Fear Of Crime Female Vs Male Criminology Essay

Introduction

The level of fear of crime across different groups within the community is a major contributor to the Governments’ focus on the type of support communities require to maintain the feeling of safety. By understanding the dynamics of fear, we are able to predict areas of likely crime through understanding the psyche of the ‘predator’ and ‘alpha’ type crimes along with other illegal activities. Due to the generally accepted level of safety within the majority of Australia’s westernised communities, a common low level of continuous fear to immediate self is evident. Therefore, to qualify this assessment, the Fear of Crime between genders will be considered across multiple situations rather than localities. The analyses derived in this paper are borne from research surveys delivered across a general and random sample of the local community. This will provide an insight into the relationship between gender and vulnerability to crime; whether it is perceived or actual. The study is limited by number of people in one country and can be treated as base for developing further research.

Previous Research

We all must know and understand fear of crime which is explained as people’s emotional response to crime. It can be safely admitted from the surveys conducted that women has more fear of crime than other population groups. Fear of crime is associated with perceptions of local problems, derived mainly from a high incidence of physical and social incivility. Women have been observed to be amongst the most vulnerable groups. There are number of communities having large fear of crime amongst all the population. The problem can be classified as crime as it serious for any segment of population to live with fear of crime. The fear problem has emerged as serious concern since last three decades, and statistical figures of Australian women indicate that women’s fear of crime is greater among those who have lower incomes, those in the older age groups, and those living with a partner.

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Women fear is characterised by dual nature namely: concrete and formless fear. Concrete fear is the fear associated with certain crimes. The implicit assumption here is that some criminal activities cause more fear than others. For example, rape fear is much more than fear than theft. Formless fear, however, is a more generic or less specific fear of crime. Younger generations have reported higher levels of both types of fear. Studies conclude that younger women reported highest results for concrete fear, or fear of specific crimes. Women consider fear of rape equivalent to fear of murder. Fear is stronger in single as compared to married women. Additionally, experiencing specific offences is better predictor of fear from specific happenings than others. The degree of fear may differ from low to high level. Studies are conducted by providing specific situations to the respondents about the degree of anxiety and fear from the situations. The situations are common in our general routine e.g. a) walking in their neighborhood at night, b) taking public transport, c) using a parking garage, and d) being home. The response categories are segregated as level of fear as: not at all worried (0), and worried (1). Logistic regression was utilized to determine the effect of demographic, experiential, and behavioral variables on fear in four situations. Majority of women narrated having at least once incidence of violence in last 12 months, approximately two thirds (66.4%) of respondents reported receiving an obscene phone call, while three out of five reported receiving unwanted attention from a stranger. Almost one third (32.4%) reported being followed by a stranger in a way that frightened them. A large proportion of women reported being somewhat or very worried walking in their neighborhood at night (61.0%). Factor of personal income is not significant factor in predicting fear while using public transportation. Women with higher levels of education were 5.2 percent more likely to be worried while in the transportation situation, 5.1 percent more likely to report being worried while in a parking garage alone at night, but 3.2 percent less likely to report fear while home alone in the evening (Scott, 2003).

Research studies also indicate that women who have already experienced violence, especially victims of domestic violence, become more fearful for crime as against other women. It was surprising to note from the revelations that 58 per cent of female homicide victims have assailants who are intimates/former intimates. These facts provide a strong argument for early intervention to prevent domestic violence and provide assistance to dysfunctional and violent families. In another survey from the sample of 6333 respondents, approximately 70% of the

Women felt unsafe when walking alone in their area after dark, which is higher than the percentages reported by the 1996 British Crime Survey (47%) and the 1991 Queensland Crime Victims Survey (45.3%). However, these figures are much lower than the result obtained in a study carried out in Edinburgh in 1992 (Carcarh, Mukherjee, 1999).

Fear of Crime in the Home

Under the crimes at home, there is important contribution of domestic violence. Under this aspect though domestic violence can impact both genders but the history confirms that chances of crime against women are high. This is mainly due to reason that women may be exposed to domestic violence at home on regular basis. The domestic violence is a crime and involves sexual abuse (whether you are married to the other person or not); physical abuse or assault (for example, slapping, biting, kicking, and threats of physical violence); damage to property or anything you value; economic abuse, that is, when the other person keeps money to which you are legally entitled, emotional abuse (that is, degrading or humiliating behaviour, including repeated insults, belittling, cursing and threats), and any other controlling or abusive behaviour which poses a threat to your safety, health or well-being. It was been amazing to observe that Women living with a partner are likely to experience greater fear of violence. The research shows that even the conclusion drawn by Madriz’s (1997) indicated that women victims of domestic violence have to face violence at home and violence on the streets that other women face, which increase their level of fear of crime in the community. Women facing physical violence by males will report fear from crime double than the women who have not experience physical violence at all. These results support Madriz’s (1997) finding that women victims of domestic violence have to face violence at home and violence on the streets that other women face, which would increase their level of fear of crime in the community (Carcach, Mukherjee, 1999).

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The Gender Difference in Fear of Crime

Studies have indicated that though both genders are prone to crime but majority of the studies confirm the gender differential is the most consistent finding in the literature on fear of crime.

There is reporting of fear of crime by women at levels that are three times that of men (Chan, 2008). Since last three decades, there has been lot of concern about women safety in the police communication in Australia, England, Canada and Wales. Police and local authorities issued safety advice to women. One of the research studies conducted (Grade 1989) focus on crime prevention indicating women as prime consumers of targeted advice about personal safety. However, review of data shows that young men are most at risk to personal violence in public. Despite this, women are considered the most important constituency for guidance about danger.

Literature Review

The effects of demographic variables on fear are mixed. There may be number of incidents of events which can create fear in the minds. One of such thinking is when people walk alone in one’s neighborhood at night. Where many demographic variables increase fear while walking in one’s neighborhood or being home alone at night (i.e. lower education levels, lower reported personal income, and living in an urban area). Majority of people understand fear of crime centered on findings using respondent’s feelings of fear or worry while walking in their neighborhood at night. There is another fear i.e fear of strangers which has been suitably referred to as “stranger danger.” During childhood, all of us are told to be wary of strangers. Women fear the danger posed by strange men even though statistics show that women are more likely to be victimized by individuals they know. It would appear that they are most afraid of the surprise sexual attack by the unknown assailant, despite the fact that statistics and public service media campaigns are making women aware of dangers of dating and marital situations. Number of survey reports discuss about the fear of crime and indicate relatively small but statistically significant differences between fear rates expressed by men and women. Majority of women are believed to be fearful of crime; and all men fearless (Gilchrist, 1988). Studies are limited to explain why women might harbor anxiety about their personal safety. Skogan and Maxfield (1981) suggest that women’s fear of crime is because of their physical and social openness. Women’s fear of sexual assault i.e. fear of rape also causes lack of safety amongst the women.

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Research Questions

This research is to assist with the targeting of safety programs and the determination of focus for future community groups and activities. This paper will address the problem of which gender within the local community fears crime, whether actual or perceived, and the times that they feel most unsafe. By understanding this, programs can be directed towards these groups and the understanding of safety and their options when confronted with a situation can be addressed.

Based on collected statically data this paper will directly address the aspects of the genders influence of the fear of crime:

Do the different genders fear crime differently?

What affect does age have on females’ fear of crime?

Do females feel safer at home during the day or evening?

Due to the results of the above previous research and general perception within the Westernised Urban Australian culture, it is expected that females will report a higher level of fear of crime. Because of this the second and third questions within this report will focus on the different generations and locations in which female’s fear crime; including showing the amounts in which it various.

If the results unexpectedly show that males are more fearful of crime, then the questions regarding the female generations’ and locations’ effects of their perceived fear are still warranted and are able to be used to target female related programs.

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Method

This analysis utilises data collected by previous research groups over the past few years. This offers the advantage of including the ‘indexing’ of generations over time allowing a slightly more average and round return compared to a frozen snapshot in time. The survey was conducted across all age groups from varying social-economic backgrounds and cultures. Also the location spread of the survey focuses on South East Queensland however reaches into other states and some samples are returned from overseas (Micronesia).

Sampling was conducted via a take home survey with instructions included. There was a directed expectation of integrity of answers, which created minimal cross-contamination. Immediately upon completion, surveys were to be returned via either mail or in person allowing coalition and further reducing the possibility of corrupted samples.

Fear of crime will be the dependent variable and will indicate the level of felt across the genders in varying situations. The gender of respondent is the independent variable which is being assessed as to whether it relates to the fear of crime and in addition to gender, age [1] and time of day will also be independent variables. All these variables will be determined by the survey responses and the dependent variable will be tested for statistical independence.

Analytic Techniques

Summary of analysis completed

The data is presented in tabular format along with graphs and charts. All descriptive statistics is calculated for each variable on interval or ratio scale. Further, data is analysed using statistical techniques such as chi-square test, one- way ANOVA followed by POST HOC tests, Z-test for comparing mean etc. Level of significance is fixed at 5%. All p-value less than 0.05 will be treated as significant.

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Dealing with missing data

Missing data is almost part of every research. In this study, missing data is limited to a small number of subjects. Hence we opted a list-wise deletion of subjects. Only the subjects with missing data will be eliminated from the study. That is if a subject is missing data on any of the variables used in the analysis, it is completed eliminated.

Dealing with outliers, errors etc.

Dealing with outliers and errors is very difficult. In this study, we found very less outliers and errors. All subjects with outliers or errors are excluded from the study. Since errors are at random, it makes no much effect on study, if we remove them from the study.

Any other problems in completing the analysis (e.g. violations of requirements)

Before conducting all parametric tests, all the necessary required conditions are checked and further analysis is done. For parametric tests, normality assumption is checked. All data is found to be approximated normally distributed.

Age-wise distribution

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Gender

Frequency

Percent

Male

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162

45.6

Female

193

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54.4

Total

355

100.0

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Findings

Question one or Hypothesis One: Does fear of crime differ by gender?

Table

gender * Afraid group Cross tabulation

Afraid Score

Total

Afraid Score less than 4

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Afraid score between 4-6

Afraid Score above 6

gender

Male

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Count

83

61

16

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160

% of Total

23.5%

17.3%

4.5%

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45.3%

Female

Count

53

76

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64

193

% of Total

15.0%

What’s Your Editing Process?

Upload your draft, tell us your goals, and our editors will refine it—boosting arguments, fixing errors, and keeping your voice. You’ll get a polished paper that’s ready to shine.

21.5%

18.1%

54.7%

Total

Count

Can You Suggest Paper Topics?

Sure! Need ideas? We’ll pitch topics based on your subject and interests—catchy and doable. Pick one, and we’ll run with it, or tweak it together.

136

137

80

353

% of Total

38.5%

38.8%

Do You Offer Rush Revisions?

Yes! If you need quick edits, our team can turn it around fast—hours, not days—tightening up your paper for last-minute perfection.

22.7%

100.0%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

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Absolutely! We’ll draft an outline based on your topic so you can approve the plan before we write—keeps everything aligned from the start.

34.275a

2

.000

Likelihood Ratio

36.068

2

.000

Linear-by-Linear Association

Can You Include Data Analysis?

You bet! Need stats or charts? Our writers can crunch numbers and craft visuals, making your paper both sharp and professional.

33.650

1

.000

N of Valid Cases

353

Conclusion: Parsons Chi-square is found to be 34.275 with p-value < 0.05; hence there is significant association between afraid score and gender. Afraid score is significantly high in females as compared to males.

Respondent’s Perceived Level of Unsafety While at Home During the Day and Gender

gender * safe day Cross tabulation

safe day

Total

Very Unsafe

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Unsafe

Neither safe nor unsafe

Safe

Very safe

Never home alone during the day

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gender

Male

Count

1

3

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4

35

111

1

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155

% of Total

.3%

.9%

1.2%

10%

32.3%

.3%

451%

Female

Count

3

7

24

72

83

0

189

% of Total

.9%

2.0%

7.0%

20%

24.1%

.0%

55%

Total

Count

4

10

28

107

194

1

344

% of Total

1.2%

2.9%

8.1%

31%

56.4%

.3%

100%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

31.670a

5

.000

Likelihood Ratio

33.680

5

.000

Linear-by-Linear Association

24.327

1

.000

N of Valid Cases

344

Conclusion:

Parsons Chi-square is found to be 31.670 with p-value < 0.05; hence there is significant association between safety during day and gender. Males feel more safety at home during day as compared to females.

Question Two or Hypothesis Two: Are older women more fearful than younger women? Graph

age * Fear Group Cross tabulation

Fear Group

Total

Fear Score less than 3

Fear Score between 4 -6

Fear Score above 6

age

Age Group 18 -24

Count

12

14

14

40

% of Total

6.3%

7.3%

7.3%

20.8%

Age Group 25-34

Count

15

30

13

58

% of Total

7.8%

15.6%

6.8%

30.2%

Age Group 34-44

Count

13

14

11

38

% of Total

7.3%

5.7%

19.8%

Age Group 45-54

Count

8

9

10

27

% of Total

4.7%

5.2%

14.1%

Age Group 55-64

Count

6

6

4

16

% of Total

3.1%

6.8%

2.1%

8.3%

Age group 65 and over

Count

2

5

6

13

% of Total

1.0%

4.2%

3.1%

6.8%

Total

Count

56

78

6

192

% of Total

29.2%

40.6%

30.2%

100.0%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

7.544a

10

.673

Likelihood Ratio

7.512

10

.676

Linear-by-Linear Association

.284

1

.594

N of Valid Cases

192

Conclusion: Parsons Chi-square is found to be 7.544 with p-value > 0.05; hence there is no significant association between fear and age group. Hence we can conclude that, age is not associated with fear.

Average Score of Female Respondent’s Fear of Crime and Age e.g. Table or graph, ANOVA Test

Descriptive (Fear)

N

Mean

Std. Deviation

95% Confidence Interval for Mean

Lower Bound

Upper Bound

Age Group 18 -24

40

5.1162

2.44853

4.3332

5.8993

Age Group 25-34

58

4.3498

1.91327

3.8468

4.8529

Age Group 34-44

38

4.3447

2.24761

3.6060

5.0835

Age Group 45-54

27

4.8770

2.42666

3.9171

5.8370

Age Group 55-64

16

4.6325

2.57747

3.2591

6.0059

Age group 65 and over

13

6.0692

2.60333

4.4961

7.6424

Total

192

4.7226

2.29671

4.3957

5.0495

ANOVA

fear2

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

44.032

5

8.806

1.700

.137

Within Groups

963.469

186

5.180

Total

1007.500

191

Conclusion: there is no significant difference in fear score among various age groups. F= 1.70, p > 0.05, hence we can conclude that the fear score is almost same among persons of all age groups.

Female Respondent’s Received Level of Unsafety While at Home During the Day and Age

e.g. Table or graph, ANOVA Test

Descriptive (safe day)

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Lower Bound

Upper Bound

Age Group 18 -24

39

4.3846

.84652

.13555

4.1102

4.6590

Age Group 25-34

57

4.2456

.66227

.08772

4.0699

4.4213

Age Group 34-44

37

4.0000

1.20185

.19758

3.5993

4.4007

Age Group 45-54

26

4.3846

.75243

.14756

4.0807

4.6885

Age Group 55-64

16

4.0625

1.06262

.26566

3.4963

4.6287

Age group 65 and over

13

3.6923

1.03155

.28610

3.0689

4.3157

Total

188

4.1915

.91074

.06642

4.0605

4.3225

ANOVA

safe day

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

7.454

5

1.491

1.838

.108

Within Groups

147.653

182

.811

Total

155.106

187

Conclusion: there is no significant difference in safe day score among various age groups. F= 7.454, p > 0.05, there is no significant difference between feeling safety during day score and age.

Female Respondent’s Perceived Level of Unsafety While At Home Alone After Dark and Age

e.g. Table or graph, ANOVA Test

N

Mean

Std. Deviation

95% Confidence Interval for Mean

Lower Bound

Upper Bound

Age Group 18 -24

34

9.1765

2.25637

1.3036

17.0493

Age Group 25-34

46

7.9130

1.94569

2.1351

13.6910

Age Group 34-44

33

3.5758

1.25076

3.1323

4.0193

Age Group 45-54

25

1.1760

2.59700

1.0401

22.4799

Age Group 55-64

16

1.5125

3.23787

-2.1284

32.3784

Age group 65 and over

11

2.6364

.92442

2.0153

3.2574

Total

165

8.2364

2.035861

5.1069

11.3658

ANOVA

safenite

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

2166.272

5

433.254

1.047

.392

Within Groups

65807.509

159

413.884

Total

67973.782

164

Conclusion: there is no significant difference in safe night score among various age groups. F= 1.047, p > 0.05, there is no significant difference between feeling safety during night score and age.

Question Three or Hypothesis Three:

Average Score of Female Respondent’s Fear of Crime and Live Alone E.g. Table or graph, z-test of mean differences

Descriptive (Fear)

N

Mean

Std. Deviation

95% Confidence Interval for Mean

Lower Bound

Upper Bound

Live Alone

121

4.6625

2.32150

4.2446

5.0803

Don’t live alone

17

6.1000

2.13131

5.0042

7.1958

Total

138

4.8396

2.34008

4.4457

5.2335

ANOVA

fear2

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

30.802

1

30.802

5.823

.017

Within Groups

719.406

136

5.290

Total

750.208

137

Conclusion: there is significant difference in fear score women who live alone and don’t live alone at home. F= 5.823, p < 0.05, there is significant difference between feeling safety during night score and age. Fear score is significantly high in women who don't line alone.

Female Respondent’s Received Level of Unsafety While at Home Alone During the Day and Lives Alone E.g. Table or graph, z-test of mean differences Female Respondent’s Received Level of Unsafety While a Home Alone After Dark and Lives Alone

E.g. Table or graph, z-test of mean differences

N

Mean

Std. Deviation

95% Confidence Interval for Mean

Lower Bound

Upper Bound

safe day

Live Alone

119

4.1176

.91296

3.9519

4.2834

Don’t live alone

16

3.6875

1.07819

3.1130

4.2620

Total

135

4.0667

.93999

3.9067

4.2267

safenite

Live Alone

102

5.5000

13.19747

2.9078

8.0922

Don’t live alone

14

2.1429

.77033

1.6981

2.5876

Total

116

5.0948

12.41946

2.8107

7.3789

ANOVA

Sum of Squares

df

Mean Square

F

Sig.

safe day

Between Groups

2.610

1

2.610

2.997

.086

Within Groups

115.790

133

.871

Total

118.400

134

safenite

Between Groups

138.743

1

138.743

.899

.345

Within Groups

17599.214

114

154.379

Total

17737.957

115

Conclusion:

There is no significant difference in fear score of women who live alone and don’t live alone at home during day. F= 2.997, p > 0.05, there is significant difference between feeling safety during day score and living alone status.

There is no significant difference in fear score of women who live alone and don’t live alone at home during day. F= 2.997, p > 0.05, there is significant difference between feeling safety during day score and living alone status.

Discussion/Conclusion

Summary of Results: how did you answer each question/hypothesis?

Each hypothesis is tested for rejection with appropriate test of significance. The level of significance is set at 5%. All p-values greater than 0.05 will be treated as insignificant and the null hypothesis will be accepted.

Implications of findings for theoretical explanations

In this, out of 355 respondents, 162 (45.4%) are males and 193 (55.6%) are females. This study clearly shows that there is significant association between gender and fear of crime (p < 0.05). Females were found to have more fear of crime as compared to males. Respondent's Perceived Level of Unsafety While at Home During the Day and Gender are significantly associated. (p < 0.05). This indicates that women feel more unsafe at home as compared to men during day. No association found between fear and womens age (p-value > 0.05). The level of fear is almost equal among all age groups in women. No significant difference was found in the average score of fear between different age groups of women (p-value > 0.05). There is no significant difference in safe night score among various age groups in women (p-value > 0.05). There is significant difference in fear score among women who live alone and don’t live alone at home (p < 0.05). There is significant difference between feeling safety during night score and age. Fear score is significantly high in women who don't live alone.

Limitations of the Research

There are limitations to this study. Firstly the sample size only pertains to only one country and considering all are local population, the data does not give diversity of opinion. Australia is a country where population has settled form wide range of countries and their cultural differences have not been considered.

The survey is conducted only in English and non English speaking women must be unable to report their experiences of victimization. As a result, these indicators lack sufficient data regarding the prevalence of violence against immigrant women as well as some groups of Aboriginal women.

Majority of countries are carving out funds for preventing violence against women. The real effect is yet to be seen. Future research is required to look into use of these funds and any improvement the funds could generate.

Moreover, due to the different sources of data used in this document, comparisons over time and between jurisdictions have been done. Moreover, quantitative data may have serious limitations. They cannot portray the reality of violence in the lives of individual women – the fear such violence instills and the trauma it causes. It is the answers of women themselves that is necessary to provide the context and texture of that reality. Quantitative data always need to be complemented by qualitative data to give an accurate and complete picture of violence against women.

The sample sizes do not permit the disaggregation of data on violence against immigrant and refugee women, women of color, women with disabilities, teenage women and girls, older women, women living in poverty, homeless women, women in rural and remote communities and bisexual women. In the absence of sufficient data on women in all their diversity, these indicators cannot provide a complete profile of the experiences of all women in Australia or their experiences of violence through their lifecycles.

It was also noted that there is a lack of national data on the individual economic costs of violence against women including costs of the loss of financial supports, legal services, housing, mental and physical health etc.

The study has not assumed the percentage of people not reporting crime because of loss of their self reputation. In certain areas, such as violence against women, methodological shortcomings and lack of reporting, or under-reporting, led to inaccurate data collection, and such unreliable or mislea

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