THESIS

                                                                                         

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The Economic Situation of Women in
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Yeunhee Shin

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W

m1

THE ECONOMIC SITUATION OF WOMEN IN

KOREA AND CRIME AMONG MARRIED WOMEN

By

Yeunhee Shin

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF ARTS

School of Criminal Justice

1997

ABSTRACT

THE ECONOMIC SITUATION OF WOMEN IN
KOREA AND CRIME AMONG MARRIED WOMEN

By

Yeunhee Shin

This study addressed two neglected areas in the research on the relationship
between women's economic insecurity and married women's crime, and married women’s
crime and the effect of spouse abuse. Within women's economic marginalization
perspective on female criminality, the empirical research of this study considered the
married women's economic situations as the independent variables, their criminal
activities as the dependent variable, and wife battering as the intervening variable. The
findings of particular importance are: The effects of poverty in terms of absolute poverty
and self-perceived poverty failed to show significant effects on married women's crime.
At the same time, the variables relating women’s household responsibility to finding
family's resources such as women’s financial contribution to their family, women's
economic burden of supporting their family, and female-headed households were closely
related to married women's crime in The Republic of Korea*. Wife battering had not
intervening effects on the relationship between women's economic situations and married
women's criminal activities. The statistical test of the present study revealed that married
women committed crime due to the burden of supporting their family's needs combined
with limited available jobs or low paying jobs for women. In this sense, the result of this

study was encouraging Women’s Economic Marginalization Theory. (* The Republic of

Korea is ofien called South Korea or Korea. In this text, Korea means the Republic of Korea.)

ACKNOWLEDGMENTS

I'm grateful to the many people who helped me complete this thesis.

My deep appreciation is extended to Dr. Hoffman whose continued supports and
guidance has been a most rewarding part of this study. He helped me any time even
weekend, whenever I requested his help. His tremendous tolerance for my misplaced
creativity made this work possible.

I also thank Dr. Morash, who contributed important insights in the early part of
this study and suggestions on the methodological part.

I really appreciate to Dr. Nalla's faithful guidance on the theoretical part and
suggestions on the organization of this thesis.

I recognize a debt to many others: persons who aided in the collection of the data,
as to my old friends, colleagues, my sister, and my brother in Korea.

Finally, I thank my husband who gave me an opportunity to study at M.S.U..
Without his aids and patience along with my two kid's love, I could not complete this

work.

iii

TABLE OF CONTENTS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Page
LIST OF TABLES vi
LIST OF FIGURES viii
CHAPTER
I. INTRODUCTION 1
II. THE FEATURES OF FEMALE CRIME IN KOREA 4
III. THEORETICAL BACKGROUND 10
(1) Main Ideas of Women's Economic Marginalization Theory 10
(2) Theoretical Framework 14
IV. PREVIOUS RESEARCH 15
(1) Women’s Economic Situations and Female
Crime in Western Society 15
(2) Women's Economic Situations and Female
Crime in Korea 20
(3) Spouse Abuse and Female Criminality
in Western Society 22
(4) Spouse Abuse and Female Criminality
In Korea 24
(5) Summary of Previous Research 27
V. THE PURPOSE OF THE PRESENT STUDY 79
(1) Objectives 29
(2) Empirical Framework of the Present Study .30
(3) Hypotheses .31
VI. DATA AND METHOD .32
(1) Subjects .32
(2) Procedures .37
(3) Operationalization and Measures .37
(4) Limitations of the Reliability and Validity Concerns 45

 

iv

VII. FINDINGS 48

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(1) The Demographic Features of the Subjects 48
(2) Summary of Women's Economic Situation

Measures 54

(3) Summary of Wife Battering Measures 56
(4) Major Empirical Findings 58
Major Hypothesis 58
Sub-Hypothesis One 61
Sub-Hypothesis Two 63
Sub-Hypothesis Three 65
Sub-Hypothesis Four 67
Sub-Hypothesis Five 69
Sub-Hypothesis Six 71
Sub-Hypothesis Seven 74

(5) Discussion 79
VIII. SUMMARY AND CONCLUSION 91
REFERENCES 95
APPENDIX A (Questionnaire English) 98

 

APPENDIX B (Questionnaire Korean) 107

LIST OF TABLES

 

 

 

 

Table Page
11-]. Percent Distribution of Criminal Arrests by Gender between 1985 and 1994 ..... 5
11-2. Percent Distribution of Offense Patterns between 1985 and 1994 6
11-3. Number of Female Arrests and Rates of Female Arrests Per 1,000 6
11.4. Percent Distribution of Marital Status among Female Inmates 8
11-5. Percent Distribution of Female Arrests by Age 8
VI-l. Percent Distribution of Offense Patterns in the Subjects 35

 

VI-2. The Comparison between the two groups in Age,

 

 

 

 

 

 

 

 

 

 

 

 

Family Income, and Education Level 36
VI-3. Summary of Demographic Measures 43
VI-4. Summary of Economic Situation Measures 44
VI-5. Summary of Wife Battering Measures 45
VII-1. Length of marriage, and Number of Children - 48
VII-2. Frequency Distribution of Marital Status 49
VII—3. Family Structure 49
VII-4. Persons who Lived with the Subjects 51
VII-5. Persons who lived the Women with Husbands Absent 52
VII-6. Women's Job 52
VII-7. Husband's Job 53
VII-8. Offense Motivations , 54
VII-9. Summary of Economic Situation Variables 55

 

VII-10. The Extent of Wife Battering 57

vi

VII-11. Correlation Coefficients Among Women's Economic Situation

 

 

 

 

 

 

 

 

 

 

 

 

Variables and Married Women’s Crime 59
VII-12. Regression Coefficients for Effects of Economic

Situation Variables on Married Women’s Crime 60
VII-13. Married Women's Crime and Monthly Income 63
VII-14.Women's Financial Contribution and Married Women's Crime -64
VII-15. Women's Economic Burden and Married Women's Crime 66
VII-16. Women's Support Network and Married Women's Crime _ 68
VII-17. Economic Problems and Married Women's Crime 70
VII-1 8. Family Structure and Married Women’s Crime 72
VII-19. Wife Battering and Married Women's Crime 74
VII-20. Correlation Coefficients for Wife Battering and Economic Variables ............ 76
VII-21. Regression Coefficients Controlling for Wife Battering 77
VII-22. Monthly Income Under and Over the Poverty Line ..... 84
VII-23. Regression Coefficients Controlling for Family Structure 85
VII-24. Divorce Rate in Korea in 1980, 1985, 1990-1993 87

 

VII-25. Labor Force Participation Rate by Marital Status and Sex in 1990-1994 ...... 88

vii

LIST OF FIGURES

 

 

 

 

Figure Page
11-1. The Trend of Female Arrests Between 1975 and 1994 -- 7
III-1 . Framework of Women's Economic Marginalization Theory 14
V-1. Empirical Framework of the Present Study ..... 38
VII-l. The Result of Empirical Tests of This Study 81

VII-2. The Relationship Between Women's Financial Contribution
and Married Women's Crime Controlling for Family Structure .................. 86

VII-3. The Final Model to Explain Married Women's Crime in Korea ...... 90

 

viii

CHAPTER I

INTRODUCTION

The theories on female criminality which seek to associate female crime with its
environmental and sociological causes are involved in women's situations which are
different from those of men. "Women's Economic Marginalization Theory" (Bloom et
al.,1996; 14) argues that a large proportion of female offenders appear to be involved in
property crimes, and female property crimes are closely related to women’s poor
economic opportunities and limited alternatives to committing crime (Messerschmidt,
1986, Box and hale, 1982, Carlen, 1988, Naffine, 1987). In western society, women are
mostly economically marginalized and they are an economically powerless group, so
women are less able to resist the temptation to engage in illegal activities, when they are
faced with financial difficulties (Box, 1983:199; Messerschmidt, 1993:56).

The Republic of Korea1 is not an exception to such western patterns of female
crime. Female property crimes are a major offense of female crime in Korea (Korean
Training Institute for Criminal Justice, 1995:341). A higher proportion of female property
crimes, especially, the increasing rates of fraud by married women, may be a
consequence of limited job opportunities for women in Korea.

With respect to female criminality in Korea, an competing explanation which has

received little attention in other studies is abusive history among female offenders.

 

' The Republic of Korea is often called "South Korea" or simply "Korea". In this text, "Korea" will always
mean the Republic of Korea.

Reflecting abusive situations, many criminal women in Korea are divorced or separated
fi'om their husbands prior to incarceration. Based on the writer’ 3 personal experience in
counseling female inmates as a counseling officer for 8 years in correctional facilities in
Korea and on experiences of many other professionals working in correctional facilities
in Korea, a majority of female inmates talked about their abusive experiences before their
incarceration. Therefore, it might be assumed that abusive situations may relate to
married women's crime.

Based on the two major assumptions that first, if women are in insecure economic
situations they are more apt to commit crime, and second, female crime and females as
victims of spouse abuse relate to each other, the present study aims to examine with
Korean data Women's Economic Marginalization Theory developed in western society.
Within this theory, the present study has two major questions: (1) what is the relationship
between women's poor economic situations and female crime in Korea? (2) Does an
abusive situation positively relate to an increase of female crime in Korea? With these
two major questions, this study will focus on women’s economic situations and how these
situations are associated with female crime. Further, this study examines how an abusive
situation may be associated with female crime in Korea.

The present study is expected to make two contributions to both the application of
Women's Economic Marginalization theory to Korea and the improvement of the analysis
model of Women's Economic Marginalization Theory. First, the study can provide
information on whether the application of Women's Economic Marginalization Theory

on female criminality can be applied to Korea, which is different from western society in

terms of cultural and economic situations. Second, the study is expected to test the theory
through micro-measures of women's economic situations and married women's crime.

In Chapter II, which considers the background information on female criminality
in Korea, the major features of female criminality in south Korea are identified. Chapter
III outlines the theoretical approach of the present study. Chapter IV providers on
overview of the prior studies with regard to the relationship between women's economic
situation and female crime both in western society and in Korea, and the effect of wife
battering on married women's crime both in western society and in Korea. Chapter V
examines the objectives of the present study including the hypotheses which will be
discussed in chapter VII. Chapter VI describes the data and method. Chapter VII presents
the statistical analyses. The hypotheses of this study will also be examined using bivariate
correlation coefficients, multiple logistic regressions, crosstabulations, and t-tests.
Discussion over the results of empirical tests and the conclusion will be presented in the
last part of this chapter. Finally, chapter VIII summarizes the empirical findings of the
present study and discusses the limitation of the present study and suggestions for future

study.

CHAPTER II

THE FEATURES OF FEMALE CRIME IN KOREA

In this chapter, the main features of female crime in Korea are presented. This
statement can provide a preliminary exploration of women's economic situations as
causes of female crime in Korea. There are four major features of female crime in south
Korea. That are relevant to the present study.2

First, women are unlikely to enter crime at any age in Korea. Arrest statistics
indicates that vast majority of crimes are committed by males, when females are
compared to males in their arrest rates. The annual report on crime reveals females were
approximately 10% of total criminals between 1985 and 1994 (Korean Training Institute
for Criminal Justice, 1995; 333-334). The difference in male-female arrests can be seen in
gender ratios in arrests reported in Table 11-] below. As shown in Table 11-], male arrests
constituted from 91.7 percent 86.5 percent of all persons arrested compared to 13.5
percent to 8.3 percent for female arrested for the last decade. For total offenses males
were arrested 11 times for every female arrested in 1987 and 6.4 times of every female
arrested in 1994, as reported in Table 11-1. What this data tell us is that the proportion of

these female crimes on society is still small compared to their male counterparts.

 

2 In Korea, there are two major sources of criminal statistics: one is Analytical Report on Crime which is
annually reported by The Supreme Public Prosecutors‘ Office, the other one is Annual Criminal Statistics
reported by Korean Training Institute For Criminal Justice under Ministry of Justice. The present study
characterized the features of female criminality in Korea based on these two criminal statistics through
directly adapting or reconstructing the data.

Nevertheless, this should not distract from the severity of the growing problem of female
crime in Korea, because a proportion of female crime in total offender population has
gradually increased. Table II-l shows the comparison between male and female in their

arrest rates for the last decade.

Table II—l . Percent Distribution of Criminal Arrests by Gender from 1985 to 1994

 

Year Percent Male Percent Female
1985 90.6 9.4
1986 90.7 9.3
1987 91.7 8.3
1988 91.4 8.6
1989 91.3 8.7
1990 90.1 9.9
1991 89.7 10.3
1992 89.9 10.1
1993 88.1 11.9
1994 86.5 13.5

 

 

 

Source: Adapted from Korea Training Institute for Criminal Justice, Criminal Statistics, 19942334

Second, arrests of female offenders for property crimes is the most common
offense in Korea. Table II-2 below shows that more than 50 percent of female offenders
are involved with property crimes. Furthermore, a proportion of female property crimes
among female offenders reached 60.2 percent in 1993, 64.4 percent in 1994.

Third, arrest trends indicate that female crime is on the rise. Between 1975 and
1994, total female arrests increase 332 percent reported in Table II-3 below. Female

crime rate and female crime rate per 1,000 had gradually increased between 1975 and

Table II-2. Percent Distribution of Offense Patterns3 between 1985 and 1994

 

 

 

 

 

 

 

 

 

 

 

Property Violent Counter- Public Careless Others Total

Crimes Crimes feiting Moral Crimes
1985 54.6 12.3 2.6 19.2 2.2 9.1 100
1986 53.5 12.6 3.0 19.5 1.9 9.5 100
1987 52.1 13.1 3.0 19.5 1.6 9.5 100
1988 50.3 14.4 3.2 21.3 1.8 9.0 100
1989 47.9 14.6 3.6 21.9 1.5 10.5 100
1990 47.1 13.8 3.4 24.1 1.3 10.3 100
1991 50.0 12.1 3.1 23.8 1.3 9.7 100
1992 56.2 10.1 2.8 21.3 1.0 8.6 100
1993 60.2 9.0 2.3 20.0 0.8 7.7 100
1994 64.4 9.1 2.6 15.6 0.8 7.5 100

 

 

 

 

 

 

 

 

 

 

Source: Adapted from Korea Training institute for Criminal Justice, Annual Criminal Statistics, 1995:34

Table II-3. Number of Female Arrests and Rate of Female Arrests Per 1,000

 

Number of Female Arrests Rate of Female Arrests per 1,000
1975 50677 (100) 2.9
1980 81059 (160) 4.3
1985 94872 (187) 4.7
1990 140831 (278) 6.5
1994 2241 18 (442) 10.2

 

 

 

Source: Adapted from Korea Training Institute for Criminal Justice, Criminal Statistics, 1994: 334.
( ):Index when we see the number of female arrests in 1975 as 100

 

3 The Supreme Public Prosecutor‘s Office classified offense patterns into six categories such as property
crimes: thefi, fraud, embezzlement, burglary, violent cranes: murder, assault, kidnap, wounding,
counterfeiting: forgery, counterfeit, public moral cranes; adultery, prostitution, gambling, careless
crimenraffic accident, careless wounding, and others.

1985. Especially, both of them had rapidly increased between 1986 and 1994.Table II-3
above shows the number of female arrests increased by 332% between 1975 and 1994,
also female crime rate per 1,000 had 3.5 times increased during this period. Table II-3
and Figure II-l indicate that female crime is a growing problem in Korea.

Figure II-1.The Trend of Female Arrests Between 1975 and 1994

 

250000
200000
150000
100000
50000

0

1975 1980 1985 1990 1994

year

numbers

 

 

 

 

Finally, married women are more likely than unmarried women to commit crime.
Over 80 percent of the female offenders are married women, compared to under 20
percent of the unmarried women reported Table II-4 below. When female population of
15 years old and over by their marital status are compared to percent distribution of
female offender by marital status reported in Table II-4, 72.2 % of general female
population were married while 81.6% of female criminals were married in 1990. From
this Table 114, a proportion of married women among female offenders was higher than a
proportion of married women in general female population ages 15 and over. Also, the
age distribution among female inmates indicates married women are more likely than
unmarried women to commit crime reported in Table II-5 below. For example, the

percent of late 20s (26-30) criminal women (15.7%) who are mostly married is higher

than those of early 20s criminal women (9.8%) who are mostly unmanied. Therefore, the

data on the comparison between the proportion of criminal married women and a

proportion of general female population married women (Table II-4), and the percent

distribution of female arrested by age (Table II-5) present that married women in Korea

are more likely to engage in criminal activities than unmarried women.

Table II-4. Percent Distribution of Marital Status among Female Offenders and among
Female Total Population Ages 15 and over

 

 

 

 

 

 

 

Female Offenders* Population Age 15 or over"

married (%) unmarried (%) married (%) unmarried (%)
1990 81.56 18.44 72.2 27.8
1991 82.06 17.94 71.9 28.1

 

 

 

 

* Source: Korea Training Institute for Criminal Justice, Criminal Statistics, 1994:368
M Source: Originally Constructed by National Statistical Office, Population and Housing Census Report,

1992, Recited from Korean Women's Development Institute, Statistical Yearbook on Women, 1995:64-65

Table II-5. Percent Distribution of Female Arrested by Age

 

1988 1989
less than 19 3.6 3.3
20 ~ 25 9.8 9.4
26 ~ 30 15.7 15.3
30 ~ 40 35.2 35.0
41 ~ 50 23.5 24.2
51 ~ 60 8.6 8.2
over 61 3.5 3.1

 

 

 

Source: Adapted from The Supreme Public Prosecutor’ 3 Office, Analytical Report on Crime, 1995 :25

In this chapter, the major features of female criminality in Korea were presented.

In conclusion, female crime in Korea is a growing problem with the increasing rates of

female crime. Especially, high proportion of married women's crime and property crimes

among female offenders appear to be critical issues.

CHAPTER III

THEORETICAL BACKGROUND

1. Main Ideas of Women's Economic Marginalization Theory

The purpose and function of this chapter is to present the theoretical approach that
guides this study. A brief review of prior studies of Women’s Economic Marginalization
Theory on female criminality will be helpful in developing the theoretical orientation

employed in this study.

The basic ideas of Women's Economic Marginalization Theory are focused on
the women's poor economic situations linked to social structure dominated by men. And
women's crime is assumed to be caused primarily by social factors such as "limited
legitimate job opporttmities for women, women's increased burden of household
production" ( Milkman, 1993: 291-300), absolute low family income, and so on.

The explanation for female crime that " women's economic marginalization has
contributed to female property offense has been advanced recently by British
Criminologist including Steven Box and Chris Hale" (Naffme, 1987: 99). Box and Hale

presented this view as they write:

..... the major factor accounting for most of the increase in property
offenses seems to be economic marginalization. In other words, as

women become economically worse off, largely through unemployment

10

11

and inadequate compensatory levels of welfare benefits, so they are less able
to and willing to resist the temptations to engage in property offenses as
a way of helping solve their financial difficulties" (Box, 1983;199, Box and

Hale, 1984: 447).

Messerschmidt (1993: 1-24) explained that women's economic situations in the
US. is linked to social structure called "Patriarchal capitalism". In his book of
Capitalism, Patriarchy, and Crime, he has consistently emphasized patriarchal gender
relations, in which the male gender has the labor power and controls the female while
females have no labor power and are economically marginalized. This is because under
patriarchal capitalism, males in all classes are wage laborers while females are primarily
housekeepers and mothers. Thus, when women need to earn the money by themselves,
they turn to illegal activities in the face of economic marginalization for women, because
of unemployment, limited types of available jobs, and low pay or poor working
conditions (Messerschmidt, 1993:73-95). Simpson briefly reviewed Messerschmidt‘s
explanation that crime and opportunities to commit crimes vary according to one's

structural position According to Simpson:

..... under the economic base of capitalistic society, lower-class and female
crime reflects a powerless status, but because of gender social organization
crime opportunities are distributes unequally, and male are apt to resist their

powerless position, while female accommodate their powerlessness, so male
and female criminality take entirely different forms (Simpson, 1995: 124-125).

According to Messerschmidt, the female subordinate position in patriarchal

12

capitalistic society means that they commit less serious crimes than men, and female
crime is a consequence of the feminization of poverty or the marginalization in the
legitimate wage labors under patriarchal capitalistic society (Messerschmidt, 1986: 87).
Bloom et al.(1995:7-8) described Economic Marginalization Theory as an
alternative to the structural opportunity theory relating women’s liberation and female
crime presented by Adler and Simon.4 They share the perspective on the effect of

women's poverty on female crime with British Criminologist Box that "female

 

‘ Adler and Simon have argued that "as women begin to assume traditionally male positions of prestige and
authority, as they begin to enter white-collar jobs, their opportunities for crime and their criminal
involvement will rise (Heidensohn, 1995: 155-156). In short, they have argued that the rise in female crime
is due to the increase in female labor force participation. In this point of view, increased participation of
females in the labor force change women's identity and self-concept, and a parallel rise in female
criminality. However this perspective has been criticized by many other feminist theories of female
criminality. According to Leonard‘s literature review on theories of female criminality, many female
offenders are poor, single, unemployed, uneducated, and belonging to a racial minority, and thus they have
not taken part in the women‘s liberation and greater social and economic opportunities. Therefore, the
increased rate of female crime is not due to liberation rather than due to their poor economic situation
(Leonard, 1982: 182). Stefl'ensmeire analyzed the differences between male and female in the patterns of
adult crime data for periods between the 1965 and 1977. He presented that arrest patterns have changed
very little, when the female labor force participation rate increased enormously, or for the decade following
1968, when feminist activists and organizations expanded (steffrnensmeire, 1980:1087). Box concluded the
result of Steffensmeire‘s research that his research was unable to locate any empirical support for linking
female emancipation to crime (Box, 1983: 192).

13

crime, the bulk of which is property crimes, constitutes a rational response to poverty and
economic insecurity" that is more likely to be unemployed or unemployable, or even if
employed, than more likely to be insecure, low paid, unskillful jobs (Box,1983: 197 ).

The other issue relating to women's poor economic situation was raised by Rafter
(1990). He pointed out that the increasing rates of female-headed households affect
married women's crime. Bloom et.al. reviewed Rafter’ s findings:

...... the increasing numbers of female-headed households supporting

dependent children lead more and more women to seek the benefits of

criminal activity as supplements or alternatives to employment"

( Bloom et. al., 1995: 9).

An economic perspective on female criminality begins with an evaluation of the
benefits and costs of women's participation in crime (Milkman,1993). Within this
perspective, Milkman suggested that people were more likely to commit crime when they
perceived that they had more gain than to lose by law-breaking (Milkman, 1993: 293). He
asserted that women are attracted to crime, because they have poor legitimate
opportunities, so "women have less to lose from unsuccessful criminal activities that can
lead to irnprisomnent or loss of employment opportunities" (Milkman, 1993:294-295).

In conclusion, women’s participation in some types of illegal activities can be
attributed to their insecure economic situations. Furthermore, their poorer economic
experiences of limited available jobs or low paying jobs make crime an attractive
alternative to legal activities for making money. In short, Women's Economic

Marginalization perspective emphasizes the importance of women's economic situations

14

as causes of female crime. The poor economic situations including women's restricted
labor market opportunities and increased burden of finding resources to support their

household needs, are the major causes of female crime, according to this theory.

(2) Theoretical Framework
Figure II-l shows a general model of Women's Economic Marginalization
perspectives on female crime.

Figure III-1. Framework of Women’s Economic Marginalization Theorys

 

Patriarchal Capitalistic Society

 

 

 

 

 

Women's Poor Economic Situation

- Unemployment
- Main providers of their family resources

- Lack of support network

1

Women’s Criminal Activities

 

 

- Poverty

 

 

 

 

5 This framework is based on Messerschmidt's explanation on female criminality within Women's
Economic Marginalization Theory.

CHAPTER IV

PREVIOUS RESEARCH

The review of the literature includes four major sections: (1) women's economic
situations and female crime in western society, (2) women's economic situations and
female crime in Korea, (3) spouse abuse and female criminality in western society, and

(4) spouse abuse and female criminality in Korea.

(1) Women's Economic Situation and Female Crime in Western Society

Some researchers who have reported positive correlation between poverty and crime
rates have assumed that as women's poverty increases, the rate of criminal behavior
increases (Box and Hale, 1982:20-21). They started the application of Women's Economic
Marginalization Theory by refuting the women's liberation movement perspective which
explained the increased rates of female crime within women's emancipation (Box, 1993;
Bartel, 1979).

With a major assumption about the possible relationship between women's
poverty and female crime, the empirical research examines the possibility of increasing
female crime accompanied by unemployment in female or income inequality (Bartel,
1979, Carlen, 1988, Box and Hale, 1984, Box, 1987).

These studies mostly focused on macro-level analysis using official data. For

instance, Bartel (1979) examined the labor force participation rates for females and the

15

16

average number of female property crimes between 1960 and 1974 in the US. With the
question that inferior legal opportunities was responsible for the female’s interest in
criminal activities, Bartel attempted to examine the determinants of female participation
in criminal activities using the number of female offenses reported to the police and
female unemployment rates between 1960 and 1974 (Bartel, 1979: 29). Bartel’s findings
showed that the labor force participation rate of married women’s crime had no effect on
personal crimes such as burglary and auto thefts. Briefly, his result indicated that inferior
legal opportunities to make money were responsible for the females interest in criminal
activities, especially a high rate of married women's property crimes were due to the
married women’s poor opportunities in legitimate job market (Bartel, 1979: 29-49).
Milkman read Bartel's finds that decreased rate of female labor force participation
resulted in the increased female participation rate in illegal activities if all other factors6
remained unchanged ( Milkman, 1993:293).

A British criminologist, Carlen, has also focused on the relationship between
women's poverty and female crime in Britain. In her book, Women, Crime and Poverty,
she described the results of research on thirty-nine women's criminal careers, as described
by the women in oral interviews. Her interview questions consisted of the four major
factors- poverty, being in residential care, drug (including alcohol addiction), and the

quest for excitement. She explicitly identified the ethnographic characteristics of the

 

6 Bartel‘s important socioeconomic variables in explaining female crime are percentage of females age 16
and over who are married with spouse present, percentage of single females age 16 and over, median age
of the female populations, unemployment rate of females age 16 and over, average number of children
under 6 in female-headed families, and so on. Bartel argued in his empirical study that the rise in female
crime was not due to the rise in the female labor force participation rate, but due to the women‘s inferior
opportunities in the legal sector if other socioeconomic variables except employment rate for women were
unchanged (Bartel, 1979: 39-49).

17

subjects and women’s economic situations prior to their incarceration (Carlen, 1988:12).
Within economic perspective of crime, Carlen presented her findings that the
respondents’ motivation of crime were mostly related to economic gains, and they
committed crime because of poverty, inability to obtain employment, avoiding going
into residential care, and so on (Carlen, 1988:69-70). She continued to explain the causes
of female crime based on economic perspective on crime. According to Carlen:

...... due to their poorer economic situations, they perceive themselves as being

marginalized and therefore, having nothing to lose, decide that law-breaking

is a preferable alternative to poverty and social isolation. The subjects felt that

they had absolutely nothing to lose and something to gain by engaging in

criminal activities (Carlen, 1988:14).

In short, one of Carlen's major findings is that her thirty-nine subjects had in the
main committed crime because of experiencing poverty and not enough financial support
relating an excess of welfare regulation (Carlen, 1988:11-14).

Box and Hale have advanced the study involved with women’s poverty and
committing crime in female population in England and Wales. They examined the effects
of women's poverty on female crime through macro-level measures of employment rates
in females and female crime rates for a certain period using official data. Like other
criminologist who presented Women's Economic Marginalization perspective on female
criminality, Box and Hale argued that the increasing rates of female crimes were not due
to women's liberation movement and the increased labor force participation in women,

but due to women's poverty caused by unemployment and limited public aids.

18

(Box,1983: 192). They considered females convicted of indictable crimes over the period
1951-1980 and reported that increases in the rate of female unemployment were
significantly related to increase in the rate of conviction for violent, theft, fraud, and so on
(Box and Hale, 1984: , Box, 1987:73).

Box considered prior research on poverty and female crime in the US. and
England and consistently suggested the causal relationship between women's poverty and
female crime. According to Box, the growing economic marginalization of females has
effect on women’s criminal activity, particularly, property crimes (Box, 1983: 193-194).
In his another book, Recession, Crime and Punishment, he reviewed North American and
British studies which dealt with the relationship between women's unemployment rates
and female crime, and he concluded that more women have become economically
marginalized during the recession, more conventional crimes are committed by females
(Box, 1987:43). Box (1983:187-200) argued about the applicability to England and Wales
of the liberation versus marginalization theses. To accomplish, Box and Hale analyzed
the four annual indicators for female liberation for the period 1951-1979. The four female
liberation indicators which Box and Hale constructed to test the effects of women's
liberation movement on female crime rates are:

(1) the number of live children per 1,000 women age 14-45;
(2) the number of unmarried women per 10,000 age 15-65;
(3) the rate of higher education experience per 100,000 women age

15-65; and (4) the rate per 100,000 women age 15-65 of participation

in the labor force (Box, 1983: 187).

19

The results that Box argued were that first, although some upper middle-class
women have male dominated professional jobs, a majority of women were unemployed,
or if employed, they have lower paid, unskilled, part-time jobs. Thus, women's economic
marginalization was more the important cause of increases in female crime than female
emancipation (Box, 1983: 187). Second, the major factor accounting for most of the
increase in female property offenses seemed to related to women's be economically
marginalized status such as poor employed and limited support network. Therefore,
women engaged in property offenses as an alternative to employment to solve their
financial difficulties (Box, 1983 : 188).

In conclusion, previous research mostly analyzed the macro-measures of female
crime using official data. According to Messerschmidt's conclusion of these previous
research on the effects of employment rate, female crime rate and female property crime
begin to increase, when the unemployment rate for women increased (Messerschmidt,
1987:87).

However, their macro-measures of female crime with aggregate time-series data
did not answer the individual differences between criminal women and non-criminal
women, because poverty lead to committing crime for some women while does not for

other some women. The limitations of prior studies will be discussed later.

(2) Women's Economic Situations and Female Crime In Korea

20

Existing studies on the features of women's economic situations both women in
general and criminal women in Korea show that Korean women are economically
marginalized (Kim, 1995; Yang, 1993: Elizabeth, 1994; Choi, 1986).

Traditional values in patriarchal society in Korea emphasizes a women's place in
the family. Until the late 1980’s, Korea exhibited more discrimination against women
than other countries. Gender disparity in education and work experience and sex
segregation by industry and occupation explains much of the lower relative wage of
women in Korea (Elizabeth, 1994: 43 8). Even though, the Korean National Assembly
enacted an Equal Employment Law in 1988, and the Government issued Guidelines to
eliminate Sexual Discrimination in Employment in 1991, the labor participation rate for
women still lower than those of men (Elizabeth,1994: 436). Economically active female
population has gradually increased from 40.4 % in 1975 to 47.3% in 1992 (Yang,
1993:133; statistical Yearbook on Women, 1995:136-137). However, a proportion of
female laborers (40%) in total economically active population is still lower than those of
male (60%) in 1992. These data indicate that south Korean women are still marginalized
in legal opportunities in terms of job market. Indeed, even if women are employed in
Korea, they are low paid or temporary employees (Kim, 1995: 104). For instance, a
majority of female laborers ( 87% ) work in one of three industrial sectors; agriculture,
manufacturing, or commercial (hotel and restaurant) which are mostly low paying or
unstable jobs (Elizabeth,1994: 436-43 8). Furthermore, the labor force participation rate of

women that have more than twelve years of formal education is lower ( 36.2% ) than for

21

women with no formal education ( 46.5%), or women with six years or less of a formal
education (45 % ) (Cho, 1986:50—51).

In short, even though, 47.3 % of female population aged 15 and over participate in
labor market and 40 % of total economically active population is female in Korea, many
of them are low paid, or temporary employed and low educated women.

Female crime in Korea reflects the women's economic situations. As mentioned
above, between 1985 and 1994 the major crimes which were committed by women were
property crimes (over 50%) (See page 6 Table II-2 above). Particularly, fraud which is
the most common offense for Korean women has rapidly increased among married
women ages 303 and 408. (Korean training Institute for Criminal Justice, 1995: 333-334).
As Messerschmidt mentioned above (1987:87), there is age specific in case of fraud in
Korea.

Lee pointed out the employment situation among female offenders in his master's
thesis. He presented that a majority of female offenders were housekeepers (25%) or
jobless women (15.5%) before their incarceration (Lee, 1991: 62). Even though he did
not read the relationship between low employment rate among female offenders and
women's crime, he suggested that the enlargement of job opportunities for women be
necessary to reduce female crime (Lee, 1991:101).

Choi (1993:88) emphasized the realities of unstable marital situations among
female offenders compared to general non-criminal married women. Even though he did

not mention out the female-headed households as a cause of married women's crime, he

22

presented that the female offender are more likely than non-criminal to be divorced,
living separated from their husbands, or separated from their husbands by death.

The issues of these previous studies related to female criminality have showed
that economic insecure situations such as poverty, insufficient support from their
husbands or others, and the burden of household responsibility to supporting their
family accompanied with unstable marital situations are links to female crime in Korea.
Although most studies on female criminality in Korea have pointed out the realities of
poor economic situations among female offenders, there is no existing empirical research
on examining the effects of women's economic insecurity on female crime in Korea.
Indeed, some studies which have dealt with the realities of female criminality in Korea
have collected the data from the Chongjoo Women Correctional Institution. Female
offenders in Korea who are accommodated in this facility are mostly serious offenders or
female recidivists. Therefore, these studies can not generalize to general female offenders

in Korea.

(3) Spouse Abuse and Female Criminality in Western Society

According to Yllo in 1993, "the problem of domestic violence is deeply rooted in
the historical imbalance of power between men and women". Therefore, the reason of
spouse abuse is not in the personality characteristics of batterer or battered persons , but
in the social structure which marginalize women in society and at home (Yllo, 1993:72).

Messerschmidt read wife battering linked to women's powerless status under

capitalistic society. According to Messerschmidt, the more traditional gender role in

23

household, the greater likelihood of wife battering (Messerschmidt, 1993: 37, 145).
However, he did not mention about the relationship between women's abusive situation
and female crime.

Some research reported that many female inmates have been victims of domestic
violence, before and during their victimization of others (Brett, 1993, Clark, 1995).
According to Brett (1993: 26), many female prison inmates have been victims of violence
before and during their victimization of others. Brett pointed out that women's
victimization of others especially, violence toward their abuser, is related to their chronic
abusive experiences by their husbands. Brett stated:

...... the psychological effects of abuse on women is that victims demonstrate

deficits in learning novel behavior, may experience chronic subjective stress.

Accordingly, when a person has lived in a situation of chronic abuse, the

motivation to avoid conflicts may become so great that she will choose a

course of action without thinking through the consequences (Brett, 1993:26—28).

Flowers also emphasized that a majority of female offenders are a kind of
victims of domestic violence, particularly homicidal women who kill their spouse or boy
friend report doing so after repeated physical, sexual, and mental abuse by their male
partners (Flower, 1995: 72-73). Flower continued to explain the influence of battered
experience among female offenders as reflecting the relationship between abusive
situation and female crime. Women in prison for murder are more likely to have killed a
spouse, ex-spouse, or other intimate person than other persons (Flowers, 1995: 74-75). He

described:

24

...... the motivation most often associated with this form of homicide is
self-defense or desperation culminating a period of abuse from a husband or
father. Abused women who have murdered their spouses reveal that they feel

that homicide was the only alternative lefi to them (Flowers, 1987:108-109).

The self—defensive nature of homicides committed by women against the men
who abused them was also argued by Browne. According to Browne, 60 percent of
husbands who were killed by their wives brought about their deaths by striking out first,
and homicides committed by women seven times as likely to be in self-defense as
homicides committed by men (Browne, 1987:140). Mechanic supported Browne‘s
perspective of female spouse homicide as self-defense activities. After reviewing several
researchers‘ argument Mechanic concludes that clearly, there is a link between prior
abuse and homicide by battered women in at least some cases. Also female perpetrated
homicides tend to be self-defensive acts committed in an interpersonal context, rather
than instrumental acts of violence (Mechanic, 1996:135-136).

In short, previous research on abusive history among female offenders presented
that at least certain kinds of female crime were related to their abusive situations and
many female offenders have experienced spouse abuse before their incarceration.
However, these studies did not discuss wife battering as a cause of female crime. To
accomplish this, the comparison between female offenders and general female population

in their abusive history may be necessary.

(4) Spouse Abuse and Female Criminality in Korea

25

Korea is one of the most traditional Patriarchal societies around the world. Even
though Korea is changing rapidly and a majority of Korean do not perceive wife battering
as permissible things, wife battering still remains many homes. In one recent study
addressed that 42 % of Korean women had been beaten by their husbands during their
married life (Campbell, 1994: 101) and the wife battering rate in Korea is higher than US
(28%), Canada ( 25%), Mexico (34%), and similar to Japan (40-59%) and Australia
(42%).

The causes of wife battering in Korea closely associated with male dominated
culture linked to Confucian tradition in Korea (Korean Women's Development Institute,
1992: 43; Song, 1996: 1920). Wife battering is still regarded by many as a family matter
not as a crime, and the police usually do not pay attention to wife battering (The New
York Times, 1996). According to Shim (1992:183-184) the reason that makes Korean
tolerate wife battering is closely related to the cultural norms originated from Confucian
ideas such as men over women and women's passive attitude to their husbands.

Korean institute for Criminology administrated the questionnaire for 1200 Seoul
residents (640 women samples, 560 men samples) in 1991 to examine the causes and
prevalence of domestic violence in Korea. This research revealed that during a one year
period, 28.4% of the respondents had experienced violence from their husbands at least
once, whereas 45.3% of the respondents had experienced non-serious violence such as
slapped or hit with something once or twice during their married life time (Shim, 1992:

70-77).

26

There is no existing study on the relationship between spouse abuse and female
crime in Korea. Also abusive history among female offenders has never been
investigated. However, as the writer’ 8 counseling experience with female offenders in
Korea, the effect of abusive situation on women might be crucial, because a majority of
female offenders had talked about their battered experience, particularly females who
killed their husbands told their husbands' chronic wife battering habits as a motivation of
their offense.

Some demographic features of female offenders presented by several research
might support the impact of women's abusive situation on female violent crime in Korea.
According to Choi's research with 306 female convicts subjects who were in Chong Joo
Women Prison (1992: 84-85), a majority (23.7%) of the victims of female offense were
husbands and family members. Further, in case of female homicide, 53.1% of the victims
were their husbands or family members (Choi, 1992: 84-86).

Lee administrated the questionnaire to 312 female offenders accommodated in
Chong Joo Women Prison to investigate the actual conditions of female offenders and
implications for female offenders in Korea. One of his finding was that a majority
(72.5%) of female homicide were motivated their criminal activities by family problems
such as abusive situation (21.1%), conflicts with their husbands or family-in-law (12.7%),
and extra-marital affairs mixed with conflict with their husbands or chronic wife battering

(38.7%) (Lee, 1991: 53-54).

(5) Summary and the Limitation of the Previous Research

27

Briefly, the prior research on the effects of women’s economic situations on their
criminal acts mostly presented that women's poor economic situations in terms of limited
job opportunities and the burden of household responsibility without sufficient support
networks are closely related to the causes of female crime.

The previous studies on the relationship between women's economic situations
and female crime rates were mostly macro-level analyses estimated from aggregate
time-serious data such as female crime rates reported from police and female
unemployment records adapted from the annual census (Box and Hale, 1984; Box, 1986;
Bartel, 1979). They provided empirical evidence for the hypotheses relating female
property crimes and socioeconomic conditions facing women. The other type of studies
analyzed the demographic features of female criminality relating economic situations
facing women using self-reported data from female offenders (Carlen, 1988, Lee, 1991,
Choi, 1992). They described women’s poor economic situations as the motivation of
committing crime.

However, these studies are incomplete. For example, they could not answer the
question that some poor women engage in illegal activities while other poor women have
always managed their lives without any criminal activities. Indeed, these research have
not distinguished married women from unmarried women in spite of the existence of
different economic situations between the two groups.

The present study focuses on individual level of variables which were ignored by
previous research. This study analyzes the data relating women's economic situations

such as monthly income in terms of absolute poverty, women‘s contribution to family‘s

28

financial resources, women‘s economic burden of supporting their family, women's
support network, self-evaluated economic problems in terms of relative and self-
perceived poverty, and female-headed household. The empirical relationships between
these economic situation variables and married women's crime will be examined through
comparing the criminal women subjects’ economic situations to those of non-criminal
women using data from Korea.

With respect to the effect of spouse abuse on female crime, most studies pointed
out that many female offenders have experienced serious spouse abuse by their husband
or boy friends prior to incarceration. Basically, female crime and wife battering may not
be directly related to each other, but both of them might be resulted from the same
situation of women’s powerlessness status linked to social structure. However the
previous studies did not examine the effect of abusive situation on female crime. The
present study will also examine whether an abusive situation positively relates to female

crime.

CHAPTER V

THE PURPOSE OF THE PRESENT STUDY

(1) Objectives

The present study examines the relationship between married women's economic
situations and their criminal activities in Korea. This study attempts to apply Women's
Economic Marginalization Theory to Korea as an explanation of the causes of married
women's crime in Korea. Indeed, the present study examines the theory through micro-
model analysis using micro-level measures of self-report data. The data were collected
from lower socioeconomic class women in terms of age, education, and income levels for
both female criminals and non-criminals. The present study intends to explore the
differences between the two groups in their economic situation variables such as family's
income level, extent of women's contribution to family's financial resources, women's
economic burden of supporting their family, women's support network, the extent of
economic problems, and family structure. Further, this study collected the data only from
married women in order to obtain a homogeneity among the subjects, and in examining
the effects of women's abusive situations on committing crime by married women in
Korea.

Thus, the two major purposes of the present study are: To test the women's
economic marginalization perspective on female crime through examining the effects of

married women's economic situations on their criminal activities in Korea; To examine

29

30

whether abusive situations increase female crime through controlling for the battered
experience on the original relationships between women’s economic situations and

married women's crime.

(2) The Empirical Framework of the Present Study

The present study considered six economic situations facing married women as
independent variables, married women's crime as a dependent variable, and wife

battering as a intervening variable.

Figure V-l. Empirical Framework of the Present Study

 

Women's Economic Situations
(Hypothesized Independent Variables )
- Family Income Level (Hypothesis 1)
- Women's Contribution to the Family's
Financial Needs (Hypothesis 2)
- Women's Economic Burden of

Supporting Family (Hypothesis 3)

/

- Women's Support Network (Hypothesis 4) ——'

- Extent of Economic Problems /

(Hypothesis 5)
- Family Structure (Hypothesis 6)

1

Women's Abusive Situation Committing Crime
(Hypothesized Intervening (Hypothesized Dependent
Variable) Variable)

 

 

 

 

 

 

V

 

 

 

 

 

 

31

(3) The Hypotheses of the Present Study
The major hypothesis and seven sub-hypotheses, which will be discussed and

tested in chapter VII are listed below:

Major Hypothesis: There is a relationship between married womenfs economic

 

situations and married women is crime in Korea.

Sub-hypothesis 1: Criminal married women are more likely than non-criminal
married women to have lower monthly income (negative relationship).

Sub-hypothesis 2: Criminal married women ge more likely than non-criminal
married women to contribute to their family's financial needs (positive relationship).

Sub-hypothesis 3: Criminal married women are more likely than non-criminal
r_n_arried women to have economic burden of suppgrting their family resources_ (positive
relationship).

Sub-hypothesis 4: Criminal married women are less likely than non-criminal

married women to have sumrt network (negative relationship).

Sub-hypothesis 5: Criminal married women are more likely than non-criminal
married women to have economic problems (positive relationship).

Sub-hypothesis 6: Criminal married women are less likely th_an non-cm;
Med women to reside in mile-headed hou_sehold (negative relationship).

Sub-hypothesis 7: Women who have been seriously abused by their snow
more liker to commit crime than women who h_ave not been seriously abused, regardless

of their economic situations (positive relationship).

CHAPTER VI

DATA AND METHOD

(1) Subjects

Composition of the sample

The subjects for the study consisted of two groups. The first group was composed
of 110 criminal married women who were in the three correctional facilities in south
Korea. The second group who were non-criminal married women included 25 factory
laborers and 40 wives of hospitalized men and the hospitalized married women in Seoul
south Korea.

Generally, over 90 % of female offenders in south Korea were lower or middle
socioeconomic class in 1990 (Lee, 1991: 50). Reflecting the socioeconomic class
distribution among criminal women, the non-criminal women subjects of this study were
selected fi'om the factory laborers and the wives of hospital male patients both of whom

were mostly lower socioeconomic class and a few of them middle socioeconomic class.

Background information for the sampling strategies

With respect to these criminal women subjects, background information for
sampling strategies are the followings:

For field-level correctional organizations, there are a total of 40 correctional

facilities in Korea. More detail, the number breaks down into 25 correctional institutions

32

33

for adults (4 only for male offenders, 21 for male and female offenders), 2 juvenile
correctional institutions, 1 women correctional institution, 2 open correctional
institutions, 6 detention houses, 2 social protection houses (Maximum-Security) for male
prisoners only, 1 branch of the correctional institution, and 1 branch of the detention
house ( Correction Bureau, 1991: 6-7).

Persons convicted are accommodated in correctional institutions if they are 20
years old or more, and in juvenile correctional institutions if they are younger than 20
years old. However, each correctional institution has a separate building in the facility for
criminal suspects and criminal defendants. Criminal suspects and criminal defendants,
who have been subjected to the execution of an arrest warrant are accommodated and
managed in a Detention House. Each Detention House has a separate building or cells for
several non-serious convicts. Accommodated in a social protection house are the persons
sentenced to protective custody under the Act for the Protection of Society, for education
and training. Exemplary prisoners selected from correctional institutions across the nation
are gathered in open correctional institutions.

Among 40 correctional facilities in Korea, female offenders can be incarcerated

at 32 correctional facilities. The institutions which do not accept female offenders are 4
male only correctional institutions and 2 social protection houses, and 2 juvenile
correctional institutions.

The criminal women subject were chosen from Seoul Detention House which is

the largest in Korea, from Sung Dong Detention House which is the second largest

34

Detention House in Korea, and from In-Cheon Correctional Institution in Korea. Thus the
criminal women subjects in this study are representative of female inmates in Korea.
With respect to the non-criminal married women subjects, most factory laborers
are middle or lower socioeconomic class women, while hospitalized married women and
the wives of hospitalized men are lower socioeconomic class women, because the
hospital is operated by Seoul city for very poor people. Therefore, the non-criminal
married women subjects may be representative of lower or middle socioeconomic class

women in Korea

Representative of the criminal women sample and homogeneity between the two
mic groups in their socioeconomic status

With regard to the criminal sample's representation of total female offender
population in south Korea, when the target subjects of 110 criminal married women was
researched, the sample was compared to the annual statistical report on female crime in
1995.7

This comparison between criminal women subjects of this study and female
offender population in Korea revealed no significant differences in the distribution of
offenses reported in VI-l below.

However, there were no violent crime (assault) in Criminal Law and only 6.7 % of

violent crime (aggravated assault) in Special Law among the criminal women subjects.

 

7 According to Korean Training Institute for Criminal Justice, Criminal Law in south Korea consist with
two categories: Criminal Law and Special Law. Therefore, as shown Table VI-l below, the comparison
between the two groups in their offense patterns were regrouped into two categories; offenses against
Criminal Law and offenses against Special Law.

35

Table VI-l. Percent Distribution of Offense Patterns in Female Crime

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Offense Female Offenders Criminal Women Criminal
Total Population Sample (%) Women Sample
( °/o )* ( #)
Criminal Law
Fraud 52.0 67.1 49
Adultery“ 8.5 1 3 .7 10
Gambling 7.0 1.3 1
Assault 6.7 0 0
Theft 5.0 6.8 5
Embezzlement 4.6 5.4 4
Counterfeit 2.2 5.4 4
Others 0 0 0
Total 100 100 73
Special Law
Food Sanitary Law 27.4 16.7 5
Aggravated Assault 22.9 6.7 2
Traffic Accident 13.5 6.7 2
Dishonored Check 10.5 60 18
Drug not reported 10 3
Others 25.7 0 0
10331 100 100 30

 

 

 

 

 

# Source: Adapted from Korea Training Institute for Criminal Justice, Criminal Statistics, 1995: 351-352

 

' There is adultery regulating law in Korea aimed sexual morality. According to adultery regulation law,
adultery refers to an extramarital sexual relationship in a sociological sense, that is, a voluntary relationship
which may threaten the existing marital relationship. Thus, a coerced or forced sex (rape) and a
commodified sex (prostitution) are excluded from this concept of adultery (Research Institute For
Criminology, 1991:168).

Research Institute For Criminology in Korea constructed a empirical research on people's attitude
on adultery. The study presented that 85 % of the respondents supported to keep adultery regulating law
while only 15 % of the respondents presented to abolish the law. As an important find, this study argued
the utilization of the adultery law: Even though the adultery law did not seem to be very effective in
practice, it have certain psychological effectiveness preventing the confusion of sexual morality and break-
up of a family in the absence of other more effective control measures (Research Institute For Criminology
in Korea, 1991:171-172).

36

Indeed, a proportion of property crimes of the criminal women subjects including
fraud, embezzlement, theft, and counterfeit (84.7%) were higher than those of female

offenders total population (63.8% ) reported in Table VI-l above.

Table VI-2. The Comparison between the two Sample Groups in Age, Family Income,
and Education Level

 

Item Criminal Women Non-Criminal Total Sample
Women
mean st.d cases mean st.d cases mean st.d cases

 

 

 

Age 40.4 8.10 110 41.5 8.8 63 40.8 8.3 173
Income 6.0 1.72 110 5.07 1.81 63 5.65 1.80 173
Level9

 

Education 4.02 1.13 107 3.40 1.12 65 3.78 1.16 172
Level10

 

 

 

 

 

 

 

 

 

 

 

 

The present study basically assumes similar socioeconomic status between
criminal women subjects and non-criminal women subjects, because the major purpose of
the present study is to explore the differences between these two groups in their
individual economic situations beyond their similar socioeconomic status. Table VI-2
above shows there is homogeneity between criminal married women subjects and non-

criminal married women subjects in terms of their socioeconomic status such as age,

 

9 The variable of family‘s monthly income item is answered on 8-point scale of 0=no monthly income,
l=under 10man Won, 2=10man-30man Won, 3=30man-50man Won, 4=50man-70man Won, 5=70man-
100man Won, 6=100man-200man Won, 7=200man-300man Won, 8=more than 300man Won.
According to Korea Research Institution for Health (1994:32), the monthly minimum standard
cost of living for 4 family members is 661684man Won. The means of the two groups in this study indicate
that both of the two groups have higher monthly income than the minimum standard of living in Korea-
6=100man-200 man Won for criminal samples, 5.07= 70man-100man Won for non-crininal women
subjects.
’0 Women‘s education level item is answered on 6-point scale of l=no formal education, 2=elementary
school or drop, 3=middle school or drop, 4=high school or drop, 5=college completion or drop, and 6=
above university completion or university drop.

37

monthly income level, and education level. However, there are some mean differences
between the two groups in their age, income level, education level. It means the two

groups have exact same socio-economic conditions.

(2) Procedures

The data for this study was obtained fi'om 175 married women in Korea. The
survey questionnaire were distributed to 110 married incarcerated women and 25 married
factory laborers and 40 hospitalized married women and the wives of hospitalized men.
The survey questionnaire consisted of 40 questions for the criminal women while 35
questions exempted 5 items relating offense for non-criminal women. The questionnaire
was administrated to ask about the women’s economic situations, abusive experience by
their husbands, and several pertinent demographic variables. Two hundred questionnaires

were distributed and 175 were returned.

(3) Operationalization and Measures

22mm .

The instrument used to operationally define the variables were a self-report
personal data sheet to determine women's economic status, offense related characteristics,
and demographic features of the subjects, and Straus’ Conflict Tactics Scale (CTS) to
measure women‘s abusive history from their husbands, ex-husbands, or boy fiiends. The

measures composed of the three categories: (1) demographic variables for the subjects,

38

(2) women's economic situation measures, and (3) wife battering measures. The

variables that are used in the empirical analysis are:

Women's economic sittfltion meam

The focus of the analysis in the present study was the women’s economic situation
measures which were measured through the following items: (1) family monthly income
level, (2) women's contribution to family's financial needs, (3) Women's economic
burden of supporting family, (4) women's support network, (5) the extents of economic
problems in terms of relative and self-perceived poverty, and (6) family structure. The
scales of each items are the followings:

(1) Income levelll was measured in terms of the amount of monthly earning
ranging from 0 to over 3 million won.12 Original response categories of 9 categories were
regrouped into five categories ranged from 0 to 4 with 100 man Won interval.

(2) Women's contribution to family financial needs is measured how many %
of family's spending came from women's earning with eleven levels: from 0=0%,
1=10%, 2=20%, 3=30%, 4=40%, 5=50%, 6=60%, 7=70%, 8=80%, 9=90% 10=100%.
However original score was recorded into 6 categories: 0=0%, 1=1-20%, 2=21-40%,
3=41-60%, 4=61-80%, 5=81-100%.

(3) Women’s economic burden of supporting family was a summated scale of

2 items such as 1) main provider for a family resources with three levels: 0=husband

 

11 Poverty usually starts with the assumption of a specific poverty line in terms of income (Hagenaars and
De Vos, 1987:213). The present study measures incomes to determine whether a household is absolutely
r.
2 Won is Korean monetary unit. The exchange rate of dollar is 8 l= 890 won in the state of Jan. 1, 1997.
Thus, 300man ( 3 Million) Won is approximately 3 3,370.

39

provide for family resources, l=wife provide part of them, and 2=wife provide them, 2)
number of dependents with four levels: 0=no dependent, 1: one dependent, 2=two
dependents, 3fihIee dependents, 4=four dependents, 5=five dependents, and 6=more than
five dependents. However, when woman provide for family resources along with her
husband, the score divided by 2. Wife's economic burden of supporting family is on 12
point scale ranging from 0 to 12. A respondent who scored 0 on this scale had no
economic burden of supporting family. Whereas a score of 12 indicates that a respondent
had heavy burden of supporting family.

(4) Women's support networks was a summated scale of two items such as 1)
financial support with three levels: 0=never helped, 1= sometimes helped, and 2=often
helped and 2) emotional support with three levels: Omever helped, 1=sometimes helped,
and 2=often helped. The variable of wife‘s support network is on 4 point scale from 0
(respondent has very limited supporting network) to 4 (a respondent has sufficient
support network).

(5) The extents of economic problems consisted of three items such as 1)
housing situation with four levels: 0=lived in own house, 1=house which was rental by
yearly, 2=house which was rental by monthly, 3= lived in relative‘s house or social
facility, 2) self-evaluated economic status with four levels: 0=wealthy,l=somewhat
wealthy, 2=moderate, and 3=poor, 3) the extent of suffering from economic problems
with four levels: 0=no extent at all, 1=to small extent, 2%0 some extent, and 3%0 a great
extent. The variable of housing situation is measure of relative poverty while the variable

of self-evaluated economic status and the extent of suffering from economic problems is

40

measure of self-perceived poverty”. Thus, 9 points summated scale variable of extent of
economic problems consisted relative poverty and self-perceived poverty. A respondent
who scored 0 on this scale indicated that she had no economic problems at all, while
scored 9 on this scales indicated that she had serious economic problems. This variable
aims to measure poverty, specially relative poverty (housing situation) and self-perceived
poverty (self-evaluated economic status and the extent of suffering from economic
problems). And the variable consists relative poverty and self-perceived poverty.

(6) Family structure consisted two categories: female headed household, when a
women lived alone or a women lived with children without husband present and, male
headed household, when a woman lived with a spouse.

Table VI-4 below presents the measures of women's economic situations.

women (s batteregl experience mew

Battered experience was measured through the use of a modified Conflict Tactics
Scale (Straus and Gulles, 1990: 70). An summated score reflecting battered experience
was calculated for each of the proceeding categories of physical abuse by adding the
responses for the following modified CTS items: (1) threatened to hit or throw
something; (2) threw or smashed or hit or kicked something; (3) threw something at her;

(4) pushed, grabbed, or shoved her; (5) slapped her; (6) kicked, bit, or hit her with fist; (7)

 

'3 According to Hagenaars and De Vos, general definition of poverty are three categories; absolute

poverty, relative poverty, and self-perceived poverty. In this study, absolute poverty was measured by
family income, relative poverty was measured by housing situation, and self-perceived poverty was
measured by self-evaluated economic status and self-evaluated the extent of suffering from economic
problems. The variable of extent of economic problems was composed of relative poverty and self-

perceived poverty.

41

hit or tried to hit her with something; (8) beat her up; (9) choked her; (10) threatened her
with a knife or dangerous thing; and (12) personally forced her to have sexual relations.
Responses to each CTS items were collapsed into six levels: 0=never, l=once or twice a
year, 2=once or twice in half a year, 3=once or twice a month, 4=once or twice a week,
and 5= almost every day. The summated scale had a range from 0 (never happened any)
to 60 ( happened each almost every day). Table VI-5 below shows the measures of

women's battered experience.

Demographic measures

The nature of the subjects was investigated through the followings demographic
variables such as (1) age, (2) education level, (3) marital situation, (4) length of a married
life, (5) number of children, (6) women‘s and husband‘s job, (7) offense patterns, (8)
number of arrest, (9) length of incarceration, and (10) offense motivations.

(1) Age was coded as the real age in years.

(2) Education level was measured with six major categories ranging from no
formal education to university graduation or above.

(3) Marital situation consisted of five categories such as living together without
marriage, legally married and living together, living separately from the legal spouse,
divorced, and separated by death. This variable aims to determine family structure which
is one of economic variables in the present study. The original response categories were
regrouped into two categories; a female- headed household and a male-headed household.

A female-headed household presents married women with spouse absence in case of

42

divorces, separation from their husband while a male-headed household presents married
women with spouse present in case of living together without marriage or living together
with illegal husband.

(4) Length of a married life was coded as the real length of a married life in years.

(5) Number of children was measured as the real number of children including
stepchildren.

(6) Women's and Husband’s job had five categories: no job, temporary employed,
permanently employed, self-employed, and own business with employees.

(7) Offense patterns was measured by asking the types of offense.

(8) Length of incarceration was coded as the real length of incarceration for the
present offense.

(9) Offense motivations was measured by asking the real motivation of their offense.

In Table VI-3 below on summary of demographic variables, in Table VI-4 below
on summary of women's economic situation variables, and in Table VI-5 below on

summary of Wife Battering Variables are presented

43

Table VI-3. Summary of Demographic Measures

 

Items

Measures

 

Age

real age in years

 

Education Level

no formal education to university graduation or above

 

 

 

Marital Status 1=living together without marriage, 2=legally married
and living together, 3=living separately from the legal
spouse, 4=divorced, and 5=separated by death

Length of a Marriage Life real length of a marriage life in years

Number of Children real number of children including stepchildren

 

Women‘s and husband‘s

job

no job, temporary employed, permanently employed,

self-employed, own business

 

Offense Patterns

types of offense

 

Offense motivations

desire for more money, for supporting family,
financial gain for excitement, incident or curiosity,
jealousy or revenge, influence of alcohol or drug, and

others

 

 

Length of incarceration

 

real length of incarceration for the present offense

 

 

44

Table VI-4. Summary of Economic Situation Measures

 

 

 

 

 

 

 

 

 

 

 

Items Measures
Income Level ( 0 to 8) 1.amount of 0: no income to 8=over 300man
monthly Won
income
Women's Economic Burden of 1.main 0=husband, l=wife and husband,
Supporting Family provider of 2= wife
family
( summated 8 point scale ranging . spending
from 0 to 8) =0, 1=1, 2=2, 3= 3, 4:4, 5=5,
2. the number 6=more than 5 (when a woman
of dependent provide family along with her
family husband, the score divided by 2)
Women's Contribution to 0=0%, 1=1-20%, 2=21-40%,
Supporting Family Resource % of family's 3=41-60%, 4=61-80%, 5:81-
(5 point scale) spending 100%
came from
wife's earning
Women’s Support Network 1.financial 0=never,1=sometimes, 2=often
support
( summated 4 point scale ranging
from 0 to 4) 2.emotional 0=never,1=sometimes,2=often
support
Extent of Economic Problems 1=housing 0=own home, 1=rental by yearly,
situation 2=rental by monthly, 3=live in
(summated 9 point scale ranging relative's house or social facility
fi'om 0 to 9 )
2=self- 0=wealthy, 1=somewhat
evaluated wealthy, 2=moderate, 3=poor
economic
status
0m
3: the extent extent, 2=to some extent, 3=to a
of economic great extent
problem
Family Structure 1=female headed household,
2=male headed household

 

 

 

 

 

45

Table VI-5. Summary of Wife Battering Measures (CTS)

 

Items Measures

 

threaten to hit or throw something 0=never

 

The Extent of Wife threw or smashed or hit or kicked 1=once or twice a

 

 

 

 

 

 

 

something year
Battering threw something at her 2=once or twice
in half a year
(summated 60 point pushed, grabbed, or shoved her 3=once or twice a
scales ranging from slapped her month
0 to 60) kicked, bit, or hit her with fist 4=once or twice a
hit or tried to hit her with something week
beat her up 5=almost every
day
choked her

 

threatened her with knife or dangerous
thing

 

used knife or dangerous thing

 

forced sexual relations

 

 

 

 

 

(4) Limitations of the Reliability and Validity of the Present Study
Before discussing the results of the statistical tests, this study must be mentioned

methodological limitations. There are reliability and validity concerns.

46

With respect to reliability problem, some incarcerated women may forget their
economic situations and the battering experience prior to incarceration. In other words,
use of self-reports reduce reliability caused by memory errors. Indeed, offense related
items and battered experience items are sensitive questions, therefore, the respondents
may hesitate to answer these questions or they might choose the response which was
different from their actual situations.

Three types of validity threats are:

First, limited numbers of subjects (110 criminal women and 65 non-criminal
women) causes problems in statistical conclusion validity. Specially, 65 non-criminal
women may not enough to represent to lower socioeconomic class married women in
south Korea.

Second, this study can only generalize to non-serious property female offenders.
A majority of the criminal subjects are property offenders (84.7%) while the percent of
serious violent offenders (aggravated Assault) is very small (2%) (See page 36, Table VI-
1). Furthermore, this study can only generalize married female offenders, because single
female offenders were not included in the sample. Therefore, external validity of this
study is limited.

Finally, the present study may have several internal validity problems related to
the micro- model of analysis. First, the present study focuses on the individual measures
of married women's crime using self- report data. Because of them, this study ignores
other effects on married women's crime such as cultural and historical values, the recent

economic recession in south Korea, age, and community size. The second internal

47

validity problem relates to the theoretical approach of the study. This study focuses on the
women’s economic situations as causes of married women's crime in south Korea. Thus,
the present study ignores other potential causes of married women's crime other than
women's poor economic situation factors. The economic approach ignores the individual
factors such as individual personality, psychological aspects, and so on. This is an
oversirnplification of a very complex problem in that the theory does not explain why
some women commit crime but others do not commit crime, even though they are in
similar economic situations. In detail, to some extent, some female inmates’ personal
characteristics in terms of laziness, low self-control, and impulsivity may affect their
criminal activities. In short, with respect to interval validity deficiencies, this study need
to be combined with official measures of macro-model analysis of married women's

crime and other individual measures of women’s crime in addition to economic variables.

CHAPTER VII

FINDINGS

The emphasis of this chapter is the statistical analyses of the data described in the
preceding Chapter and the statistical tests of the hypotheses stated in Chapter V
concerning the effects of women's economic situations on married women's crime and
controlling effect of spouse abuse on the relationship between women's economic
situations and married women's crime.

(1) The demographic features of the subjects

To understand the nature of the subjects, the following demographic variables
were described. The findings of these variables will be mentioned again, if these variables
are helpful to explain the results of the hypotheses of the present study. Tables VII-1,
VII-2, VII-3, VII-4, VII-5, VII-6, and VII-7 below show the comparison between the two
groups in the demographic variables of this study, and Table VII-8 below shows offense

motivations in the criminal women subjects.

Table VII-1. Length of a Married Life, and Number of Children

 

Item Criminal Women Non-Criminal Women Sample Total
mean st.d cases mean st.d cases mean st.d cases

 

 

Length of a 15.94 9.12 106 16.31 10.40 64 16.08 9.6 170
married life 0

 

 

Number of 1.90 0.92 107 2.1 1.3 62 1.9 1.1 169
children

 

 

 

 

 

 

 

 

 

 

 

43

49

Table VII-1 above shows that there are no significant differences between the
criminal women and the non-criminal women in their length of marriage and number of
children. The mean of length of marriage (16.08) relates to the mean of ages of the
subjects (40.8).

Table VII-2. Frequency Distribution of Marital Situations

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Criminal Women Non-Criminal Sample Total
Women
cases % cases % cases %
Living Together 7 6.4 20 30.8 27 15.4
Without Marriage
Living Together with 58 52.7 32 49.2 90 51.4
Legal Husband
Living Separated 17 15.5 2 3.1 19 10.9
from Legal Husband
Divorced 24 21.8 4 6.2 28 16.0
Separated by Death 4 3.6 7 10.8 11 6.3
Total 110 100 65 100 175 100
Table VII-3. Family Structure

Criminal Women Non-Criminal Sample Total

Subject Women Subjects

cases % cases % cases %
Female Headed 46 41.8 13 20.0 59 33.7
Household
Male Headed 64 59.2 52 80.0 116 66.3
Household
Total 110 100 65 100 175 100

 

 

 

 

 

 

 

 

 

 

50

Table VII-2 above on marital situations shows that the divorce and separation rate
for the criminal women subjects are higher than those of the non-criminal women
subjects. The data indicate that the criminal women subjects are in unstable marital
situations rather than the non-criminal women subjects. The five categories of marital
situations reported in Table VII-2 were regrouped into two categories; female-headed
household and male-headed household as shown in Table VII-3 above. The subjects with
spouses absence are female-headed households while the subjects with spouses present
are male-headed households in Table VII-3 above. As shown Table VII-3, a proportion of
female-headed households for criminal women (41.8%) is higher than those of non-
criminal women (20%).

Table VII-4 below present a primary information on the subjects' family
environment. The criminal women subjects reside in more unstable family environment
than the non-criminal women subjects. For example, the percent of the criminal women
with husband absent and lived with children is 22.7 % compared to those of the non-
crirninal women of 9.2%. While, the percent of criminal women lived with husband and
their children which is a typical family model in south Korea is only 29.1% compared to

those of the non-criminal women subjects of 55.4%.

51

Table VII-4. Persons who Lived With the Subjects

 

 

 

 

 

 

 

 

 

 

 

 

 

Criminal Women Non-Criminal Sample Total
Women

cases (#) % cases (#) % cases (#) %
(1) Husband 16 14.5 2 3.1 18 10.3
(2) Children 25 22.7 6 9.2 31 17.7
(3) Women's family 7 6.4 1 1.5 8 4.6
(4)Husband‘s family 0 0 1 1.5 1 0.6
(5)Friend or relative l 0.9 0 O l 0.6
(6)Lived alone 15 13.6 6 9.2 21 12.4
(7)= (1)+(2) 32 29.1 36 55.4 68 38.9
(8)=(7)+(3), (7)+(4) 10 9.1 1 1 16.9 21 12.0
Not reported 4 3.6 2 3.1 6 3.4
Total 110 100 65 100 175 100

 

 

 

 

 

 

 

The purpose of Table VII-5 below is to show whether women have the economic
burden of supporting their children, when women are divorced or separated from their
husbands. Table VII-5 shows that a high proportion of women with spouses absence
became the main providers of their children in both of the two groups. However, the data
indicate that the percent of single parents for criminal women (52.6%) is higher than
those of non-criminal women (46.1%). Therefore, criminal women have higher economic

burden of supporting their children than non-criminal women.

 

52

Table VII-5. Persons Who Lived with Women with Spouse Absent

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Criminal Women Non-Criminal
Women
cases % cases %
Children 23 52.2 6 46.1
Women's Family 5 11.3 1 7.1
Spouse's Family 0 0 1 7.1
Friend or Relative 1 0.2 0 0
Lived alone 15 34.1 5 38.5
Total 44 100 13 100
Table VII-6. Women's Jobs
Criminal Women Non-criminal Sample Total
Women
cases % cases % cases %
No job 40 36.4 19 29.2 59 33.7
Temporary 3 2.7 7 10.8 10 5.7
Employed
Permanently 15 13.6 30 46.2 45 25.7
Employed
Self-employed 32 29.1 5 7.7 37 21 .1
Own Business with 6 5.5 0 0 6 3.4
Employees
Not-reported 14 12.7 4 6.2 1 8 10.3
Total 1 10 100 65 100 175 100

 

 

 

53

Table VII-6 above shows that criminal women are less likely employed. Indeed, a
majority of criminal women are merchants (self-employed)l4 which lacks job security.
Therefore, the higher proportion of the criminal women subjects have no jobs or insecure
jobs.

Table VII-7. Husbands' Jobs

 

 

 

 

 

 

 

 

 

 

Criminal Women Non-Criminal Sample Total
Women

cases % cases % cases %
No job 4 3.6 3 4.6 7 4.0
Temporary 2 1.8 2 3.1 4 2.3
Employed
Permanently 22 2.0 23 35.4 45 25.7
Employed
Self-employed 34 30.9 8 12.3 42 24.0
Own Business with 9 8.2 2 3.1 11 6.3
Employees
Not reported 39 35.5 27 41.6 66 37.8
Total ‘ 110 100 65 100 175 100

 

 

 

 

 

 

 

The comparison between the two groups in their husbands' job reported in Table
VII-7 above shows that the husbands of the criminal women subjects have less stable
jobs, because a majority of them are self-employed merchants while a majority of the
husbands of the non-criminal women subjects are permanently employed who usually

have job security.

 

" In south Korea, even though self-employed merchants have higher income, mostly they do not have job
security, because their business are easily influenced by the market conditions or business fluctuation.

 

54

Table VII-8. Motivations of Offense

 

 

 

 

 

 

 

 

 

 

 

 

cases %

Desire for more money 16 14.5
Financial gain for supporting family 31 28.2
For financial gain for excitement 0 0

Incident or curiosity 2 1.8
Jealousy or revenge 1 0.9
Influenced by other person 7 6.4
Influence of alcohol or drug 3 2.7
Others 38 34.5
Not reported 12 10.9
Total 110 100

 

 

 

Table VII-8 above presents offense motivations of the criminal women subjects.
As shown Table VII-8, a majority (42.7%) of the criminal women committed crime
aimed at financial gain. Specifically, 28.2 % of the criminal women committed crime to
support their family. Thus, it is assumed that women committed crime in insecure

financial situations.

(2) Summary of Women's Economic Situation Measures
Table VII-9 below shows the result of economic situation items. As mentioned

above, there are six economic situation variables as the hypothesized independent

 

55

variables; monthly income in terms of absolute poverty, women's contribution to family
financial resources, women's economic burden of supporting their family, women‘s
support network, self-evaluated economic problems in terms of relative poverty and self-
perceived poverty, and family structure. The variable of family structure was presented in

Table VII-3 above (see page 49).

Table VII-9. Summary of Economic Variables

 

 

 

 

 

 

Items Criminal Non-Criminal Sample Total
Women Women
mean st.d mean st.d mean st.d
Monthly Income 6.0 1.72 5.07 1.81 5.65 1.80
(ranged 0-9)
Main Provider of 1.13 0.76 0.75 0.79 0.99 0.79
Farrrily Resources
(ranged 0-2)
Number of 1.78 1.07 1.20 1.03 1.56 1.09
Dependents
(ranged 0-6)
Women's Financial 5.05 3.34 3.81 3.50 4.59 3.44
Contribution (% of
family's spending

came from women's
earning ranged 0-10)
Financial Support 0.42 0.56 0.45 0.59 0.43 0.57
(ranged 0-2)
Emotional Support 0.93 0.79 0.70 0.69 0.84 0.76
(ranged 0-2)

 

 

 

 

Housing Situation 1.00 1.04 0.69 0.86 0.88 0.98
(ranged 0—3)

Self-Evaluated 2.07 0.76 2.23 0.66 2.13 0.67
Economic Status

(ranged 0-3)

 

Extent of Economic 1.49 .95 1.21 0.87 1.34 0.92
Problems (ranged 0-3)

 

 

 

 

 

 

 

 

 

56

Thus, Table VII-9 above presents women's economic situation variables except
family structure. These data will be discussed with testing the hypotheses of the present
study. The relationships, and if related, and the strength of the association between each

economic situation variables and married women's crime will be tested later.

(3) Summary of Wife Battering Measures

Table VII-10 below shows the comparison between the criminal women subjects
and non-criminal women subjects in each items of wife battering measures. The
hypothesized original relationships between each economic variables and married
women‘s crime will be controlled by wife battering in order to examine whether battered

situations increase married women’s crime.

57

Table VII-10. Summary of Extent of Wife Battering

 

Item (each items ranged Criminal Women Non-Criminal Sample Total

 

 

 

score 0-5) Women

mean st.d mean st.d mean st.d
Threatened to hit 0.93 1.31 0.70 1.04 0.85 1.22
Threw, smash, or hit 0.88 1.38 0.69 1.04 0.81 1.27
something

 

Threw something at her 0.84 1.31 0.58 1.05 0.75 1.22

 

Pushed, grabbed, or shoved 0.76 1.33 0.57 1.07 0.69 1.25

her

 

Slapped her 0.57 1.04 0.50 1.03 0.54 1.03

 

Kicked, bit, or hit with fist 0.58 1.15 0.50 0.99 0.55 1.09

 

 

 

 

 

 

Hit, tried to hit with 0.69 1.24 0.47 0.87 0.62 1.13
something

Beat her up 0.52 1.19 0.21 0.66 0.41 1.04
Choked her 0.25 0.75 0.15 0.50 0.21 0.67
Threatened with knife 0.28 0.84 0.06 0.32 0.20 0.71
Used knife 0.30 0.85 0.23 0.87 0.27 0.85
Forced sexual relations 0.51 1.04 0.49 1.14 0.50 1.08

 

Total 6.35 10.68 4.93 9.11 5.86 10.15

 

 

 

 

 

 

 

 

 

58

(4) The Major Empirical Finding

Major Hypothesis : There is a relationship between m_arried women'Js economic
situations and married women's crime.

Before examining each hypothesis on the relationships between each economic
situation variables and married women's crime, correlation coefficients using bivariate
correlation reported in Table VII-11 below and logistic regressions reported in Table
VII-12 below were conducted.

In order to determine if each economic variables are related to married women‘s
crime, depending on the level of measurement for each economic variables, t-tests or
crosstabulations along with logistic regression reported in Table VII-12 below were
conducted.

The correlation coefficients reported in Table VII-11 below provides a
preliminary exploration of the effects of women‘s economic situations on married
women‘s crime. As shown Table VII-11, the effects of some of the bivariate correlation
(Pearson‘s r) of economic situation variables on married women‘s crime are negligible,
but some are not. Correlation between committing crime and the variables of economic
problems and support network were not significant. On the other hand, correlation
between committing crime and family's monthly income, women’s contribution to
family's financial resources, women's economic burden, and family structure variables
are significant ( p< .05). Even though these four variables are significantly related to the
crime variable, the strength of the relationships are weak using Person's r of the four

variables were less than 0.5.

59

Table VII- 11. Correlation Coefficient Between Women's Economic Variables and
Crime Variable (N=175: Two-Tailed Significance Tests in Parentheses)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Income F inanc- Econo- Econo- Support F amily- Crime
ial Burden Proble Net- Struc-
Contri- ms- work ture
bufion
Monthly Income 1 .000 .007 -.006 - . 478 .157 . 101 .267
( . ) ( . 920) ( .937) ( .000)* ( .043)* ( .185) (.000)*
Financial .007 1.000 .746 .130 - .091 - .293 .169
Contribution ( .920) ( . ) ( .000)* ( .089) ( .243) ( .000)* ( .027)*
Women's - .000 .731 1.000 .151 - .185 -.405 .247
Economic Burden ( .997) ( .000)* ( . ) ( .047)* ( .017)* ( .000)* ( .001)*
Econo-Problems -.432 .147 .151 1 .000 - .375 - .261 .084
( .000)* ( .055) ( .047)* ( . ) ( .000)* ( .000)* ( .266)
Support-Network .138 - .088 - .185 - .375 1.000 .121 .054
( .075) ( .262) ( .017)* ( .000)* ( .000)* ( .120) ( .487)
Family Structure .142 - .327 - .405 - .261 .121 1.000 - .233
( .062) ( .000)* ( .000)* ( .000)* ( .120) ( . ) ( .003)*
Committing .267 .174 .247 .084 .054 -.233 1 .000
Crime ( .000)* ( .023)* ( .001)* ( .266) ( .487) ( .003)!!! ( . )

 

* p < .05 (Two-Tailed Test)

Regression coefficients reported in Table VII-12 below is the outcome of a

equation where the crime variable is the dependent variable and the economic situation

variables are the independent variables. Since the dependent variable of crime variable is

a dichotomous variable coded 0 for non-criminal women and 1 for criminal women, the

coefficients for them were obtained from logistic regression.

 

60

Table VII-12. Regression Coefficients for the Effects of Economic Situation Variables
on Crime (N=175; Two-Tailed Significance Tests in Parentheses)

 

 

 

 

 

 

 

B df Sig R
Family's Monthly Income .5596 l (. 0006)* .2053
Women's Financial Contribution .2036 1 (. 0283)* .1167
Women’s Economic Burden .3051 1 (. 0015)at .1888
Women's Support Network .1016 l (. 4847) .0000
Economic Problems .0912 1 (. 2652) .0000
Family Structure - 1.056 1 ( . 0039)* - .1659

 

 

 

 

 

 

 

* p < .05 (Two-Tailed Test)

As shown Table VII-12, regression analyses revealed that family's monthly
income, women's contribution to family's financial resources, women's economic burden
of supporting their family, and family structure are statistically related to married
women's crime. This data will be discussed again, when each hypothesis is examined.

As shown Table VII-12, regression analyses also indicated that women's
economic burden of supporting family and family’s monthly income contributed more
unique variance to married women's crime than women's economic contribution to
family resources and family structure (R for women’s economic burden= .1888, R for
family's monthly income= .2322, R for family structure= -. 1659, and R for women's
financial contribution= .1167). Again, family's monthly income accounted for 23%
unique variance and women's economic burden accounted for approximately 18% unique

variance. Whereas family structure accounted for 16% unique variance to married

61

women's crime and women’s economic contribution accounted for 11% unique variance
to married women's crime. Therefore, the R values of the logistic regressions show that

monthly income appears to have had the greatest influence on married women's crime

(See Table VII-12 above).

Sub-Hypothesis One: Criminal mg’ed women are more likely than non-

 

criminal married women to have lower monthly income (negative relationship).

The rational for this hypothesis stems from the theoretical model that criminal
women may commit crime due to poverty (Messerschmidt, 1987; Box, 1983; Carlen,
1988). Usually, income plays an important role in detennining whether a household is
poor which is under a specific poverty line in terms of income (Hagenaars and De Vos,
1991:212-213). Thus, in order to examine the effect of poverty on committing crime,
monthly income was used as a independent variable.

As shown Table VII-12 above, regression coefficient for monthly income ( .0001)
indicates that family's monthly income significantly relates to married women's crime
(p< .05). Further, the R value of .2322 indicates that the strength of the relationship
between income level and married women's crime is somewhat weak.

However, unexpected direction of R ( .23 22) indicates that criminal women are
more likely than non-criminal women to have higher income. Thus, the result of the
statistical analysis does not support the original hypothesis that criminal women are less

likely to have higher income than non-criminal women.

62

In order to examine the relationship between family's monthly income and
married women's crime crosstabulation using chi square was also conducted. In Table
VII-13 below, family's monthly income is presented in the columns and crime variable is
shown in the rows. As shown Table VII-13 below, a chi square of 15.17 (Significance=
.0043) is significant at the .05 level. The Gamma is .414 and shows that about 41 % of
the variation in married women's crime is explained by the family's monthly income.
This represents a moderate relationship between income and married women's crime.

An important thing of the results relating monthly income is unexpected direction
of the association between income and married women's crime. The positive value of
Gamma shows that criminal women are more likely than non-criminal women to have
highly monthly income. The sub-hypothesis one states criminal women are less likely to
have higher monthly income than do non-criminal women.

In summation, even though the statistical analyses using both R value at the
logistic regression coefficient and chi square at the crosstabulation presents that family's
monthly income and married women's crime are statistically related to each other, it does
not indicates that women with higher income are more likely than women in lower
income to commit crime. Again the statistical results can not claim that as monthly
income increased, married women's crime increased. Therefore, the statistical data does
not support the hypothesis that criminal married women are less likely than non-criminal
married women to have higher monthly income. However, the data revealed that absolute

poverty does not cause married women's crime.

63

Table VII-13. Married Women's Crime and Monthly Income

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

No income 1-100 Man 101-200 201-300 Over 300 Tot-
Won Man Won Man Won Man Won al
N % N % N % N % N % N
Criminal 3 2.8 28 25.7 33 30.3 24 22.0 21 19.3 109
Non- 2 3.1 29 44.6 25 38.5 5 7.7 4 6.2 65
criminal
Total 5 2.9 57 32.8 58 33.3 29 16.7 25 14.4 174
12 = 15.17, P ( .0043) < .05, Gamma= .414

 

 

Sub-Hypothesis Two: Mal med women are more $er than non-
criminal married women to contribute to their family's financial needs.

The rationale for this hypothesis is that south Korean women whose husbands
provide enough money for their family are tend to stay at home without earning money
than women whose husbands do not provide enough money. Thus, it is assumed that in
south Korea, women who contribute to a high proportion of family's financial resources
due to insufficient supports or no supports from their husbands may commit crime to
solve their financial difficulties, when they have no suitable alternatives to illegal
activities.

In order to test this hypothesis, the logistic regression reported in Table VII-12
above (see page 60) and t-test reported in Table VII-14 below were conducted.

As shown Table VII-12 above ( see page 60), the logistic regression coefficient (
.0283) indicates that women's contribution to their family's financial needs statistically

relates to married women‘s crime (p< .05). However, the relationship is somewhat weak

54

and positive based on the R (R= .1118), because women's economic contribution can
explain approximately 11% unique variance attributed to married women's crime. Thus,
as women's economic contribution to their family's financial needs in general increased,
married women's crime increased.

In order to examine the relationship between women’s contribution to family's
financial needs and married women’s crime, two-independent t-test was conducted In
Table VII-14 below, the t-value of 2.23 (T Significance = .027) is significant at the two
tailed t-test. Therefore, the relationship between women's economic contribution to
family resources and married women's crime are statistically significant (p< .05). In
detail, criminal women are more likely than non-criminal women to financially support

their family.

Table VII-14. T-Test for Women's Financial Contribution and Married Women's Crime

 

 

 

Range of scores Mean Number of Cases
Criminal Women 0-5 2.740 108
Non-Criminal 0-5 2.127 63
Women

 

 

 

 

 

 

F=1 .619 P= .205 t-value=2.23 df=169 Two-Tail Significance: .027

 

In sum, the result of analyzing the data using multiple logistic regression reported
in Table VII-12 above (see page 60) and the two independent two tailed t-test reported in
Table VII-14 below present strong support for the hypothesis that the extent of women's

contribution to their family's financial needs causes married women's crime. Briefly,

65

women who support a high proportion of family's financial resources are more likely to

commit crime than women who support a low proportion of family's financial resources.

Sub-Hypothesis Three: Criminal manied women are more likely than non-

criminal manied women to hpve economic burden of supporting their family.

The rationale for this hypothesis is when women have higher economic burden of
supporting their family because they are main providers for the family and have many
dependent farrrily, they may be engage in illegal activities to make money as alternatives
to employment which are limited for manied women in Korea.

In order to test this hypothesis, the logistic regression reported in Table VII-12
above and t-test reported in Table VII-15 below were conducted.

As shown Table VII-12 above (see page 60) of the logistic regression equation
(p< .05) indicates that the economic burden facing married women to support family
significantly relates to married women's crime. However, the relationship is somewhat
weak based on the R value (R= .1888), because R value of - .1888 explains only 19
percent of the variation observed. Again, the variable of women's economic burden of
supporting their family can explain approximately 19% unique variance to married
women's crime. Therefore, the logistic regression for the effect of women's economic
burden of supporting their family on women's criminal activities revealed that women's
economic burden of supporting their family and married women’s crime are significantly

related to each other. However, the strength of the association is weak and the direction is

66

positive. Thus, as women's economic burden of supporting their family for a cause of
committing crime increased, married women’s crime increased.

Two-independents t-test was also conducted to test the relationship between
women’s economic burden of supporting their family and married women's crime. In
Table VII-15 below, the t-value of 3.34 ( T Significance: .001) is statistically significant
beyond .05 level. Criminal are more likely than non-criminal women to have economic
burden of supporting their family, because the mean of criminal women (2.922) is higher
than those of non-criminal women (2.039) reported in Table VII-15.

In sum, the result of statistical analyses using logistic regression and t-test, on the
effect of women's economic burden of supporting their family on married women's
crime, provided strong supports for the hypothesis that criminal women are more likely
than non-criminal women to have the economic burden of supporting their family. In
detail, women who are main providers for family's resources and have many dependent
family are more likely to commit crime than women who are not main providers for

family's resources or small number of dependents.

Table VII-15. T-Test for Women's Economic Burden and Married Women's Crime

 

 

 

Range of Mean Number of cases
scores
Criminal Women 0 - 8 2.922 109
Non-Criminal Women 0 - 8 2.039 64

 

 

 

 

 

 

F=3.881 P= .050 t-value=3.34 df=17l Two-Tail Significance= .001

 

67

Sub-Hypothesis Four: Criminal women Jere less likely than non-criminal women

 

to have supmrt network. (negative relationship)

According to Box, the rationale of this hypothesis is that the major factor of the
increase in property offenses is due to economic marginalization for women, largely
through unemployment and inadequate compensatory levels of welfare benefits (Box,
1983:199). Unlike Britain or US, a proportion of single mother households which
receive public aids is less than .01 % among total households in 1991 in Korea (Korean
Women's Development Institute, 1995: 70, 278). Thus, it is not meaningful to discuss the
levels of welfare benefits as a women's support network in Korea. From this reason,
instead of welfare benefits, financial and emotional supports outside the home were
examined in the present study, in order to test whether women's support networks affect
committing crime for married women.

The logistic regression reported in Table VII-12 above (see page 60) and t-test
reported in Table VII-16 below were conducted to test this hypothesis.

As shown Table VII-12 above of the logistic regression equation, the Significant
for women's support network ( .484) indicates that the variable of women's emotional and
financial support networks does not statistically relate to married women's crime (p> .05).
Also, the R value of .0000 for a equation shown in Table VII-12 indicates that women's
support networks is not a contributor to married women's crime.

However, the positive value of B ( .1016) is in unexpected direction. The sub-
hypothesis four states criminal women are less likely to have support network than non-

criminal women. In the observed relationship, however, criminal women have more

68

support networks than non-criminal women. The finding of the logistic regression for the
effect of women's support network on their criminal activities does not support the
hypothesis that criminal women are less likely than non-criminal women to have support

network.

Table VII-16. T-Test for Women's Support Network and Married Women's Crime

 

 

 

 

Range of scores Mean SD Number of Cases
Criminal Women 0 - 4 1.257 1.127 105
Non-Criminal Women 0 - 4 1.131 1.118 61

 

 

 

 

 

 

F= 0.012 P= .951 t-value=0.70 df=l64 Two-Tail Significance== .487

 

In Table VII-16, the t-value of 0.70 ( T Significance= .484) is not significant (p>
.05). The two-tail significant indicates that the relationship between women's support
network and married women's crime are not statistically related to each other. The effect
of women's support networks fail to show significant effects on married women's crime.

In summation, the result of statistical analyses shown in Table VII-12 (seepage
60) above of the logistic regression and Table VII-16 of two-independents t-test do not
provide supports for the hypothesis that the extent of women’s support networks relates
to married women's crime. However, the direction of the association in the regression
coefficient (Table VII-12 above) and mean difference in the t-test (see Table VII-16 )

present that rather criminal women have higher support networks than non-criminal

69

women. Briefly, women's support network as a cause of committing crime for married

women does not seem to lead to married women's criminal acts.

Sub-Hypothesis Five: m1 women pre more lil_<ely than non-criminal women
mve economic problems (positive relationship)

The rationale for this hypothesis is that poverty may lead to women’s crime to
make money. Again, the variable of economic problems composed of relative poverty
measured by housing situation and self-perceived poverty measured by self-evaluated
economic status and self-evaluated extent of suffering from economic problems
(Hagenaars and De Vos, 1987: 212). The present study assumes, when women is having
less than others in terms of their own home, or they are feeling they do not have enough
to get along, they may engage in illegal activities to make money.

In order to test the hypothesis on the relationship between extent of economic
problems and married women's crime, the logistic regression coefficient reported in
Table VII-12 above (see page 60) and t-test reported in Table VII-17 below were
conducted.

As shown Table VII-12 above of the logistic regression equation, the Significant
of .265 indicates that the extent of economic problems facing women does not
significantly relates to married women's crime (p> .05). Also, the R value of .0000 for a
equation shown in Table VII-12 presents that extent of women's economic problems is
not a contributor to married women's crime. Thus, the finding of the logistic regression

for the effect of women's economic problems on married women’s criminal acts does not

70

support the hypothesis that criminal women are more likely than non-criminal women to
have economic problems.

The result of two-independents t-test shown Table VII-17 below coincide with the
finding of the logistic regression for the effect of women's economic problems on married
women’s crime reported in Table VII-12 above. In Table VII-17, the t-value of 1.12 is not
significant ( T Significance= .266) with two-tailed test. The two-tail significant indicates
that the relationship between women's economic problems and married women's crime
are not statistically related to each other. Thus, the effect of women's economic problems
fail to show significant effects on married women's crime. However, the comparison
between criminal women and non-criminal women in their means shows that criminal

women have more economic problems than non-criminal women.

Table VII-17. T-Test for Women's Economic Problems and Married Women's Crime

 

Range of Scores Mean SD Number of Cases

 

Criminal Women 0 -9 4.463 2.021 110

 

 

Non-Criminal Women 0 -9 4.123 1.824 65

 

 

 

 

 

 

F= 2.267 P= .134 t-value=1.12 df=173 Two-Tail Significance= .266

 

In sum, the result of statistical analyses shown in Table VII-12 above of logistic
regression coefficient (see page 60) and Table VII-17 of two-independents t-test do not
provide supports for the hypothesis that the extent of women's economic problems relates

to married women's crime. Briefly, economic problems which was measured with three

71

items; housing situation, self-evaluated economic status, and extent of suffering from
economic problems does not significant affect married women's crime. However, the
direction of the association in the regression coefficient using positive value of R (see
Table VII-12 above) and higher mean for the criminal women subjects using the t-test
(see Table VII-17) present that the criminal women subjects have higher economic

problems than the non-criminal women subjects.

Sub-Hypothesis six: Criminal married women are less 1&er than non-criminal married
women to reside in male headed hou_seholds. (negative relationship).

According to the previous research ( Rafter, 1990; Bloom and Steinhart, 1993;
Lewis, 1982; Hagan, Gills and Simpson, 1985) the rationale for this hypothesis is that the
increasing numbers of female-headed households supporting dependent children or
themselves, lead to married women’s crime as supplements or alternatives to employment
(Bloom et.at, 1995:9). The two situations- the increased burden of household
responsibility for married women combined with limited job opportunities for women-
are main keys which can lead to married women's crime (Milkman, 1993:300).

In order to test this hypothesis, statistical analyses with a logistic regression
reported in Table VII-12 above (see page 60) and crosstabulation using Chi-square shown
Table VII-18 below were conducted.

As shown Table VII-12 above, the logistic regression coefficient for family
structure ( .0039) indicates that family structure significantly relates to married women's

crime (p< .05). However, the relationship is somewhat weak based on R (R= - .1659),

72

because family structure can explain approximately only 16 % unique variance to married
women’s crime. The negative value of R also indicates that criminal women are less
likely than non-criminal women to reside in male-headed households. Thus, women who
are in female headed households are more likely than women who are in male-headed

households to engage in criminal activities.

Table VII-18. Family Structure and Married Women’s Crime

 

 

 

 

 

F emale-headed Male-head Total
Households Households
N (%) N (%) N
Criminal Women 46 41.8 64 58.2 1 10
Non-Criminal Women 13 20.0 52 80.0 65
Total 59 33.7 116 66.3 175

 

 

 

 

 

 

 

 

x2=8.70, Gamma= -.484, p ( .0031)< .05

 

Chi-square value was also used to examine the relationship between family
structure and married women's crime reported in Table VII-18. Table VII-18 reveals the
relationship between female-headed households and male-headed households in the
columns, with criminal or non-criminal in the rows. The findings in Table VII-18
indicates women with female-headed households are more likely than women with male-
headed households to commit crime, because Chi-square of 8.70 is statistically significant
(Significance= .0031) at the .05 level. A Gamma value of - .483 shows that the strength

of the relationship between the two variables are moderate, because the independent

73

variable of family structure explains about 48 percent of the variation in the dependent
variable of married women's crime observed in Table VII-18 above. The negative value
of Gamma also indicates that criminal women are less likely than non-criminal women to
reside in male-headed households.

In sum, the statistical analyses reported in Table VII-12 above and Table VII-18
above support hypothesis six that criminal women are less likely than non-criminal
women to be in male-headed households. The results exanrined in this study presented
that married women with husbands absence are more likely to engage in criminal
activities than married women with husbands present. The strength of association
between the two variables is weak to moderate using coefficient R (- .1659) and Gamma
value (-. 483). In this sense, the statistical result can claim that female headed households

increased in general, married women's crime increased.

Sub-Hypothesis Seven: Women who have been serious abused by their partners/ex-
partners are more likely than women who hpve not been serious abused by their

partners/ex-partners to commit crime regardless of their economic situations.

The purpose of this hypothesis whether the relationship between women's
economic situation variables and married women's crime are affected by wife battering.
According to previous research on wife battering, the rational of this hypothesis is that a

majority of female offenders expressed their abused experience by their husbands

74

(Grossman, 1985:5—6; Flowers, 1987: 81; Brett, 1993;26—27). Thus, it is assumed that
wife battering may positively relate to married women's crime.

Before examining the intervening effects of wife battering on the relationship
between women's economic situations and married women's crime, it is necessary to
determine whether there is a difference between criminal women and non-criminal
women in the extent of battered experience by their spouses. To accomplish this, two-
independent t-test was computed reported in Table VII-19.

The data in Table VII-19 shows that the effect of wife battering on married
women's crime is not significant (p> .05). The t-value of .78 is not large enough to
support significant difference between criminal women and non-criminal women in their

extent of wife battering.

Table VII-19. T-Test for Wife Battering and Married Women's Crime

 

 

 

 

Range of Mean SD Number of

scales cases
Criminal Women 0-60 6.35 10.68 91
Non-criminal Women 0-60 4.93 9.11 48

 

 

 

 

 

 

F=1.964, p=.134, t-value=.78, two-tail significance= .437, df=137

 

However, as shown in Table VII-19 above, the criminal women group has a
higher mean score (6.35) than those of non-criminal women group (4.97). From these
findings, even though the extent of wife battering is not statistically related to married '
women's crime, the direction of the relationship tentatively supports that criminal women

have more frequently experienced wife battering than non-criminal women.

75

To test the hypothesis seven that heavily abused women are more likely than
lightly abused women to commit crime regardless of women's economic situations, this
study computed multiple regression coefficients for the effect of women's economic
situation variables on married women's crime controlling for wife battering. Women's
economic situation variables were used as the independent variables, married women's
crime as a dependent variable, and the extent of wife battering as a control variable.The
Regression Coefficients in the Table VII-21 below, are separate regression equation. In
Table VII-21, the outcomes of a separated equation both bivariate logistic regressions and
partial logistic regressions (controlling for extent of wife battering) are presented.

However, to accomplish, it is necessary to examine whether women’s economic
situation variables relate to wife battering. Correlation coefficients among economic
variables, crime variable, and wife battering variable were examined to discover
preliminary information on the correlation among these variables. The results are reported
in Table VII-20 below.

As shown Table VII-20, women's contribution to family's financial resources,
women's economic burden of supporting farrrily, and family structure are statistically
related to wife battering (p<..05). At the same time, monthly income, women's support

network, and the extent of economic problems have no effects on wife battering.

76

Table VII-20. Correlation among Economic Situation Variables, Married Women's
Crime and wife battering (N=128; Two-Tailed Significance Tests in Parentheses)

 

 

 

 

 

 

 

 

 

 

Fami- Finan- Eco- Suppor Eco— Farni-ly Comm Batt-
ly cial nomic t nomic Structur itting ered
Inco- Contri Burd- Networ Proble e Crime Exper-
me bution en k ms ience
Family 1.000 .0066 .03 72 .1317 -.5003 .0481 .2201 -.0476
Income ( . ) (.941) (.674) (.135) (.000) (.587) (.012) (.591)
Financial .0066 1.000 .7685 -.0754 .1651 -.2263 .191 1 .2523
Contributi (.941) ( . ) (.000) (.394) (.061) (.010) (.029) (.004)
on
Economic .0372 .7685 1.000 -.1583 .1 134 -.3558 .2798 .2886
Burden (.674) (.000) (. ) (.072) (.199) (.000) (.001) (.001)
Support .1317 -.0754 -.1583 1.000 -.3446 .0867 .0055 -.l 187
Network (. 135) (.394) (.072) ( . ) (.000) (.327) (.951) (.178)
Economic -.5003 .1651 .1134 -.3446 1.000 -. 1692 .1136 .1296
Problem (.000) (.061) (.199) (.000) ( . ) (.054) (.198) (.142)
Family .0481 -.2263 -.3558 .0867 -.1692 1.000 -.2782 -.3252
Structure (.587) (.010) (.000) (.327) (.054) (. ) (.001) (.000)
Married .2201 .191 1 .2798 .0055 .1 136 -.2782 1.000 .0693
Women's (.012) (.029) , (.001) (.951) (.198) (. 001) (. ) (.433)
crime
Battered -.0476 .2523 .2886 -.1 187 .1296 -.3252 .0693 1.000
Experienc (.591) *(.004) *(.001) (.178) (.142) *(.000) (.433) (. )

C

 

 

 

 

 

 

 

 

 

* Two--Tailed Significance < .05 (between economic variables and wife battering)

 

77

Table VII-21. Regression Coefficients for the Effects of Economic Situation Variables
on Crime (before and after Controlling for Battered Experience N=175;
Two- Tailed Significance Tests in Parentheses)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Income Economic Women’s Support Econo- Family
Contribut- Economic Networks mic Structure
ion Burden Problems

before
B .5596 .2036 .3051 .1016 .0912 -l.0560
df l 1 1 1 1 1
Sig .0006* .0283 * .0015* .4847 .2652 .0039*
R -.2053 .1167 .1888 .0000 .0000 -.1659
after
B .4917 .23 86 .3415 .0657 .0903 -1.7541
df 1 1 1 1 1 1
Sig .0095* .0365* .0030* .6878 .3656 .0015*
R -.1628 .1186 .1965 .0000 .0000 -.2125

 

* two-tailed significance < .05

 

Bivariate logistic regression and partial logistic regression controlling for
battering experience are reported in Table VII-21 above. The results shows that the
original relationships between women's economic situation variables and married
women's crime did not disappear. No meaningful differences were found before and after
the elaboration by wife battering. In detail, regardless of the extent of wife battering, the

variables of family income, women's contribution to supporting their family's financial

78

resources, women's economic burden of supporting their family, and family structure are
significantly related to married women's crime. Again, women's support network and the
extent of economic problems are not statistically related to married women's crime. In
sum, women who have lower income, higher contribution to family's financial resources,
higher economic burden of supporting their family, and women with female-headed
households are more likely to commit crime than women who have higher income, lower
contribution to family’s financial resources, higher economic burden of supporting their
family, and women with male-headed households.

Even though, the statistical analyses have found no effects of wife battering on the
relationships between women's economic situation variables and married women's crime,
the strength of associations between each independent variables of women's economic
situation variables and the dependent variable of married women's crime were changed
before and after controlling for wife battering. In Table VII-21 above, Partial Regression
analyses indicates that the effects of monthly income and women’s contribution to
family's financial resources on married women's crime were decreased after controlling
for battered experience. At the same time, the effects of women's economic burden of
supporting their family and family structure on married women's crime were increased.
Whereas, women's support network and extent of economic problems both before and
after controlling for wife battering had no contribution to explain the variance of married
women's crime. Therefore, family structure appears to have had the greatest influence on

married women’s crime. Again, the findings show that family structure is an important

79

contributor to manied women's crime regardless of whether battered experiences are
accounted for.

In conclusion, some economic variables such as women's financial contribution to
their family, women's economic burden of supporting their family, and family structure
are statistically related to wife battering reported in Table VII-20 above (see page 76).
However, there is no direct effect of wife battering on married women's crime reported in
Table VII-19 above (see page 74). Indeed, as shown Table VII-21 above (see page 77) no
meaningful intervening effects of wife battering on the relationship between women's
economic situations and married women's crime were found in the present study.

Briefly, the statistical analyses reveals that the effects of women's financial
contribution to family’s need, women’s economic burden of supporting family, and
family structure both on married women's crime and on wife battering are significant.
However, there is no intervening effects of wife battering on the relationship between

women's economic situations and their criminal acts.

(5) Discussions

Summa o the F indin s

The previous research on the effects of women's economic situations on female
crime presented that women's insecure economic situations are the major causes of
female crime (Box, 1983, 1987; Carlen 1989; Milkman, 1993 ). These perspectives are
partly supported, when Women’s Economic Marginalization Theory was examined by the

present study using data from manied women in Korea. From these results, the present

80

study revealed that women's contribution to family's financial resources, women's
economic burden of supporting family, and family structure are significantly related to
married women's crime. On the other hand, women's support network, absolute poverty,
and relative poverty and self-perceived poverty fail to show significant effects on married
women's crime. Especially, this result showed that poverty was not related to married
women's crime.

With respect to the intervening effects of wife battering, the statistical tests
presented that wife battering did not affect the original causal relationships between
women's economic situation variables and married women's crime. Even though some
economic variables which had effects on women's criminal activities were significantly

related to wife battering, wife battering had no intervening effects.

The ResulA of Statisticgl Tests of the Presentfludy

Figure VII-1 below summarizes the results of empirical tests on the seven
hypotheses in the present study. As shown Figure VII-1, the results are something
different from the empirical framework of the present study reported in Figure V-l (see
page 30): First, some economic variables relate to married women's crime while some are
not. Second, some economic variables which have significant effects on married women's
crime are also related to wife battering. Third, there is no intervening effects of wife
battering on the original relationships between the economic variables and married

women's crime.

81

Figure VII-l. The Results of Empirical Tests of this Study

 

 

-Women’ 5 Financial Contribution\

 

-Women' 8 Economic Burden . Wife Battering

-Female-headed Households

 

 

 

 

 

 

 

 

 

- Absolute Poverty (Income) \ _.
- Support Networks

oooooooooooooooooooooo

Committing Crime

 

 

 

- Relative and Self-perceived Poverty /

 

 

 

 

—> Existence of Causal Relationship (all are significant at or below the .05 level)

------------- Absence of Causal Relationship (all are no meaningfiil effects)

Discussion (povem versus the women ’s burden ot household responsibilim

 

An important finding of the present study is that the effect of women's all forms
of poverty (absolute poverty and relative and self-perceived poverty) on married women's
crime is not significant. On the other hand, the increased burden of finding household
resources among female-headed households is a major cause of married women's crime.

From this point of view, the present study discusses the effect of poverty versus

the increased burden of household responsibility on married women's crime in south

82

Korea. To accomplish, this study has the two questions: Does married women’s poverty
have no effect on their committing crime? Why do the women with burden of household
responsibility engage in illegal activity and, what are the causes of the increased burden
of household responsibility for married women in Korea?

With respect to the first question on the effects of poverty on married women's
crime, according to criminologists within economic marginalization perspective argue
that the major cause of female crime is poverty (Box, 1883, Carlen, 1988). This
perspective was not supported by the results of statistical analyses in the current study.

As shown Table VII-22 below, the percent of monthly income under the
minimum standard cost for living in the criminal women (13%) is lower than those of the
non-criminal women (27 .8 %). According to Korean Research Institute for Health
(1994:32), the minimum standard cost for living15 for a four family member household
is 661,627. Thus, in order to know the proportion of the subjects under the poverty line
(under the minimum standard cost for living), the subj ects' family income are categorized
0 (no income) to 4 (50 Man-70 Man Won) as under the poverty line. This is reported in
Table VII-22 below. Table VII-22 shows percent distribution of monthly income under

and over the minimum standard cost for living. The data show that more of the non-

 

” The minimum standard cost for living for a month in Korea reported by Korean Research Institution for
Health is 206,402 for one family, 356,030 for two family members, 545,729 for three family members,
661,684 for four family members, and 765,627 for five family members ( Korean Research Institution for
Health, The Statistical Annual Report, 1994:32-33). Many women subjects of the present study have four
family members, so minimum standard cost for living for four family members (661,684) was a standard
line of poverty in Table VII-10. Since some subject have less than four family members while some other
subjects have more than four family members, percent distribution of monthly income under and over the
minimum standard cost is not exact reported in Table VII-10. However, these findings can provide primary
information on the comparison between criminal women subjects and non-criminal women subjects in their
economic situation compared to poverty line.

83

criminal are under the poverty line (27.8%) than the criminal women subjects (13%) in

the present study.

Table VII-22. Percent Distribution of Monthly Income under and over the Minimum

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Standard Cost for Living
Criminal Women Non-Criminal Women Total
N % N % %

Under standard cost of 15 13.8 18 27.7 18.8
living (Total)
0=no income 3 2 2 3 2.9
l=under 10 man Won 0 0 2- 3 1.1
2=10 man- 30 man Won 0 0 2 3 1.1
3=30man - 50 man Won 8 7.3 6 9.2 8.0
4=50man-70 man Won 4 3.5 6 9.2 5.7
Above standard cost of 94 86.2 47 82.3 81.2
livin
5=70man-100man Won 16 14.6 13 20 16.7
6=100man-200man 33 30.3 25 38.5 33.3
Won
7=200man-300man 24 22.0 5 7.7 16.7
Won
8= over 300man Won 21 19.2 4 6.1 14.4
Total 109 100 65 100 100

 

 

Furthermore, the result of statistical tests of this study (see page 60, Table VII-12
; page 63, Table VII-13; and page 70, Table VII-17) presented that the effects of poverty

in terms of income level and extent of economic problems on married women's crime

84

were not significant. Therefore, poverty is not a major cause of married women's crime.
In other words, women do not commit crime due to their poverty.

With respect to the second question what makes the increased burden of
household responsibility for married women in south Korea, cause them to engage in
criminal activities. With respect to the increased burden of women’s household
production, the present study considered the four factors; first, the controlling effects of
female-headed households on the relationships between the independent variables of
women's economic situations and the dependent variable of married women's crime;
second, the increasing rates of divorce in south Korea; third, the increased burden of
household responsibility for married women with husband absent; and finally women's
economically marginalized status in terms of limited available jobs for women in Korea.

First, the present study has paid attention to the effect of family structure on
women's economic situation variables (monthly income, women's contribution to their
family financial resources, women's economic burden of supporting family, women's
support network, and extent of economic problems). Correlation Coefficients (see page
59, Table VII-11) shows that family structure variable is statistically correlated to other
economic situation variables such as women's contribution to family's financial
resources, women's economic burden of supporting their family, and the extent of
economic problems. Therefore, to determine the real effect whether family structure
affects the relationships between women's economic situation variables and married

women's crime, the partial regression coefficient controlling for family structure was

85

conducted. Each partial regression coefficient is the outcome of a equation controlling

for family structure.

Table VII- 23. Partial Regression Coefficients (Controlling for Family Structure) for the
Effects of Economic Situation Variables on Crime (N =175; Two-Tailed

 

 

 

 

 

 

 

Significance Tests)
B df Sig R
Family's Monthly Income .3766 1 . 0003* .2191
Women's Financial Contribution .1461 1 . 1392 .0288
Women's Economic Burden .2369 1 . 0219* .1194
Women’s Support Network .1614 1 . 2853 .0000
Economic Problems .0326 1 . 7078 .0000

 

 

 

 

 

 

* Two-Tailed Significance < .05

The comparison between the bivariate multiple regression coefficient reported in
Table VII-12 above (see page 60) and multivariate partial regression coefficient
(controlling for family structure) reported in Table VII-23 reveals that surprisingly, after
controlling for family structure, the original relationship between women's contribution
to family’s financial resources and married women's crime disappear. The elaboration
effects of family structure on the variable of women's contribution to family's financial
resources indicates that the relationship between women's financial contribution and
married women's crime can be explained by family structure. While the relationships
between the other independent variables (family's monthly income, women's economic

burden of supporting family, women's support network, and extent of economic

86

problems) and married women's crime are still significant after elaboration. The
controlling effect on the relationship between women's contribution to family's financial
resources and married women's crime indicates that the original relationship between the
variable of women's contribution to family's financial resources and the variable of
committing crime originates from family structure. Figure VII-1 diagrams shows the
relationship among these three variables.

Figure VII-1. The Relationships among Women's Contribution to Financial
Resources, Married Women's Crime, and Family Structure

 

Women's Financial Contribution

Family Structure / (Hypothesized Independent Variable)

\ Married Women’s Crime

(Hypothesized Dependent Variable)

 

 

 

 

 

 

 

 

 

 

 

In sum, family structure is correlated to other women’s economic variables,
especially women's contribution to family’s financial needs.

Second, the increasing rate of divorce may be closely related to the increased
burden of household responsibility for married women in Korea. The data estimated from
aggregate time-series data reported in Table VII-24 below, shows the increasing rates of
divorce in Korea for the last decade. Divorce rate of 5.8 % per 100 marriages in 1980 is

compared to 15.0% in 1993.

87

Table VII-24. Divorce Rate in Korea in 1980, 1985, 1990-1993

 

 

 

 

 

 

 

Year Divorces (#) Divorces per Divorce rate

1,000 females (#) per 100
marriages (%)

1980 23150 0.6 5.8

1985 38609 0.9 10.3

1990 42898 1.0 10.8

1991 44772 1.0 1 1.2

1992 41511 1.0 12.7

1993 46832 1.1 15.0

 

 

 

 

 

 

Source: Adapted from Korean Women's Development, Statistical Yearbook on Women in 1995: 67,

Originally constructed by National Statistical Office in Korea, Annual Report on the Vital Statistics
(1989, 1994),

Reflecting the increased divorced rates many criminal women are divorced. As
shown Table VII-2 above (see page 49), a proportion of divorce in criminal women
(21.8%) is significantly higher than those of non-criminal women (6.2%). Again, the
criminal women subjects are more likely to be divorced or separated from their husbands.
Therefore, a high proportion of criminal women with husband absent may related to the
increasing rates of divorce in Korea. Also, it is assumed that the increasing rate of divorce
may lead to women's criminal acts.

Third, a majority of women with husbands absent are the main providers for their
children. As shown in Table VII-4 above (see page 51) 52.2% of the criminal women
lived with their children compared to 46.1% for the non-criminal women, after they were

divorced or separated from their husbands. The data indicated that more criminal women

88

are main providers for their children than non-criminal women. Furthermore, higher
percent of offense motivation is to gain money for supporting family (28.2%) and desire
for more money (14.5%) reported in Table VII-8 (see page 54) Thus, the increased
burden of household responsibility of finding family’s needs combined with the
increasing rates of female-headed households may be closely related to married women's
crime in Korea.

Finally, women in Korea are economically marginalized, and this situation may
relate to married women's crime in Korea. Economic marginalization for women in
Korea in terms of limited job opportunities or low paying jobs for married women may
be major cause of married women's crime along with the increased burden of finding
resources to support household needs. I

Table VII-25. Percentage of Labor Force Participation Rates*
by Marital Status and Sex in 1990-1994

 

 

 

 

 

 

 

Year Female Male

married unmarried married unmarried
1990 46.8 45.6 88.2 43.2
1991 47.1 47.9 88.6 45.6
1992 47.0 48.1 88.9 46.3
1993 46.8 49.8 88.8 47.7
1994 47.1 50.5 88.8 49.5

 

 

 

 

 

 

 

Source: Constructed by National Statistical Office in Korea, Annual Report on the Economically Active
Population Survey, 1995, Korean Women‘s Development Institute, Statistical Yearbook on Women,
1995:131.

* Economically Active Population includesl4 years of age.

As shown Table VII-25 above, in case of 1994, married women's labor force

participation rate of 47.1 was lower than their male counterpart for 88.8 %. Also, the

89

labor force participation rate for married women (47.1%) was lower than those of
unmarried women (50.5). Thus, it is more difficult for married women in south Korea to
find a job rather than unmarried women and males.

The comparison between the criminal women subjects and non-criminal women
subjects in their job status (see page 52, Table VII-6 and page 53, Table VII-7) shows the
unstable job status in criminal married women. As shown Table VII-6 above (women's
jobs) and Table VII-7 above (husband's jobs), both criminal women and their husbands
have no job, or insecure jobs, rather than both non-criminal women and their husbands.

A high proportion of hand among female offenders in Korea reflect women's
economic marginalization. A high proportion of married female fraud offenders who are
mostly ages 308 and 408, suggests there might be a relationship between women's limited
job opportunities and married women's crime. Fraud is the most common offense among
female offenders, and has rapidly increased among married women ages 303 and 405.
(Korea training Institute for Criminal Justice, 1995: 333-334). In case of fraud, married
women's increasing involvement in fraud may be related to limited available job
opportunities for these age groups of women. It is very hard for women to become
employed, when they have to make money to support their children or themselves mostly
due to divorce, separation, or limited supports from their husbands. Thus, illegal activities
are attractive to these women to support their family as alternatives to legal employment.

In conclusion, the results of the empirical findings in the present study reveals that
women's poverty in terms of absolute poverty and relative and self-perceived poverty is

not simply related to married women’s crime, the situation is more complex. The major

90

causes of married women's crime closely relate to the increased burden of household
responsibility for married women. This relates to several socioeconomic situations such
as the increased divorce rates, the increased women's economic burden of supporting

their children, and women's economic marginalization through limited available jobs.

The Final Model to Explain Married Women's Crime in Korea

 

 

Poor Financial Supports
from their Husbands
(due to divorce, separation, and so on)

 

 

 

Economic Marginalization
for Women

- Limited Available Jobs
Burden of Household Responsibility - Low paying Jobs

 

 

 

 

- Women’s Financial Contribution
to Family’s Needs

- Women’s Economic Burden of
Supporting their Family

- Female-Headed Households

 

 

 

 

fi

Married Women's Crime

 

CHAPTER VII

SUMMARY AND CONCLUSION

Summgg of the Empirical Findings and Conclusion

Within the women's economic marginalization perspective on female criminality,
the present study analyzed the seven hypotheses of this study. In short, the measures of
women's contribution to families financial resources, women's economic burden of
supporting their family, and family structure are significant predict married women's
crime beyond .05 level. However, the findings support a weak relationship using
regression coefficients R (R for women's financial contribution=.1167, R for women‘s
economic burden= .1888, and R for family structure= .2125). In this sense, the results of
the present study on the effects of women's economic situations on married women's
crime using Korean data are encouraging for Women's Economic Marginalization
Theory.

Especially, the previous perspective that the increasing numbers of female-headed
households lead women to engage in illegal activities alternative to employment (Barbara
et. al., 1995:9) is strongly supported. However, in contrast to a previous study (Box,
19832195), the results of the present study do not support the effects of women's poverty

on married women's crime.

91

92

The empirical tests generally substantiated the hypotheses of this study. A
summation of these findings follows:

1. Facing poverty does not appear to be a cause of married women's crime.

2. Women who contribute to a high proportion of family's financial needs are
more likely to commit crime than women who do not contribute or minimally contribute
to family's financial needs.

3. The hypothesis of this study on the effects of women’s economic burden of
supporting their family on married women's crime is supported. Specifically, women who
are the main providers with many dependent family members have a greater economic
burden and are more likely to commit crime.

4. There are no significant differences between criminal women and non-criminal
women in their financial and emotional support networks, and extent of economic
problems in terms of relative and self-perceived poverty.

5.Female-headed households appear to have had its greatest influence on married

women's crime. It is closely correlated to other women's economic situation variables.
Furthermore, the variable of female headed households is an important contributor to
married women’s crime regardless of whether battered experiences are accounted for.

6.The intervening effects of battered situations on married women's crime is not
significant. However, the statistical data reveals two important things: first, women's
economic situations especially, women’s contribution to their family’s financial needs,

women's economic burden of supporting their family, and female-headed households are

93

significantly related to wife battering; second, criminal women seem to be more abused
by their spouses than non-criminal women.

In conclusion, the major causes of married women’s crime in Korea is not due to
women's poverty, but due to the increased burden of household responsibility to support
their family. This situation is combined with the limited available jobs for women.
Therefore, the present study suggests that the causes of married women’s crime in Korea
is closely related to women's economic marginalization in terms of limited job

opportunities or low paying jobs for women .

Limitstions of the Present Studyapd Suggestions for Future Resea_rph

There are several methodological limitations in this research. The following
suggestions appear to be helpful for future study to provide more complete understand of
the women's economic marginalization perspective on female crime.

First, the measures of individual women’s economic situations of the present
study seem to require some modification. For example, women's contribution to family's
financial needs, women's economic burden of supporting their family, and family
structure are correlated to each other. Especially, the controlling effect of family structure
on the relationship between women's financial contribution to family resources on
married women's crime was significant. Therefore, it is necessary for future examinations
to clarify the conceptual definition of the variables relating to women's burden of

household responsibility.

94

Second, the theoretical perspective of Women's Economic Marginalization
Theory on female criminality raises a question on personality characteristics for criminal
women which may be related to their criminal activities. Many non-criminal women
subjects of the present study especially, factory laborers manage their lives without illegal
activities in spite of their low paying jobs with poor working conditions. At the same
time, criminal women turn to illegal activities, when they have experienced limited
employment availability or low paying jobs. Thus, the need for further consideration on
personality characteristics variables may be necessary.

Third, the micro-measures of women's economic situations of this study that
focused on individual experiences ignored the macro-measures of economic variables.
Individual women's economic situations are basically influenced by broad economic
situations in the society such as an economic recession and welfare benefits (Box,
1987:68-69). Thus, it is suggested that the effect of macro-measures of women's
economic situations on women’s crime should be considered in the future study. Briefly,
the micro-measures of married women's crime using self-report data of this study need to
be combined with official measures of macro-model analysis of married women's crime.

Finally, because of the limitation of this study focused on married women's crime,
it is critical that future studies should include unmarried women subjects or male subjects

along with married women to examine the hypotheses of the present study.

LIST OF REFERENCES

95

LIST OF REFERENCES

Anderson, Margaret Thinking About Women. New York: Macmillan, 1980..

Bartel, Ann P. Women And Crime: An Economic Analysis. Economic Inguig.
Vol. XVII, Jan. 1979, 29-51.

Barbara Bloom, Cheoleon Lee, and Barbara Owen. Oflense Patterns Among
Women Prisoners: A Preliminary Analysis. The 47th Annual Meeting of the
American Society of Criminology, Nov. 1995.

Box, S. , Hale, C. Economic Crisis and the rising Prisoner Population in
England and Wales, 1949-1979. Crime and Social Justice 1982 (16), 20—35

 

Box. 8. Recession. Crime and Punishment. London, Macmillan, 1987.

Box. S. Power. Crime. and Mystification. Travistock Publications. London and
New York, 1983.

Brett, Crista. From Victim to Victimizer. In Gondles, James A.(Eds.), Female Offenders:
Meeting Needs of s Neglected Ponulation. American Correctional Association, United
Book, Inc., 1993, 26-30.

Browne, A. When Battered Women Kill. New York: Free Press, 1987.

Campbell, Jacquelyn C. Relationship Status of Battered Women over Time, Journal of
_F_amily Violence. 1994 (9): 99-112.

Carlen, Pat Women. Crime and Poverty. Open University Press, 1988.

Cho Hyung. Labor F orce Participation of Women in Korea. In Chung Sei-Wha
(ed). Challenges for Women. Women‘s Studies in Korea. Seoul: Ewha Womarrs
University Press, 1988.

Choi In- Sub. A Stuay on the Realities of Female Crime in Korea. Research on

Criminology, 1993(4), 45-102.

Correction Bureau Ministry of Justice in Korea. Correctional Administration
in Korea. 1991.

96

Elizabeth, M. Turner, and Charlie, G. Turner. South Korean Labor Market
Discrimination Against Women: Estimating Its Cost. American J oumpl of Economics
and Sociology, 1994 (53), 433-441.

Flowers, R. Barri. Female Crime Criminals and Cellmates. McFarland &
Company, Inc., Publishers, 1995.

Flowers, R. Barri. Women and Criminality: the women as victim. offender. and
practitioner. New York Greenwood Press, 1987.

Grossman, Judy. Domestic Violence And Incarceration Women. Division of Program
Planning and Evaluation, State of New York Department of Correctional Services.
1 989.

Hagenaars, Aldi & Klaas De Vos. The Definition and Measurement of Poverty. fl;
Journal of Human Resources 1987 (23); 210-225.

 

Heidensohn, Frances. Women and Crime. New York University Press, 1995.

Kim Tae-Hong._Analysis on the Reasons of Married Women’s Labor F orce Participation.
Studies on Women in Korep, 1993 (11):134-155.

Korean Women's Development Institute. A Study on The Realities of Wife Battering,
1993.

Korea Training Institute for Criminal Justice. Criminal Statistics 1995.

 

Korea Training Institution for Criminal Justice. Criminal Statistics 1992.

 

Lee In-Soon, A Study on Realities on Female Offenders and Policy Implications.
Choong- Pook University, 1991.

Leonard, Eileen B. Women, Crime, and Socieg: A Critique of Criminology Theory.
Longrnan, 1982.

Mangold, William D. Jr. and Patricia, R. Koski. The relationship Between Parental and

Silbing Violence and Non-family Violence. Journal of Family Violence, 1990: 225-
234.

Mechanic, M. B. Battered Women, Homicide, and the Legal System. In Albert R.
Roberts (Eds). Helping Battered Women. New York, 1996: 132-150.

Messerschmidt, James W. Masculinities and Crime: Critique and
Reconceptualization of Theory. Rowman & Littlefield Publishers, Inc., 1993.

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Messerschmidt, James W. Capitalism Patriarchy, and Crime. Rowman &
Littlefield Publishers, Inc., 1986.

Milkman, Martin. Female Criminality: An Economic Perspective. In Concetta C. Culliver
(Eds), Female Criminalig. Garland Publishing, Inc. New York & London, 1993.

Moon Yoo- Kyeong. Statistical Yearbook on Women. Korean Women's Development,
Seoul Korea, 1995.

Naffine, Nagaire. Ferrpfle Crime: The construction of women in criminology.
Allen & Unwin. Sydney Wellington London Boston, 1987.

Rafter, N. Partial Justice. Women. Prisons_and Social Control ( 2nd ed). New
Brunswick: Transation, 1990.

Research Institute for Criminology. An Empirical Study on Adultery in Korea: Focusing
on th_e Extent and Attitude, Seoul Korea, 1991.

Research Institute For Criminology. A Study on the Prevalence and Policy Implications
of the Domestic Violence in Seoul. 1992.

Simpson, Sally S. Caste, Class, And Violent Crime: Explaining Diflerence in Female
Oflenders. Criminology, 199 l (29): 1 15-135.

Song Young-In. Battered Women in Korean Immigmt Families. Garland Publishing,
Inc. New York and London, 1996.

Steffensmeier, D. J. Sex diflerences in patterns of adult crime. 1965-1977: A
Review and Assessment. Social Forces 1980 (58) :1080-1108.

 

Straus, Murray. Physical Violence in American Family; Risk Factor and Adaptation to
Violence. Transaction Publishers, 1990.

The Supreme Public Prosecutors‘ Officer. The Analytical Report on Crime. Seoul Korea,
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Yang Seung-Joo. An Analysis on the Reason of Labor F orce Participation among
Married Women in Korea. Studied on Women in Korea, 1993 (11):133-155.

Yllo, K. A. Through a feminist Lens: Gender, Power, and Violence. In R. Gelles and D.
Loseke (Eds). In Current Controversies on Female Violence. Newbur Park, 1993: 47-
62.

APPENDIX A

 

98

QUESTIONNAIRE

* only for criminal sample

(1) Background Information

 

Please read the questions and answer to the best of your ability. Please write down or
circle your responses.

 

 

1.What is your age? ( )
2. What is your religion?
1. no religion 2. Buddhism
3. Christianity 4. Catholic
5. Muslim 6. others
3. What is your education level?
1.no formal education 2.elementary school or less
3. middle school or less 4. high school or less
5. technical college completion or less
6. university or above
4. What was your marital status before your incarceration?
1. living together 2. legally married and living together
3. living separately from your legal spouse

4. divorce 5. separated by death

5. How long have you been married ? ( ) years ( ) months

99

6. How many children do you have? ( )

7. How many children do you have aged under 8 ? ( )

8. Who did you live with before your incarceration? Please circle all of your responses.

1. husband 2. children
3. your husband or your farmly member(s)

4. fiiend(s) 5. lived alone
6. other

9. Who will look after your children after your release?

1. you and your husband 2. you or your family
3. husband or husband's family 4. relatives
5. social facilities 6. do not know

(2) Economic Situation

 

The following questions ask about your economic situation. Please select the closest

to your situation, and circle the number.

 

 

10. What is your husband's job?

 

0.nojob

 

1. temporary employed

 

2. permanently employed

 

3. self-employed

4. own business with more

 

100

 

than one person outside the family

11. What was your job before your incarceration?

 

O.nojob

 

1. temporary employed

 

2. permanently employed

 

3. self-employed

4. own business with more

 

than one person outside the family

12. What was the monthly average income of your family before your incarceration?

0. 0 1. less than 10 man Won
2.10 man - 30 man Won 3.30 man - 50 man Won
4.50 man - 70 man won 5. 70 man - 100 man won
6. 100 man- 200 man 7. 200 -300 man won

8. more than 300 man won

13. Did you provide for your family‘s resources, before your incarceration?
0. I did not provide at all.
1. I was in charge of part of them along with my husband.

2. l was totally in charge of them.

14. If you answer on 2 or 3 above question, how many dependents did you have

including you? ( )

15. If you had earned money before incarceration, what percent of your family‘s spending

came fi'om your eaming? ( ) %

101

16. Where did the money come from for your family's spending?

1. husband's income
2. husband’s and your income
3. your income
4. supported from your family or husband‘s family, friends, or neighbors

5. supported from social welfare system or religious group

17. When you had financial problems, and your husband could not help you, did someone

else help you?
0. never I. sometimes
2. often 9. I did not want that kind of help.

18. When you were serious ill, and your husband was not available, did someone else

help you?
0. never I. sometimes
2. often 9. I did not want that kind of help.

19. What was your housing situation before your incarceration?
0. lived in your family‘s house 1. rental by yearly
2. rental by monthly
3. relative‘s house, friend‘s house, or social facility

20. How do you evaluate the economic status of your family before your incarceration?

0. wealthy 1. somewhat wealthy

2. moderate 3. poor

102

21. To what extent did your family suffer from economic problems?

0. to no extent at all 1. to a small extent

2. to a some extent 3. to a great extent

22. If you had experienced to fail to take a job, what the reason was?

1. my poor job skill, or incompetence
2. limited job opportunities for manied women
3. poor working condition or low payment
4. there was no way to take care of my children ( lack of day care facilities for my
young kids).
5. husband's oppression

6. others

24. If yes on question 25, what kind of job do you think you will have?

1. no occupation 2. housekeeper
3. employee in the company 4. service women
5. merchant 6. do not know

7. others

( 3) Questions on Offense (only for incarcerated women sample)

 

Following questions are related to your incarceration. Please write or circle your

reSponses.

 

*24. Incarcerated for what type of offense? ( )

 

103

*25. Have you been arrested before?

1. yes 2. no

*25-1. If yes, how many times ( not including this case)? (

*26. How long have you been incarcerated? ( ) years (

*27. What was the motivation of your offense?

I. desire for more money

2. financial gain for family need

3. for financial gain for excitement

4. incident or curiosity

5. jealousy, revenge

6. influenced by others

7. under influence of alcohol or drugs
8. others

*28. Who was your victim of offense?

1. family member 2.relative
3. neighbor or friend 4. job related person
5. unacquainted person 6. no human victim

7. do not know 8. others

) months

104

(5) The Extent of Spouse Abuse

 

 

I am going to ask some things that you and your husband might do when you had an
argument in the last 12 months before your incarceration. Did your husband do any of

these ?

 

29. He threatened to hit or throw something at you.

1. almost every day 2. once or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7. can not remember

30. He threw or smashed or hit or kicked something.

1. almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year Some or twice a year 6. never 7 can not remember

31. He threw something at you.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

32. He pushed, grabbed, or shoved you.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year Some or twice a year 6. never 7 can not remember

33. He slapped you.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year Some or twice a year 6. never 7 can not remember

 

105

34. He kicked, bit, or hit you with fist.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

35. He hit or tried to hit you with something.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

36. He beat you up.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

37. He choked you.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

38. He threatened you with a knife or dangerous thing.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

39. He used a knife or dangerous thing.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

106

40. He personally forced you to have sexual relations after conflict with you.

1.almost every day 2.0nce or twice a week 3. once or twice a month

4. once or twice in half a year 5.once or twice a year 6. never 7 can not remember

APPENDIX B

107

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