained a list of 40 precisely defined paths for each city (from point A towards point B) where the pollsters would move and in such designed areas find their interviewees. Inside each sampling point, 10 interviews were conducted.

Stage 3: Households. The next step involved specifying the procedure for finding of convenient households in which the poll or interview would be conducted. The selection of a household was carried out using the random-route technique. The disposition of households was defined according to the city size and the type of settlement. In Belgrade, the selected household was each 10th flat in the areas with blocks of flats (counting from the top floor in each entrance), that is, each 7th house in the areas with private individual housing. In Ljubljana, it was proposed that polls should be conducted in each 5th flat or each 3rd house, respectively. The pollsters were instructed to walk on the left hand side of the street.

Stage 4: Respondents. The final step in sample design consisted of defining the procedure for the choice of the interviewees inside the previously correctly chosen household. Our selection of one respondent per household was on „next birthday" selection-key. The procedure prescribed that the pollster should knock at the door of the correctly chosen household, say his/her name and ask for cooperation in the survey, ask how many members of that household are adults (18 years or older), and then pick one whose birthday falls next (chronologically). The change of such designated respondents was allowed only if after three attempts (one initial visit and two call-backs) the pollster could not conduct the interview. In case that it was impossible to find the correctly chosen interviewee or if he refused to participate in the poll, the pollsters continued the interviewing according to the plan of movement in that sampling point.

The polling was conducted during the period (1 to 15 April 2009?), by the students of the final years of the Faculty of Security Studies in Belgrade and Fakulteta za varnostne vede in Ljubljana, after the field work training and after receiving precise instructions about the procedure for polling and keeping the research documentation. The interviewing process was supervised by experienced researchers of the universities, the research assistants at the faculty, who also controlled the input and creation of the databases. 

Apart from the permanent supervision of the interviewing process by the staff of the universities, and in accordance with international research standards, a check of at least 15% of the effective interviews was performed in each city using some of the back/checks options (direct supervision during the interview, visit of the supervisor to the interviewed households, check by phone calls to the interviewed households).

3. Sample

A total of 800 female and male respondents from Ljubljana, Slovenia (400) and Belgrade, Serbia (400) were included in the sample. Table 1 shows the characteristics of the sample. The sample is relatively big and can be seen as representative for both cities.

Table 1: Characteristics of the Sample in Slovenia (Ljubljana) and Serbia (Belgrade)

N = 800

Slovenia

Serbia

Both

N

%

N

%

N

%

Age

(n = 795)

18-20

29

7,3

18

4,5

47

5,9

21-30

85

21,5

76

19,0

161

20,3

31-40

64

16,2

57

14,2

121

15,2

41-50

41

10,4

49

12,2

90

11,3

51-60

53

13,4

86

21,5

139

17,5

61-70

56

14,2

63

15,8

119

15,0

Over 70

67

17,0

51

12,8

118

14,8

Gender

(n = 787)

Female

238

61,5

235

41,2

473

60,1

Male

149

38,5

165

58,8

314

39,9

Marital status

(n = 795)

Single

103

26,1

107

26,8

210

26,4

Married

152

38,5

185

46,2

337

42,4

Cohabitating

69

17,5

19

4,8

88

11,1

Divorced

25

6,3

39

9,8

64

8,1

Widowed

46

11,6

50

12,5

96

12,1

Education

(n = 796)

Unfinished Primary School

2

0,5

3

0,8

5

0,6

Primary School

27

6,8

17

4,2

44

5,5

High School (3 years)

46

11,6

59

14,8

105

13,2

High School (4 years)

118

29,8

111

27,8

229

28,8

Gymnasium

46

11,6

27

6,8

73

9,2

College

42

10,6

69

17,2

111

13,9

BA

93

23,5

98

24,5

191

24,0

Post-graduate study

22

5,6

16

4,0

38

4,8

Employment status

(n = 800)

Employed (for an indefinite period)

131

32,8

120

30,0

251

31,4

Employed (for a definite period)

25

6,2

17

4,2

42

5,2

Schoolboy/girl, Student

63

15,8

54

13,5

117

14,6

Unemployed

14

3,5

39

9,8

53

6,6

Employed (waiting)

1

0,2

4

1,0

5

0,6

Housekeeping

2

0,5

2

0,5

4

0,5

Retired

153

38,2

147

36,8

300

37,5

Other

11

2,8

17

4,2

28

3,5

Frequency of visiting religious ceremonies

(n = 800)

Once or more per day

3

0,8

1

0,2

4

0,5

Once or more per week

32

8,0

15

3,8

47

5,9

Once per month

22

5,5

50

12,5

72

9,0

Several times per year

74

18,5

144

36,0

218

27,2

Once per year or rarely

61

15,2

77

19,2

138

17,2

Never

208

52,0

113

28,2

321

40,1

Religious believes

(n = 797)

Atheist

174

43,8

67

16,8

241

30,2

Liberal religiosity

48

12,1

59

14,8

107

13,4

Moderate religiosity

161

40,6

260

65,0

421

52,8

Conservative religiosity

9

2,3

10

2,5

19

2,4

Fundamental religiosity

5

1,3

4

1,0

9

1,1

Economic status

(n = 796)

I have enough money for a nice living.

142

35,9

52

13,0

194

24,4

I have enough money for living, but I can't afford a lot.

194

49,0

211

52,8

405

50,9

I have enough money only to survive.

45

11,4

111

27,8

156

19,6

I have enough money only for necessary things. Many times I don't know how to survive.

15

3,8

26

6,5

41

5,2

Monthly consumption (housekeeping)

(n = 784)

0 - 100 EUR

2

0,5

5

1,2

7

0,9

101 - 200 EUR

17

4,4

19

4,8

36

4,6

201 - 300 EUR

19

4,9

73

18,2

92

11,7

301 - 400 EUR

49

12,7

74

18,5

123

15,7

401 - 500 EUR

54

14,0

71

17,8

125

15,9

501 - 600 EUR

67

17,4

53

13,2

120

15,3

601 - 700 EUR

47

12,2

35

8,8

82

10,5

701 - 800 EUR

40

10,4

26

6,5

66

8,4

800 + EUR

91

23,6

42

10,5

133

17,0

How often do you...

(Likert scale: 1- never, 2 - very rarely, 3 - several times per month, 4 - at least once per week, 5 - almost every day, 6 - every day)

m

s.d.

m

s.d.

m

s.d.

... watch national TV?

4,18

1,654

4,30

1,656

4,24

1,655

... watch local TV?

3,91

1,919

4,28

1,686

4,09

1,815

... watch foreign TV?

3,97

1,661

3,80

1,886

3,89

1,778

... listen to the radio?

4,81

1,534

3,39

1,992

4,10

1,914

... read the newspaper?

4,63

1,553

4,63

1,707

4,63

1,631

... watch video/DVD?

2,61

1,511

2,70

1,653

2,66

1,583

... read news on the internet?

3,26

2,044

2,52

1,898

2,89

2,006

The age is relatively good distributed about the different groups. Concerning the sex of respondents more women participated in the survey a result very often found. Women are more willing to participate in such surveys (ovo izbaciti, uzorak je slučajan, zato je "ispala" ovakva polna struktura - dešava se, a ne zbog toga što su žene bile spremnije na učešće) . Concerning the marital status and the education we have a good distribution. The number of unemployed is in both cities relatively low. 37,5 % are retired, a relatively high number if we see the age distribution. Concerning the religious activities 40 % are not active, a high percentage, but in the former Sovjet states religious was not or only little supported so it is not surprising that so many are not active in religious topics. 30 % are atheists, in Slovenia 44 % and in Serbia 17 %. One fourth (24 %) say they have enough money for a nice live, but in Slovenia 36 % and in Serbia only 13 %. So the Serbes are much poorer than the Slovenes. 11 % of the interviewed Slovenes but not less than 28 % of the Serbes point out they only have money to survive. That shows clearly that living conditions in Servias (Belgrade) are much worse than in Slovenia (Ljubljana). (Ne, podaci ne govore o faktičkom materijalnom stanju - to se i ne utvrđuje anketnim ispitivanjem, već samo o percepciji ispitanika. Dakle, ispitanici iz Srbije percipiraju svoj materijalni status kao daleko nepovoljniji nego ispitanici iz Slovenije. Takva nepovoljna percepcija, naravno, ima svoj izvor u objektivno nepovoljnijim ekonomskim uslovima koji realno postoje u ove dve države, ali mi nemamo pravo da zaključujemo "So the Serbes are much poorer than the Slovenes"). According to this result the monthly consumption for housekeeping are in the medium lowere than in Slovenia. While in Serbia 43 % of the interviewed persons spend per month at maximum 400 Euros, in Slovenia this are only 22 %, that is round about half. On the other side in Slovenia 64 % spend every month 500 Euros or more in Serbia this are only 39 %. While in Serbia more interviewed respondents look national and local TV, the Slovenes hear more radio and use the internet, what has obviously to do with the financial conditions in both countries. In Slovenia both sexes and all age groups use more the radio than in Serbia, the same time the Slovenes use more the internet in all age and both sex groups.

Regarding gender, age and frequency of media we joined those variables into five new variables:

regarding gender, age and frequency of watching TV (young women who watch little TV, young women who watch TV a lot, older women who watch little TV, older women who watch TV a lot, young men who watch little TV, young men who watch TV a lot, older men who watch little TV, older men who watch TV a lot);

regarding gender, age and frequency of listening to the radio (young women who don't listen to the radio a lot, young women who listen to the radio a lot, older women who don't listen to the radio a lot, older women who listen to the radio a lot, young men who don't listen to the radio a lot, young men who listen to the radio a lot, older men who don't listen to the radio a lot, older men who listen to the radio a lot);

regarding gender, age and frequency of reading newspaper (young women who don't read newspaper a lot, young women who read newspaper a lot, older women who don't read newspaper a lot, older women who read newspaper a lot, young men who don't read newspaper a lot, young men who read newspaper a lot, older men who don't read newspaper a lot, older men who read newspaper a lot);

regarding gender, age and frequency of watching video/DVD (young women who don't watch video/DVD a lot, young women who watch video/DVD a lot, older women who don't watch video/DVD a lot, older women who watch video/DVD a lot, young men who don't watch video/DVD a lot, young men who watch video/DVD a lot, older men who don't watch video/DVD a lot, older men who watch video/DVD a lot);

regarding gender, age and frequency of reading news on the internet (young women who don't read news on the internet a lot, young women who read news on the internet a lot, older women who don't read news on the internet a lot, older women who read news on the internet a lot, young men who don't read news on the internet a lot, young men who read news on the internet a lot, older men who don't read news on the internet a lot, older men who read news on the internet a lot).

Frequencies of individual variables are presented in table 2.

Table 2: Frequencies regarding age, gender and frequency of media

 

Ljubljana

Belgrade

Both

Watching TV

 

f

%

f

%

f

%

young women - little TV

39

10,2

26

6,5

65

8,3

young women - lots of TV

70

18,3

80

20,0

150

19,2

older women - little TV

21

5,5

30

7,5

51

6,5

older women - lots of TV

105

27,5

99

24,8

204

26,1

young men - little TV

26

6,8

16

4,0

42

5,4

young men - lots of TV

55

14,4

57

14,3

112

14,3

older men - little TV

0

0,0

0

0,0

0

0,0

older men - lots of TV

66

17,3

92

23,0

158

20,2

Listening to the radio

young women - little radio

23

6,0

45

11,3

68

8,7

young women - lots of radio

85

22,3

61

15,3

146

18,7

older women - little radio

18

4,7

87

21,8

105

13,4

older women - lots of radio

108

28,3

42

10,5

150

19,2

young men - little radio

20

5,2

35

8,8

55

7,0

young men - lots of radio

61

16,0

38

9,5

99

12,7

older men - little radio

7

1,8

49

12,3

56

7,2

older men - lots of radio

59

15,5

43

10,8

102

13,1

Reading newspaper

young women - little newspaper

22

5,8

23

5,8

45

5,8

young women - lots of newspaper

86

22,6

83

20,8

169

21,6

older women - little newspaper

23

6,0

28

7,0

51

6,5

older women - lots of newspaper

103

27,0

101

25,3

204

26,1

young men - little newspaper

27

7,1

17

4,3

44

5,6

young men - lots of newspaper

54

14,2

56

14,0

110

14,1

older men - little newspaper

10

2,6

22

5,5

32

4,1

older men - lots of newspaper

56

14,7

70

17,5

126

16,1

Watching video/DVD

young women - little video/DVD

74

19,5

52

13,0

126

16,2

young women - lots of video/DVD

34

8,9

54

13,5

88

11,3

older women - little video/DVD

116

30,5

110

27,5

226

29,0

older women - lots of video/DVD

10

2,6

19

4,8

29

3,7

young men - little video/DVD

37

9,7

31

7,8

68

8,7

young men - lots of video/DVD

44

11,6

42

10,5

86

11,0

older men - little video/DVD

55

14,5

81

20,3

136

17,4

older men - lots of video/DVD

10

2,6

11

2,8

21

2,7

Reading news on the internet

young women - little internet

32

8,4

61

15,3

93

11,9

young women - lots of internet

77

20,2

45

11,3

122

15,6

older women - little internet

102

26,7

111

27,8

213

27,2

older women - lots of internet

24

6,3

18

4,5

42

5,4

young men - little internet

22

5,8

31

7,8

53

6,8

young men - lots of internet

59

15,4

42

10,5

101

12,9

older men - little internet

43

11,3

74

18,5

117

15,0

older men - lots of internet

23

6,0

18

4,5

41

5,2

4. Results

4. 1. Correlations

From figure 1 we can see correlations (for both cities together) between new variables and variable "Fear of Crime".

The most correlated variables with fear of crime are: V9 - Influence of victimisation (r = 0,497), V6 - Possible weight of victimisation (r = 0,493), V12 - Avoidance strategies (r = 434), V4 - unease because of crime (r = 0,371), V5 - probability of victimisation in next 3 months (r = 0,229) and V2 - signs of incivility (r = 0,211). All correlations are positive and significant at the 0,01 level. Self-defence ability is logically negatively correlated with fear of crime (r = -0,333). More people think of themselves that they are capable of chasing off a potential assailant, less they are afraid. Correlation is significant at the 0,01 level. These correlations are all significant and more or less the same in all three samples, that is, factors which influence feelings of insecurity are more or less the same in both cities. There are only two correlations only in one of the two cities: Fear of crime is positively correlatet with V3 - trust in criminal justice institutions (r = 0,148) in Ljubljana and also positively correlated with V14 - media frequency (r = 0,089) in Belgrade. That means that in Ljubljane respondents who trust in criminal justice institutions are a little bit more fearful and in Belgrade people who use more media are more fearful. The correlations are in both cases relatively small (see also Table 3).

Table 3: Correlations between the 13 variables and "Fear of Crime" - Ljubljana, Belgrade and both cities

Variables Corelations

Lubljana Belgrade Both

V1- social networks in neighbourhood .022 .048 .011

V2- signs of incivility .189** .179** .211**

V3- trust in criminal justice institutions .148** kako? .002 .045

V4- unease because of crime .410** .311** .371**

V5- probability of victimis. In next 3 months .201** .242** .229**

V6- possible weight of victimisation .482** .504** .493**

V7- self-defense ability -.335** -.325** -.333**

V8- supportive networks -.062 -.048 -.051

V9- influence of victimisation .515** .475** .497**

V10-victim in the past 12 months -.018 -.018 -.040

V11-vicarious victimisation .042 .045 .043

V12-avoidance strategies .439** .417** .434**

V13-media frequency .064 .080 .089*

PRVO : Šta je strah od kriminala u ovom istraživanju?

DRUGO : Treba objasniti svaku varijablu, i objasniti INSTRUMENT. Ovako se iz skraćenih naziva varijabli aspolutno ne mogu pokapirati sadržaji na koje se odnose (zamisli nekoga ko nema pojma o našem istraživanju, šta može da pomisli o sadržaju varijable V12-avoidance strategies, npr)

V3 - zar nije nelogično da se više plaše ako više veruju u pravosudje? Možda da ovo ne prikažeš.

Malo su grubi zaključci za ovako niske korelacije... the results should be studied and interpreted with a certain degree of caution.

MOŽDA : Ljudi u Ljubljani koji se više plaše kriminala - zbog toga više veruje u pravosuđe.

MOŽDA : Ljudi koji se više plaše u Beogradu više prate medije.

Nemamo elementarni podatak : koliki procenat ljudi u LJ i BG je uplašeno. Valjda je glavno pitanje trebalo da bude :

How prevalent is the fear of crime in the LJ and BG population, and

how much do people worry about different types of offences?

Ako bi ovo išlo u neki ozbiljniji časopis, takođe nemamo dve značajne stavke:

level of non-response (ne verujem da je iko od kolega, a ni ja, dostavio podatak o ovome)

item non-response (Don‚t know/ Dont want to answer) O ove dve stavke bi trebalo voditi računa sledeći put (to se zahteva kao obavezno)

Figure 1: Correlations - Pearson's (Ljubljana & Belgrade)

* Correlation is significant at the 0.05 level (2-tailed).

** Correlation is significant at the 0.01 level (2-tailed).

In figure 2 and 3 are presented correlations for both cities separately. The findings are, as mentioned, very similar. Correlations for Ljubljana, Slovenia (figure 2) show that the most correlated variables with fear of crime are: V9 - Influence of victimisation (r = 0,515), V6 - Possible weight of victimisation (r = 0,482) and V12 - Avoidance strategies (r = 434). All correlations are positive and significant at the 0,01 level. Self-defence ability is negatively correlated with fear of crime (r = -0,333). Correlation is significant at the 0,01 level.

Figure 2: Correlations - Pearson's (Ljubljana)

* Correlation is significant at the 0.05 level (2-tailed).

** Correlation is significant at the 0.01 level (2-tailed).

Correlations for Belgrade, Serbia (figure 3) show that the most correlated variables with fear of crime are: V6 - Possible weight of victimisation (r = 0,504), V9 - Influence of victimisation (r = 0,475) and V12 - Avoidance strategies (r = 417). All correlations are positive and significant at the 0,01 level. Self-defence ability is again negatively correlated with fear of crime (r = -0,325). Correlation is significant at the 0,01 level.

Figure 3: Correlations - Pearson's (Belgrade)

* Correlation is significant at the 0.05 level (2-tailed).

** Correlation is significant at the 0.01 level (2-tailed).

4. 2. Regression analysis

In addition we used those 13 variables (social networks in neighbourhood, signs of incivility, trust in criminal justice institutions, unease because of crime, probability of victimisation in the next three months, possible weight of victimisation, self-defence ability, supportive networks, influence of victimisation, victim in the past twelve months, vicarious victimisation, avoidance strategies and media frequency) as predictor variables and fear of crime as the dependet variable. We performed regression analyses for both cities together and then separately for Ljubljana and Belgrade. In table 4 we can see R2 for all three regressions. The largest R2 for Ljubljana shows that all those variables can account for 40,7 % of the variation in fear of crime, in Belgrade for 37,9 % and in both samples for 39,1 %.

Table 4: Model summary - R2

City

R2

Both

0,391

Ljubljana

0,407

Belgrade

0,379

Table 5 shows the results of the regression analyses in an overview. The results show that the correlation analyses are more or less confirmed. Variables with most influence on fear of crime are V12 - avoidance strategies, V6 - possible weight of victimisation, V9 - influence of victimisation and self-defense abilities (negative). Signs of incivility looses of importance and also unease because of crime.

Table 5: Regression Analyses of the 13 independent variables and "Fear of Crime" as dependent variable - Ljubljana, Belgrade and both cities

Variables Regression - beta coefficients

Lubljana Belgrade Both

V1- social networks in neighbourhood -.091 .039 -.020

V2- signs of incivility .085 .045 .075*

V3- trust in criminal justice institutions .056 .040 .033

V4- unease because of crime .104* .087 .099*

V5- probability of victimis. In next 3 months .025 .074 .037

V6- possible weight of victimisation .150* .227* .201*

V7- self-defense ability -.160* -.164* -.154*

V8- supportive networks -.053 -.006 -.021

V9- influence of victimisation .196* .148* .155*

V10-victim in the past 12 months -.003 .007 -.002

V11-vicarious victimisation .016 .013 .018

V12-avoidance strategies .218* .208* .214*

V14-media frequency .070 -.012 .028

In figure 4, 5 and 6 are presented standardised beta coefficients for all three regressions.

Figure 4: Regression - standardised beta coefficients (Ljubljana & Belgrade)

* Significant.

Regression for both cities together (figure 4) shows six significant predictors (independent variables):

V12 - avoidance strategies (0,214),

V6 - possible weight of victimisation (0,201),

V9 - influence of victimisation (0,155),

V7 - self-defence ability (-0,154),

V4 - unease because of crime (0,099),

V2 - signs of incivility (0,075).

All coefficients are positive except for self-defence ability (which is in accordance with correlations).

Figure 5: Regression - standardised beta coefficients (Ljubljana)

* Significant.

Regression for Ljubljana (figure 5) shows six significant predictors (independent variables):

V12 - avoidance strategies (0,218),

V9 - influence of victimisation (0,196),

V7 - self-defence ability (-0,160),

V6 - possible weight of victimisation (0,150),

V4 - unease because of crime (0,104),

V1 - social networks in neighbourhood (-0,091).

All coefficients are positive except for self-defence ability and also social networks in neighbourhood.

Figure 6: Regression - standardised beta coefficients (Belgrade)

* Significant.

Regression for Belgrade (figure 6) shows only four significant predictors (independent variables):

V12 - avoidance strategies (0,208),

V6 - possible weight of victimisation (0,227),

V9 - influence of victimisation (0,148),

V7 - self-defence ability (-0,164).

All coefficients are positive except for self-defence ability.

5. Discussion

The results show very similar outcomes of the correlation as well the regression analyses for both cities. There are no big differences. Fear of crime correlates significantly with influence of victimisation, with the possible weight of these experienced victimixations, with avoidance strategies, with feelings of unease because of crime, with the estimated probabilitiy of a victimisation within the next three months and with signs of incivilities in the cities. There is a negative significant correlation with self-defense ability, that is people who feel more able to defense themselves have less fear of crime. In Belgrade there is obviously a little bit more influence on fear of crime by the media.

The regression analyses show fewer significant relationships. According to the results there is an influence on fear of crime or a link by avoidance strategies, the possible weight of a victimisation and the influence of a victimisation. People who feel a stronger possibility to self defence have lower fear of crime rates. So the possible victimisation plays a crucial role in fear of crime according these results. Signs of incivility are significant only for both samples together.

It is very important to analyse the data more and to find out differentiated results. The results show how important empirical surveys in these countries are (see also Mesko et al. 2008). It is very important to include these countries in further criminological analyses to test theories, for example about fear of crime and other concepts.

Potreba za daljim istraživanjem uz primenu različitih istraživačkih pristupa, uključivanje kvalitativnog pristupa i drugih tehnika prikupljanja podataka čime bi se obuhvatili svi aspekti kompleksnog sadržaja pojma strah od kriminala (affective, cognitive and behavioral). Ograničenje ove studije je u tome što je korišćeno samo samoizveštavanje (merena je samo percepcija ispitanika), nema arhivskih indikatora (objektivnih pokazatelja, prijavljeni incidenti, procenjeni incidenti) i sve je zasnovano samo na anketnom ispitivanju percepcije. O predikciji je teško zaključivati ako se ne sprovede longitudinalna studija, čime bi se tek mogla pratiti prediktivnost faktora (udeo tih faktora u stvaranju straha od kriminala).

NISAM TI JA MNOGO PAMETNA KAD SU BROJEVI U PITANJU. A I INAÄŒE.