MUST BE 250WORDS WITH 3 SCHOLARY SOURCES APAP FORMAT .
After reading Chapter 5 of the Mosher textbook, the article entitled “Internet Development, Censorship, and Cyber Crimes in China” by Liang and Lu, and the article entitled “‘Snitches End Up in Ditches’ and Other Cautionary Tales” by Morris, discuss the following prompts:
- Although presented differently, how do the research articles affect the development of criminal justice public policy?
- As a criminal justice leader, does the National Crime Victimization Survey (NCVS) give you a reason for concern? How/Why?
- What are the advantages of the NCVS versus the Uniform Crime Report (UCR)/National Incident-Based Reporting System (NIBRS) data?
- As a criminal justice leader or school safety leader, does the “‘Snitches End Up in Ditches’ and Other Cautionary Tales” article cause you to act? In what way?
Articles
Journal of Contemporary Criminal Justice
26(1) 103 –120
© 2010 SAGE Publications
Reprints and permission: http://www.
sagepub.com/journalsPermissions.nav
DOI: 10.1177/1043986209350437
http://ccj.sagepub.com
Internet Development,
Censorship, and Cyber
Crimes in China
Bin Liang1 and Hong Lu2
Abstract
Since its first Internet connection with the global computer network in 1994, China
has witnessed explosive Internet development. By the end of 2008, China replaced
the United States as the largest Internet user of the world. Although China enjoyed
tremendous economic benefits from Internet development, the Chinese government
has tried to maintain tight control over the telecommunications industry and the
public Internet use, and fight increasing cyber crimes. In this article, we first review
historical development of Internet use in China and then focus on China’s Internet
censorship and its regulatory control. Next, we explore how the Internet is actively
utilized by both the government and the public to serve political and civic functions.
Finally, we discuss cyber crimes as an emergent form of crime in China and examine
how the Chinese government reacts to these offenses. Lessons from Internet use
and regulation in China are also discussed within the context of China’s economic,
political, and legal conditions.
Keywords
Internet, Internet censorship, Internet regulation, cyber crime, China
Introduction
Internet use and development is one of the most important inventions in the second
half of the 20th century. It has transformed people’s lives and its impact is beyond
one’s imagination and is still to come in many aspects.
1Oklahoma State University-Tulsa
2University of Nevada, Las Vegas
Corresponding Author:
Bin Liang, Associate Professor, Department of Sociology, Oklahoma State University–Tulsa, 700 North
Greenwood Avenue, Main Hall, 2223, Tulsa, OK 74106
Email: bin.liang@okstate.edu
104 Journal of Contemporary Criminal Justice 26(1)
China’s Internet use and development did not begin until a decade later after its
economic reforms. Its growth has outpaced other countries, and China by 2008 has the
largest number of Internet users in the world. What accompanied China’s Internet
development is the government’s tight control and regulation over Internet infrastruc-
ture, its commercial and social use, and its potential political ramifications. Despite
being criticized by human rights groups and activists, China’s Internet censorship
system seemingly functions well as the “Great Firewall of China.”
On the other hand, there is high hope that Internet use and development in China
will eventually lead to democracy in the largest country, testing the hypothesized rela-
tionship between Internet use, free flow of information, and democracy. Indeed, the
Internet has profoundly transformed the Chinese society in the last decade, even in
China’s political-legal reforms. However, democracy is still as far-reaching as it once
was and the role of the Internet in this reform has been constrained by the wider socio-
political and economic context of China.
Like many other nations, China’s Internet use and development also witnessed
surging cyber crimes, many in traditional forms but others as new phenomena. Unfor-
tunately, this appears to be the least studied subject. Key questions such as the status
of cyber crimes in China, the features of such crimes, and the government’s response
to these crimes are rarely answered.
In this article, we briefly review the historical development of Internet use in China
and its regulation. We also explore the issues of China’s democracy on Internet use,
the political and civic functions of the Internet, and emergent forms of cyber crimes
and the Chinese government’s response to them. These issues are all discussed within
China’s wider social, economic, political, and legal conditions.
Internet Development: Beyond
the Great Wall, Joining the World
China’s Internet development has come a long way in a very short time (Wu, 1996).
Though China initiated the economic reform and “open-door” policy in the late 1970s
and early 1980s, the use and development of Internet did not appear until almost a
decade later. In the late 1980s, China’s academia, with the support of foreign partners,
began to explore Internet use. In September 1987, a symbolic message “Beyond the
Great Wall, Joining the World (yueguo changcheng, zouxiang shijie)” was sent from
China via email (Qiu, 2003). In 1994, China connected its first international dedicated
line to the Internet and became the 71st country to register onto the global computer
network and received CN as the highest level domain name (Lu et al., 2002; Taubman,
1998).
Similar to other countries, China’s early efforts at creating Internet networks were
focused on the scholarly exchange of information. Its first networks reflected these
interests, including the China Academic Network (CANET), China Research Network
(CRNET), and the Institute of High Energy Physics (IHEP) Network (Harwit & Clark,
2001). Soon after, China began to realize the significance of computer information
Liang and Lu 105
technology in its economic development and encouraged fast development of Internet
in commercial use to embrace the new information era. As a result, China witnessed
tremendous expansion of Internet use.
China’s total estimate of Internet users was only a few thousands by the mid-1990s
but grew exponentially afterwards. Based on annual survey data by the Chinese Inter-
net Network Information Center (CNNIC), Internet uses in China reached 2 million in
1998, surpassed 100 million in 2005, and rose to 298 million by the end of 2008.
China also replaced the United States as the largest Internet user of the world. Despite
its uneven distribution across geographical regions (e.g., rural areas carry fewer users
than urban areas), China’s Internet coverage of its total population (23% by 2008)
already passed the world average coverage (22%) (CNNIC survey reports at http://
www.cnnic.cn/en/index/0O/02/index.htm; Dowell, 2006; Srikantaiah & Dong, 1998;
Tan, 1999; Tai, 2006; Wang, 2002).
Along with the growth of Internet users, other indexes of Internet development are
impressive as well. Since the official establishment of the CNNIC in 1997, the number
of registered domain names increased from a little more than 4,000 in 1997 to 1.8 mil-
lion in 2004 and reached nearly 17 million by 2008; the number of registered Web
sites increased from less than 4,000 in 1997 to almost 3 million by 2008.
China’s Internet development has been bound to its overall economic development
in general and the growth of its telecommunication industry in particular over the
years. For example, in 1997, the numbers of fixed-line telephones and mobile phones
were about 70 million and 13 million, respectively (annual data reported by the
National Bureau of Statistics of China). By 2001, China surpassed the United States to
become the world’s largest mobile telecom market and its total number of mobile
phone users reached nearly 373 million by 2005 while the number of fixed-line tele-
phone reached 342 million (Tai, 2006, p. 119). CNNIC (2008) estimated that more
than 117 million Internet users accessed Internet via their mobile phones by 2008 and
more than 90% of Internet users (270 million) had broadband Internet access.
In comparison to other nations (e.g., Abbott, 2001; Fan, 2005; Srikantaiah & Dong,
1998; Xue, 2005), the intervention and domination by the Chinese government has
been the major distinctive feature of China’s Internet development. The Internet boom
was made possible largely because of a “state-centric strategy for comprehensive
informationization” (Hartford, 2000). This state-precipitated development of the
Internet also ensured the state ownership and control of main Internet infrastructure
and the use of Internet.
Internet Censorship and Regulation: The Great Firewall,
Self-Censorship, and Multidimensional Regulations
Given China’s single-party political system and its heavy intervention in Internet
development, its Internet censorship and regulation has evolved into a comprehensive,
multidimensional system that governs Internet infrastructure, commercial and social
use as well as legal domains.
106 Journal of Contemporary Criminal Justice 26(1)
The great firewall. The predominant method of control at the infrastructure level is
restriction of access to Internet information (e.g., regulating access and content, moni-
toring Internet use). At the national level, only government-approved agencies and
businesses are permitted to establish an Internet Interconnecting Network (also called
“backbone network” or gugan wangluo in Chinese) and to license the operation of
Internet service providers at the next tier. These networks are required to go through
international gateways located in Beijing, Shanghai, and Guangzhou and are subject
to governmental control and regulation (see, for example, Cheung, 2006; Fan, 2005;
Perritt & Clarke, 1998; Tan, 1999). At the next tier, all private Internet service provid-
ers are licensed through one of these Internet Interconnecting Networks and are
required to install filters to block away undesirable content. The bottom tier involves
Internet users who are required to register with Internet service providers to gain Inter-
net access.
The Chinese government has also been constantly updating its surveillance and
control system. Take the “Golden Shield” project for example. As one of the “Three
Golden Projects,” it was first proposed in 1993 and approved in 1998. This project,
still going on, is part of the Great Firewall of China. Its main function is to censor and
control Internet information both domestically and globally (Dowell, 2006). In addi-
tion, China has established a special Internet police force to assist its Internet
surveillance. In August 2000, Anhui became the first province to set up Internet police
force and 20 others followed suit later; more than 300,000 personnel were reportedly
hired nationwide by the end of 2000 (Endeshaw, 2004; Harwit & Clark, 2001; Keith
& Lin, 2006; Tai, 2006).
Prohibited activities/materials/information related with the Internet are placed in
nine broad categories by the Chinese government. These include information that
(a) is contrary to the basic principles that are laid down in the Constitution, laws, or
administration regulations; (b) is seditious to the ruling regime of the state or the
system of socialism; (c) subverts state power or sabotages the unity of the state;
(d) incites ethnic hostility or racial discrimination, or disrupts racial unity; (e) spreads
rumors or disrupts social order; (f) propagates feudal superstitions; disseminates
obscenity, pornography, or gambling; incites violence, murder, or terror; instigates
others to commit offences; (g) publicly insults or defames others; (h) harms the
reputation or interests of the state; or (i) has content prohibited by laws or administra-
tive regulations (pp. 13-14; Cheung, 2006; Dai, 2000; Human Rights Watch, 2006,
pp. 18-19).
Despite its great effort, the effectiveness of China’s Internet censorship is unclear.
Although some argued that it is very questionable (e.g., Deibert, 2002; Lacharite,
2002), others viewed it as effective (e.g., Kalathil & Boas, 2001) and even as “the
most sophisticated effort of its kind in the world” (Open Net Initiative, 2005).
Though there are many ways to circumvent the government’s Internet filtering,
such as use of proxy servers, private emails, and manipulating one’s search (Abbott,
2001; Dai, 2000; Deibert, 2002; Lacharite, 2002; Zittrain, 2004), there still lacks
knowledge of how many Chinese Web surfers adopt such approaches (Human Rights
Liang and Lu 107
Watch, 2006). One common finding is the inconsistent enforcement of China’s Inter-
net filtering. Studies show that Internet blocks have come and gone, and the content of
blocks also varies from time to time, most likely because of the fact that there is no
coherent and consistent decision-making process (Hartford, 2000; Sohmen, 2001).
Another finding is the extensive scope of China’s censoring, covering not only politi-
cal issues but also issues such as crimes and economics (Hartford, 2000; Open Net
Initiative, 2005). Empirical testing of the Chinese filtering system also found that the
filtering system is rather dynamic and has been self-changing and refining over time
(Open Net Initiative, 2005). In sum, China’s Internet control represents an “imperfect
control,” aiming at keeping the vast majority from sensitive materials and preventing
the nonconforming small minority from mounting a real challenge (Hartford, 2000).
Self-censorship. In addition to setting up technological restrictions to Internet infor-
mation at the infrastructure level, the Chinese government also put high pressure on
businesses and individuals to conform to its censorship in Internet commercial and
social use. For instance, governmental regulations after 2000 set a priority instituting
self-regulation and increasingly delegated policing power to nonstate sectors (Cheung,
2006; Endeshaw, 2004). Given their limited choices, high governmental pressure, and
potential stiff penalties, adopting “self-regulation” and complying with state censor-
ship seems to be the only viable option to business owners. In March 2002, for
example, the Internet Society of China (ISC) issued a “Public Pledge on
Self-Discipline for the China Internet Industry” (zhongguo hulianwang hangye zilü
gongyue) in Beijing, establishing the foundation of domestic self-discipline mecha-
nism (Endeshaw, 2004, CNNIC Web site). Given the broad and vague nature of
government regulations, many businesses decided to play safe and end up with even
more sweeping censor mechanisms (e.g., Human Rights Watch, 2006; Sohmen, 2001).
China’s surveillance system also target foreign business investors in China. The
Chinese government gained technical support from foreign companies (e.g., Cisco,
Sun Microsystems) in building its Internet infrastructure (e.g., Qiu, 2003), yet required
Internet corporations such as Google, Inc., Yahoo!, inc., Microsoft Corp., and Skype
to comply with Chinese laws and regulations and to modify their Chinese version of
search engines to filter sensitive information (Battelle, 2005; Fry, 2006; Hinman,
2005; Human Rights Watch, 2006). In 2002, Yahoo! also voluntarily signed the
“Public Pledge on Self-Discipline for the China Internet Industry” (Dowell, 2006;
Human Rights Watch, 2006). Despite strong criticism from human rights activists,
these corporations have justified their censoring as necessary compliance with local
laws to run business (and the Chinese market is simply too large to ignore). Moreover,
foreign investors are specifically prohibited from owning, operating, or managing
telecommunications services in China. Even after its entry into the World Trade Orga-
nization (WTO) in 2001, the Chinese government carefully controlled its
telecommunication industry: foreign ownership is capped at 50% for value-added ser-
vices and 49% for mobile telephone and domestic and international services (Pangestu
& Mrongowius, 2002). Despite great hope by many (e.g., Dai, 2000; Deibert, 2002;
108 Journal of Contemporary Criminal Justice 26(1)
Harwit & Clark, 2001), the impact of WTO on China’s democracy in general and
Internet censorship and control in particular remains unclear.
Multidimensional regulations. China’s legislation over Internet use and development
has definitely grown and become more comprehensive over time. The increasing leg-
islation also accompanied a series of changes in regulating agencies. As Tan (1999)
delineated, the pre-1994 era represented an experimental era characterized as a frag-
mented structure without a single authority; from 1994 to 1998, China witnessed a
transitional period, during which a single regulatory coordinator, the State Council’s
Steering Committee of National Information Infrastructure, was established to negoti-
ate and cooperate with other governmental agencies; in 1998, the Chinese government
merged the existing Ministry of Post and Telecommunications with the Ministry of
Electronics Industry to form one major single regulator, the Ministry of Information
Industry (MII). Since then, the MII has become the dominant regulator of China’s
telecommunications industry.
Given the complex and comprehensive scope of China’s Internet regulations, how-
ever, many other agencies (e.g., State Council, Ministry of Public Security (MPS),
Ministry of Culture, and State Secrets Bureau) still have regulatory authorities in
Internet use and development and remain actively involved (Open Net Initiative,
2005; Zheng, 2008). While making comprehensive Internet control possible, the
involvement of multiple agencies and players also creates inefficiency, redundancy,
uncertainty, and confusion (Endeshaw, 2004; Qiu, 2003). In addition, the lack of sepa-
ration between state-owned operation and regulation (e.g., the MII is closely involved
with China Telecom which owns CHINANET) may enable agencies with regulatory
power to directly obtain financial gains (Sohmen, 2001).
One direct result of such a multidimensional regulatory system is the comprehen-
sive scope of agency regulations. Laws and regulations enacted over time cover a
broad range of issues from infrastructure construction to Internet network security,
Internet domain names registration, computer encryption, management of online busi-
ness operation, Internet news reporting and publication, and copyright protection. For
example, regulations in April 1996 stipulated that all domestic computer systems
could only be connected to Internet Interconnecting Networks via the gateways estab-
lished and managed by the Ministry of Post and Telecommunications (which was later
merged into the MII). The Administration of the Maintenance of Secrets in the Inter-
national Networking of Computer Information Systems Provisions in 2000 prohibited
Internet users from sending state secrets via email or discussing state secrets in Inter-
net chat rooms or on bulletin boards. The Administration of Engagement by Internet
Sites in the Business of News Publication Tentative Provisions in 2000 and Interim
Regulations for the Administration of the Internet Publications in 2002 tightened con-
trol over Internet news reporting and publication. Based on both, the only bona fide
news is official news from government sources such as the Xinhua News Agency and
the People’s Daily (renmin ribao); Internet organizations cannot cite foreign news
without official approval; all online publications must be inspected and approved as
well. The Regulations on the Administration of Business Sites of Internet Access
Liang and Lu 109
Services in 2002 (replacing the old one in 2001) requires that Internet business owners
(e.g., Internet cafés) keep records of users’ information for 60 days for government
inspection purpose.
Besides its broad scope, there are a number of other features about China’s legisla-
tion over time. First, China’s legislation is often vague and uncertain in nature. For
example, the key term “state secret” was ill-defined in the 2000 regulation cited above
(Tai, 2006). Some scholars (Cheung, 2006; Endeshaw, 2004; Keith & Lin, 2006;
Weber, 2002) pointed out that the Chinese government did this on purpose to ensure
ample room for its interpretation and manipulation. In addition, the uncertain and
unspecified broadness holds Internet business owners and users in constant fear and
therefore strengthens their self-censorship (Cheung, 2006). Second, many regulatory
measures are often post hoc reactions to unpredictable conditions (Endeshaw, 2004;
Qiu, 2003). As a result, many key regulations have been revised and refined over the
years to “bring social and economic life in line with a priori principles and expecta-
tions” (Endeshaw, 2004, p. 46). Third, many laws and regulations overlap and create
redundancy and confusion sometimes (e.g., due to different expectations and require-
ments between the Communist Party and the central administration), and such
confusion is reflected in the lack of coherent and consistent decision-making pro-
cesses and inconsistent enforcement (Endeshaw, 2004; Sohmen, 2001; Qiu,
1999/2000).
Internet Development and Democracy,
E-Government, and Civic Engagement
Internet & democracy. Given China’s Internet censorship and authoritarian polity, a
question, often asked, is the relationship between Internet development and democra-
tization in China. There is a strong belief that Internet development, free flow of
information, and formation of civil cyber groups pose potential threat to authoritarian
regimes and China is no exception (Kluver, 2005; Tai, 2006; Taubman, 1998; Yang,
2003). However, Internet use and development in China has so far failed such an
expectation (Kalathil & Boas, 2001) and some even argue that the Internet has become
a new tool for governmental control (Tsui, 2003).
One possible answer could be found in the profile of Chinese Internet users. Besides
demographic changes over the years (e.g., greater Internet penetration rate, lesser
gender and geographic disparity), one consistent finding is the majority Chinese Inter-
net users’ apathy for political communications (Hong & Huang, 2005). Instead, the
majority of Chinese citizens use the Internet for gaming, entertainment, sports news,
celebrities, and study and career opportunities (Kluver, 2005). Furthermore, China’s
culture may have a role to play as well (Weber, 2002). Zhang, Chen, & Wen’s com-
parative study (2002), for example, found that compared to Americans, Chinese
Internet users are more supportive of a greater extent of government involvement in
Internet regulation, consistent with Chinese citizens’ general attitude toward a greater
role of the government in governing the society. It is not clear, however, why the
110 Journal of Contemporary Criminal Justice 26(1)
majority of Chinese Internet users show little interest in political issues. More empiri-
cal studies need to address how Chinese Internet users feel about Internet use and
development, despite the heavy top-down approach adopted by the Chinese
government.
E-government project. The Government Online Project (zhengfu shangwang
gongcheng) was kicked off in 1999. As part of this project, all government departments
are required to build their own Web sites and provide online management and service
functions (Lu et al., 2002; Wang, 2002). Registered government domain names (gov.
cn) increased from 323 in 1997 to 13,963 by July 2004 (3.7% of the total registered
domain names), and the number of Chinese government Web sites also amounted to
12,332 by 2004 (2.0% of the total Web sites) (Lagerkvist, 2005; Zheng, 2008, p. 38).
Through its E-government project, the Chinese government aims at reaching a
number of goals such as increasing government transparency and organizational effi-
ciency, strengthening propaganda (e.g., the opening of Tibet human rights Web site
recently, www.tibet328.cn), reestablishing legitimacy of the Communist Party, con-
taining or eradicating more pressing political problems (e.g., corruption), and gaining
better control over lower-level and/or local cadres (Kalathil & Boas, 2001; Kluver,
2005; Lagerkvist, 2005). In this process, governments at all levels are encouraged to
take advantage of the new computer information technology, and the central govern-
ment is eager to show its lead. On June 20, 2008, for example, President Hu Jintao
hosted his very first online communication with Web surfers, and Premier Wen Jiabao
followed suit on February 28, 2009. Such Internet communication between users and
top national leaders was hailed as a significant step toward “Internet politics” in which
Internet users’ political rights of information, participation, and supervision were
honored.
These e-projects also have an impact on the legal system. Take judicial reforms for
example. In 2009 the Supreme People’s Court (SPC) published its Outline of the 3rd
Five-Year Reform of the People’s Courts (2009-2013). To improve adjudication and
execution of judicial verdicts, the SPC proposes displaying judicial judgments online
whenever feasible. Several courts such as courts in Beijing, Henan, and Hebei have
already started such a practice as early as in 2003. By April 10, 2009, more than 160
basic courts and 50 intermediate level (appellate) courts have reportedly adopted such
a practice, and a total of 59,744 judicial judgments have been posted online at various
courts’ Web sites (News reported on April 10, 2009 at http://www.chinacourt.org/
html/article/200904/10/352466.shtml, last retrieved on April 29, 2009; the Legal
Daily, December 17, 2008; the People’s Daily, March 17, 2009). Most recently on
April 14, 2009, the official Web site of China’s courts (www.chinacourt.org) also
announced establishment of free email boxes at all courts to facilitate communication
between the courts and the public (News posted on April 14, 2009 at http://www
.chinacourt.org/html/article/200904/14/352922.shtml, last retrieved on April 29,
2009). Such a practice echoed similar moves by many administrative organizations
and leaders, which seemingly gained much support (Hartford, 2005). To go one step
further, some courts even started televising live trials online.
Liang and Lu 111
Civil engagement. It is not accurate that all Chinese Internet users shun away from
political issues in China. Rather, their participation shows in a unique form (often
event driven) at critical moments (sometimes unexpected). Given the growing mass of
Internet users, their online response, reaction, and participation have already created
an unexpected amplification of public engagement in some key events (Dowell, 2006;
Zheng, 2008). Take the 2009 “hiding from the cat” event for example. In January,
2009, Li Qiaoming was arrested for cutting down and stealing trees and put into jail in
Jinning county, Yunan province. On February 8th, Li was mysteriously injured and
died in a local hospital on the 12th. After a perfunctory investigation, local police and
procuratorate announced that Li got injured when he was playing a game called
“hiding from the cat” (duo maomao) with his jail mates. What was unexpected after
the official announcement this time was the strong criticism and questioning by Inter-
net users, and suddenly “hiding from the cat” became a new online bomb.
Under the pressure to discover and disclose the “truth”, the Chinese Communist
Party Propaganda Department in Yunan (CCPPDY) recruited five Internet users to
form a special investigation committee (and two Internet users even chaired the com-
mittee). On the 20th, the committee went to Jinning county and conducted its
investigation. Due to lack of access to key evidence (e.g., the coroner report, surveil-
lance tape of the jail, and interviewing jail mates), the committee could not reach a
conclusion and simply posted its investigation process online on the 21st.
On the 27th, the Public Security and Procuratorate officials of the Yunan province
announced the result of its official investigation. According to the report, Li was bul-
lied numerous times by his jail mates in jail and suffered injuries. On the 8th, his jail
mates blindfolded Li and beat him up. Li’s head was hit and bumped into the wall,
which eventually caused his death. Li’s jail mates made up the story of playing a game
to cover the truth. The report also disclosed various violations of prison management
rules and regulations by both prison guards and bully inmates and called for further
action. As a result, one director of the procuratorate in Jinning county was deposed,
and three jailmates were charged with assaults and sentenced in August along with
two prison guards who were found negligent (information summarized from various
Internet sources).
The “hiding from the cat” event finally came to a conclusion but the term becomes
a new symbol among Chinese Internet users. It is true that public engagement in major
events such as the “hiding from the cat” is nonsystematic, spontaneous, and unpredict-
able. These events, however, do carry a great potential to shake political-legal reforms
in China to some extent.
Cyber Crimes: Control and Evolution
In comparison to Internet censorship and regulation, studies on China’s cyber crimes
(wangluo fanzui) are scarce. Similar to Western nations, cyber crimes are broadly
defined in China to cover crimes that are committed with the involvement of computer
information technology; cyber crimes are further classified into two large categories:
one on crimes directly targeting computer systems and information networks, and the
112 Journal of Contemporary Criminal Justice 26(1)
other on crimes committed through the use of computers and their related networks
(Chen, 2004; Keith & Lin, 2006, p. 119).
Based on statistics from the MPS, Yu (2007) reported that the total number of
investigated cyber crimes in China was a little more than 400 in 1999; it jumped to
2,700 in 2000, 4,500 in 2001, and reached 6,633 in 2006. These numbers are no doubt
only the tip of the iceberg, as the Chinese official admitted that the authority could
have only managed to investigate 20% of estimate cyber crimes (News reported by the
Xinhua net.com in Tianjin on November 17, 2005, available at http://www.tj.xinhua.
org/misc/2005-11/17/content_5613021.htm, last retrieved on April 30, 2009). A report
from singtaonet.com in 2007 even listed China as the second largest cyber crime
nation in the world, only behind the United States (News reported at http://www.sing-
taonet.com/society_focus/200708/t20070810_595551.html, last retrieved on April 30,
2009).
Laws and regulations. Cyber crimes are not regulated by one single special law in
China. Rather, they are covered by a scope of laws and regulations with a comprehen-
sive nature as discussed above (Zhou, 2009). The first effort, the Ordinance for
Security Protection of Computer Information System issued by the State Council in
February 1994, gave the MPS the overall responsibility to supervise, inspect, and
guide the security protection of computer information systems and “to investigate
criminal activities” that undermine computer networks, though the ordinance failed to
specify the forbidden content (Tai, 2006).
The revised Criminal Law in 1997 (CL97) tried to formalize legislation on such
crimes in articles 285-287. Article 285 covered unauthorized criminal access to
computer-housed information concerning state affairs, national defense establishment
facilities, and sophisticated science and technology; article 286 stipulated crimes of
deleting from, altering, adding to, and interfering with computer information system,
causing abnormal operations and grave consequences, and addressed the creation and
spread of viruses; article 287 covered crimes concerning the use of a computer to carry
out financial fraud, stealing, embezzlement, the appropriation of public funds, the
stealing of state secrets, and other like criminal activities (Keith & Lin, 2006, p. 123).
To keep up with the new development of Internet use, the Standing Committee of
the National People’s Congress further issued a Decision Regarding the Maintenance
of Internet Security in 2000. The 2000 Decision places cyber crimes within six catego-
ries: (a) crimes disrupting the safe operation of computer networks; (b) crimes of
using the internet to fabricate and disseminate information harmful to national secu-
rity and social stability; (c) crimes of using the internet to disrupt the socialist market
economic order and the management of social order; (d) crimes of using the internet
to violate personal, property, and other legal rights of individuals, legal entities, and
other organizations; (e) illegal acts, using the internet, that are not serious enough to
warrant CL97 punishment, but could not be alternatively punished under the 1986
Provisions on Administrative Punishment concerning the Management of Public
Security; and (f) civil infringement and liability committed while using the internet
that are not serious enough to be punished according to either the CL97 or the 1986
Liang and Lu 113
Provisions (Keith & Lin, 2006, p. 128). Besides these two major laws (CL97 and 2000
Decision), many administrative rules and regulations are also adopted to cover various
instances of cyber crimes.
Pornography and online gambling. Due to this comprehensive nature of China’s regu-
lation, an array of crimes are targeted by the Chinese authority such as online fraud,
selling illegal goods, libel, invasion of personal privacy, manufacturing and dissemi-
nating computer virus, online gambling, and pornography (Chen, 2004). Though
online fraud constitutes the largest group of cyber crimes, the Chinese official has paid
more attention to online pornography and gambling, because these types of moral
crimes are often viewed as serious challenges to socialist social order.
In 1996, the Chinese authority took its first action against pornography on the Inter-
net by adopting the Interim Regulations on the Management of International
Networking of Computer Information. Article 13 of the regulation stipulated that
“Organizations and individuals who get involved in Internet business shall abide by
national laws, administrative regulations . . . shall not browse, copy and disseminate
harmful information to public security, and pornographic materials and information.”
Online pornography was once again prohibited under Article 5 of the Computer Infor-
mation Network and Internet Security, Protection and Management Regulations
(December 1997). Section (6) of the Article 5 prohibits any organization or individual
from manufacturing, copying, browsing, and disseminating information that “propa-
gates feudal superstitions; disseminates obscenity, pornography or gambling; incites
violence, murder, or terror; instigates others to commit offences.” As usual, such regu-
lations on pornography could also be found among many other regulations (Gomez,
2004).
One frequent target of the antipornography campaigns is Internet cafés (wangba).
Since their first debut in 1996, Internet cafés have gained tremendous growth. The
proportion of Internet café users as China’s total internet population soared from 3%
in 1999 to 21% in 2001; the total number of registered cafés reached 64,000 in 2002
and the number of users rose to 16 million in 2004, though the percentage remained
relatively stable between 15%-20% from 2002 to 2004 (Hong & Huang, 2005, p. 379;
Qiu & Zhou, 2005, pp. 266-267). Besides registered Internet cafés, unregistered ones
in China are virtually uncountable. Though they are heavy targets in crackdowns,
unregistered cafés (heiba, literally “black bar”) remain popular and sometimes out-
number the registered one in some cities, and a total of 110,000 were estimated by the
end of 2003 (Hong & Huang, 2005). Many features of Internet cafés make them popu-
lar among Chinese young Internet users, such as the private-business nature, relaxed
regulation, low cost, convenience, and updated equipments and services. Gaming and
group chat are very popular among Internet café goers and some even search for cen-
sored information and express their political opinions with the assumption that it is
easier to hide their identities there (Hong & Huang, 2005). Nevertheless, online por-
nography and violent games are the primary concerns for parents and the government.
China’s definition on pornography and violence are much broader and the government
tries to stop both in the real and the virtual worlds.
114 Journal of Contemporary Criminal Justice 26(1)
Despite existence of various regulations (e.g., user registration, record keeping,
prohibition of smoking, filtering of gambling, and pornographic content, no entry for
those under 18, no Internet café in the vicinity of 200 meters of elementary and middle
schools), enforcement by café owners is very relaxed in practice (Qiu, 2003). The
government therefore has resorted to frequent crackdowns to clean up Internet cafés
since 2001. In 2002, for example, followed a deadly fire at an Internet café in Beijing
that killed 24, the government closed 3,300 cafés indefinitely and 12,000 others until
they improved their safety measures (Endeshaw, 2004); in 2003, another 27,000
unregistered cafés were shut down (Hong & Huang, 2005). Since 2003, the govern-
ment has also tried to push forward a chain-store model and hoped to tighten its control
through chain-store standard management (Hong & Huang, 2005; Qiu & Zhou, 2005).
The effect of such standardization, however, remains to be seen and it is unlikely that
the chain stores will take up the whole market, especially given the existence of many
unregistered cafés. In February 2007, 14 ministries and commissions further issued
the Circular Concerning Further Strengthening the Management of Internet Cafés
and Online Games, which regulates for the first time the virtual currency transaction
in online games (CNNIC).
In addition to physical control over Internet cafés, the Chinese government keeps
constant surveillance online via its infrastructural and technological equipments and
skills (e.g., blocking and filtering pornographic Web sites; Zittrain & Edelman, 2003),
and there are signs that the authority has stepped up such surveillance in recent years.
For example, the MPS in 2007 announced 10 major cyber crime cases that the author-
ity cracked in 2006 and 2007. Seven of the 10 were online obscenity, pornography,
and prostitution-related cases (News posted by Xinhua.net on April 13, 2007 at http://
news.qq.com/a/20070413/001256.htm, last retrieved on April 30, 2009). The CNNIC
also stepped up its role and has been exposing and cleaning up Web sites where por-
nographic, vulgar, and degrading contents were found. Twenty such Web sites were
exposed in the CNNIC’s ninth and tenth public postings this year, and even foreign
investors such as Google were targeted (see the People’s Daily, February 24, 2009;
http://news.sina.com.cn/c/2009-04-10/135817584966.shtml, last retrieved on April
30, 2009; the Straits Times, January 6, 2009).
Compared to pornography, online gambling is seemingly less prevalent in China
(especially given the increasing popularity of traditional gambling), but the scale and
impact of such crimes is still staggering. Citing data from the China Center for Lottery
Studies at Beijing University, Wang (2009) reported that more than 300 billion Yuan
(RMB) were transferred out of China and were invested in online gambling abroad in
2008 alone, and so did more than 600 billion Yuan in 2006. Systematic data and
research on online gambling are extremely lacking and the public only gains a glimpse
of the scale of such crimes through occasional news reports. On February 15, 2009, for
instance, the largest-ever Shanghai online gambling case was tried in Shanghai and
more than 20 defendants were sentenced to various terms of imprisonment. These
offenders reportedly managed to build a rather sophisticated online gambling scheme
and amassed more than 6.6 billion Yuan in 2006 and 2007 (Wang, 2009). As mentioned
Liang and Lu 115
above, much of online gambling action and funds was shoved abroad to avoid tight
control and severe punishment domestically, making governmental investigation more
difficult.
New crimes and regulations. In addition to traditional cyber crimes, China also strug-
gles with many new issues of Internet use. Take the “human flesh search” (renrou
sousuo in Chinese), for example, in the last few years. Though targeted online people
search started as early as 2001, the term did not draw enough attention until 2006. In
2006, a video clip was posted online in which a woman stomped a cat to death with
her high-heeled shoes. Once the clip was posted, angered Internet users initiated the
first mass search of the perpetrator. Soon she was found to be a nurse in Heilongjiang
province. Under the pressure, her hospital fired her and she had to make an open apol-
ogy for her misbehavior (information gathered and summarized from various internet
sources).
As the “kitten killer” fell as the first “victim”, “human flesh search” has quickly
become a powerful new tool by Web surfers to expose and hunt for immoral and
unethical individuals who are labeled “human flesh”. Although such a practice gained
more popularity and strength, concerns on potential abuse and invasion of people’s
privacy started looming. In December 2007, a white-collar worker, Jiang Yang, com-
mitted suicide by jumping off the 24th floor balcony of her apartment in Beijing. In
her blog (written before her death), she blamed her suffering to her unfaithful husband
Wang Fei and posted a picture of Wang and his new lover. After her death, angry Inter-
net users, led by a college classmate of Jiang, turned to “human flesh search”, posted
all detailed information of Wang and his family online in a short time, and even sent
Wang death threat emails and painted curses at his place. Wang lost his job as a result
and suffered tremendous distress. In March 2008, Wang sued three Web sites where
his information was posted for cyber violence and privacy violation. In February
2009, the people’s court in the Chaoyang district in Beijing ruled in Wang’s favor and
awarded him 8,000 Yuan. This trial is quickly labeled as the first case of “human flesh
search” and the first case of cyber violence, though public debates continue to support
or question the use of “human flesh search” (information from various internet sources;
Magnier, 2008; Wu, 2009). More recently in October 2008, Lin Ming, from Anhui
province, tracked down his ex-girlfriend Zhou Chunmei, whom he got to know online,
via “human flesh search,” and stabbed her to death in Xinxiang, Henan province. In
April, 2009, Lin was convicted of murder and sentenced to death by the Xinxiang
Intermediate People’s Court (information from various internet sources).
Facing rampant use of the “human flesh search,” many people including scholars
called for new regulation. While the central government is moving slow, local govern-
ments took the first action. In January 2009, Xuzhou city in Jiangsu province adopted
a new ordinance, the Computer Information System Security Protection Ordinance in
Xuzhou City. The new regulation specifically prohibits misuse of the “human flesh
search” and stipulates that violators could be subjected to a fine up to 5,000 Yuan and
banned from accessing Internet services. Internet users who favor the “human flesh
search” quickly question Xuzhou’s new regulation and believe that it will carry a
116 Journal of Contemporary Criminal Justice 26(1)
negative effect on Internet use and development in China (reports at http://tech.163
.com/09/0119/04/500BCRE0000915BF.html, last retrieved on May 1, 2009; the
Guangzhou Daily, January 20, 2009; Ye, 2009). Amid continuing debate, “human
flesh search” represents an example of Internet evolution in China and the government
will definitely face more such challenges in future.
Conclusion
Since China’s first global Internet connection in 1994, a mere 15 years has passed.
However, China’s Internet development in such a short time has been eye-catching
and China has already had the largest Internet users of the world by 2008. The impact
of Internet use and development has been enormous and it is evident in almost every
aspect of people’s lives in China. Such dramatic changes have left ample room for
scholars’ research, potentially covering a broad scope of issues and subjects.
Nevertheless, social studies on Internet use and development have been primarily
concentrated on the implications of the Internet for China’s democratization, and the
main concern is therefore state censorship, control, and regulation (Tsui, 2005). As we
reviewed in this article, the Chinese government has, from the very beginning, adopted
a “top-down, hands-on” approach in its plans and investments of telecommunications
industry and tried to facilitate the national economic growth and maintain its political
control at the same time. Tight control and regulation are implemented through a mul-
tidimensional approach involving multiple agencies and players and cover both
Internet infrastructure and commercial and social use. All these requirements and
measures eventually are backed up by various laws and regulations, aiming at a com-
prehensive control of Internet use and development.
Though there is strong hope internationally for China’s democracy potentially led
by Internet development, free flow of information, and formation of civil groups, an
increasing number of scholars are realizing that the Internet is a double-edged sword.
As a technology tool, the Internet cannot be isolated from social context in which its
use and development is inevitably intertwined with habits, beliefs, and values in a
specific culture (Tsui, 2005). The borderless nature of Internet information is also
subject to control of local laws and regulations within boundaries (Goldsmith & Wu,
2006). China’s testing case seems to prove just that. This is not, however, to deny the
great impact that the Internet has brought to the Chinese society. We have seen ample
evidence, especially in recent years, that the Internet empowers both the government
and the general public to move forward political-legal reforms. Indeed, the Internet
provides another tool for the public to better participate in such processes. To what
extent that this type of government–public e-interaction will lead to democratization,
however, still remains to be seen.
Although Internet use and development prompted economic development in China,
it also led to rising cyber crimes, a topic largely understudied. Similar to its approach
toward Internet regulation in general, the Chinese government combined its criminal
laws with many other administrative rules and regulations to cover cyber crimes com-
prehensively (online pornography and gambling are such examples). Besides
Liang and Lu 117
conventional cyber crimes, the Chinese government struggles with new phenomena
such as the “human flesh search” and ponders the costs and benefits of new legislation
and regulation. It is clear that China will face more challenges, both legally and politi-
cally, in its further transition in the new century, and the role of the Internet is still to
be unfolded.
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interests with respect to their authorship or
the publication of this article.
Funding
The authors declared that they received no financial support for their research and/or authorship
of this article.
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Bios
Bin Liang is an associate professor in the Department of Sociology at Oklahoma State
University–Tulsa. He has published numerous articles on crime and the legal system in China.
He is also the author of two books, titled The Changing Chinese Legal System, 1978—Present:
Centralization of Power and Rationalization of the Legal System with Routledge (2008) and
China’s Drug Practices and Policies: Regulating Controlled Substances in a Global Context
120 Journal of Contemporary Criminal Justice 26(1)
with Ashgate (2009). His current research interests include globalization and its impact on the
Chinese legal system, crime and deviance in China, and the drug court in Tulsa County,
Oklahoma.
Hong Lu is associate professor in the Department of Criminal Justice at University of
Nevada, Las Vegas. She has published extensively in the fields of sociology of law and
comparative criminology.
The Mismeasure of Crime
Mosher, Clayton; Miethe, Terance D.; Hart, Timothy C.
CHAPTER 5
VICTIMIZATION SURVEYS
Homicide victims are notoriously poor respondents to Census Bureau interviewers.
—Benjamin Renshaw (1990, p. 226)*
Another method of studying crime that arose in response to concerns about the limitations of official data was the victim survey. Instead of asking criminal justice system officials or offenders about criminal behavior, this approach asked people about their experiences as victims of crime. The first large-scale victimization survey appeared in the late 1960s. Since that time, they have been widely used to measure the frequency and characteristics of particular types of crime and the demographic profiles of victims, both in the United States and in other countries. By eliciting information about both crimes that citizens report to the police and those they do not, victimization surveys provide us with further information regarding the dark figures of crime. These surveys have also had a profound effect on theories of crime causation. Routine activity, opportunity, and even rational choice theory have flourished in the discipline of criminology in recent years in part because of the availability of victim survey data (Cantor & Lynch, 2000). However, as we will see in this chapter, similar to other measures of crime, victimization surveys have their own unique strengths and limitations.
Victimization surveys differ from other methods of measuring crime in their nature, their scope, and in the type of information collected. As implied by the basic definition, these surveys involve self-reports of victimization experiences by victims themselves, and as such, they are subject to many of the same problems associated with other forms of survey research. Victimization reports are usually elicited from random samples of the general public, and a variety of screening questions are utilized to identify different types of victims. A number of crimes addressed in other data sources—for example, prostitution and drug and alcohol offenses—are not covered in these surveys because they are considered to be victimless. In addition, in some crime situations, it is not possible to interview the victim; it is obviously not feasible to interview the victim of a homicide. Finally, some crimes, such as vandalism, are viewed as trivial and are not covered by these surveys; others, such as white-collar and corporate crime victimizations, are seen as difficult to accurately measure. This lack of coverage of certain types of crimes renders direct comparisons between victimization and official data problematic, an issue that will be addressed in more detail later in the chapter.
This chapter examines how victimization surveys have been used to measure crime. We begin with a review of the major victimization surveys used in the United States in the last five decades and proceed to describe the distribution of crime that emerges from a consideration of these surveys. We conclude with a discussion of the various problems associated with current efforts to accurately measure victimization experiences. While focusing on the findings from victimization surveys in the United States, we will include research from international studies where relevant, including the British Crime Survey and the International Crime Victimization Surveys, which shed light on the methodological weaknesses of this method of counting crime.
THE NATIONAL CRIME VICTIMIZATION SURVEY
As discussed in Chapter 2, surveys of crime victims in the United States developed during the mid- to late-1960s out of a concern with the weaknesses of official data in measuring the extent and characteristics of crime.
Given the initial success in using survey methods to provide information on victimization experiences, a number of additional pilot studies were conducted to address several important methodological questions: What is the ideal time frame for asking respondents about their experiences with victimization; how reliable is victimization recall; what is a suitable lower limit for the age of eligible respondents; and what are the advantages and disadvantages associated with mail or telephone interviewing methods versus in-person methods (Dodge & Turner, 1981)? These test studies aimed at validating and improving techniques used in victimization surveys were designed by the Law Enforcement Assistance Administration, in cooperation with the Census Bureau.
With insights derived from the earlier surveys, the National Crime Surveys (NCS) were initiated in 1972. The original NCS involved a national panel study of the victimization experiences of both households and individuals, as well as a number of surveys of particular cities. The initial NCS included samples of approximately 60,000 households (containing approximately 136,000 individuals) and about 15,000 businesses. The central-city surveys had samples of approximately 12,000 households in each of 26 cities; in addition, a probability sample of between 1,000 and 5,000 businesses was selected for each city. Both the national surveys of businesses and the city surveys of individuals were terminated in the mid-1970s on the basis of findings from external reviews that the sample was undersized, that the surveys were of limited utility as fielded, and that the surveys failed to collect information beyond that already gathered by the police, apparently due to their cost (Rennison & Rand, 2007). However, the national victimization survey of households, although having undergone several modifications over time, continues as an annual series.
Compared to official reports of crime, national victimization surveys have several advantages. These surveys, for example, have been perceived to provide more accurate measures of the absolute rates of some serious crimes and are believed to be more reliable than official statistics in analyzing crime trends in the United States (O’Brien, 1985). It is also believed that victim surveys provide more detailed information about the situational factors surrounding criminal acts—for example, the physical location of crime events; the day and time of events; the type of weapon used, if any; the number of victims and offenders; and the relationship between the victim and offender. General characteristics of offenders, such as their race, gender, and age in direct-contact predatory crimes such as assaults and robberies, can also be identified in victim surveys.
Procedures in the National Crime Victimization Survey
The National Crime Victimization Survey (NCVS) is the most comprehensive and systematic survey of victims in the United States.1 This survey has been designed and modified by the leading researchers and institutions in the country. The sampling procedure is supervised by the Census Bureau, the survey is conducted by well-trained staff and interviewers, and changes in the sampling design and format of questions are rigorously evaluated in terms of their effects on estimates of victimization experiences.
The basic procedures for selecting households to participate in victimization surveys have been essentially unchanged since the inception of the national survey. Recall that the goal is to obtain a nationally representative sample. The NCVS uses a complex, stratified, multistage cluster sample in which approximately 673 primary sampling units are initially identified by standard metropolitan statistical areas (SMSAs), a county, or small groups of contiguous counties. These clusters are then stratified with respect to important demographic characteristics, and sample elements (in this case, households) are selected from each stratum in a manner that is proportionate to their representation in the larger population.
The NCVS uses a rotating panel design. This means that sampled households are organized into panels. Each panel is divided into 6 groups so that interviews are ongoing throughout the year, thereby reducing seasonality effects. Residents of sampled households are interviewed seven times—once every six months for three years. After seven waves of interviews are complete, the panel is rotated out of the sample and replaced by a new panel of sampled households. It is important to note that although individuals are interviewed for the NCVS, it is a panel survey of housing units. This means that a housing unit remains in the sample even if the original residents of a household move during the seven interview waves. Although all this certainly sounds complex, the rotation pattern is designed with the goal of ensuring the representativeness of the sample.
In the earliest surveys, approximately 72,000 households were sampled. Over time, that number has decreased considerably. Twice during 2008, 42,000 households and 77,850 people age 12 or older were interviewed. The response rate for the survey was 90% of eligible households and 86% of eligible individuals. NCVS response rates for both household and individual surveys conducted between 1996 and 2008 are presented inExhibit 5.1
NCVS data collection instruments consist of three core items: (1) the Control Card (NCVS-500), (2) the Basic Screen Questionnaire (NCVS-1), and (3) the Crime Incident Report (NCVS-2). The Control Card provides the basic administrative record for each sampling unit, including information identifying the address of each sample unit and basic household data such as family income, whether the household unit is owned or rented, and the name, ages, race, sex, marital status, and education level of each individual living there. The Control Card also serves as a record of visits, telephone calls, interviews, and information about noninterviews (Biderman & Lynch, 1991).
An adult 18 years of age or older serves as the household respondent, providing answers to the basic questions on the Control Card, the Basic Screen Questionnaire, and, if necessary, the Crime Incident Reports for each victimization against the household (e.g., burglaries, motor vehicle thefts, and household larcenies). This individual also serves as a proxy for household members who are 12 or 13 years of age and whose parents do not allow the interviewer to speak to directly, for those mentally or physically unable to complete an interview, and for those who are unavailable for interview during the entire interview period.
The NCVS screening questions are designed to elicit information about whether particular incidents can be classified as a victimization, either for the household or the individual respondent. Screening questions are followed by more detailed questions about each incident identified as a victimization. The NCVS uses these screen questions to elicit maximum recall of victimization experiences, primarily by reducing respondent fatigue that can result from answering a large number of questions. As illustrated in Exhibit 5.2 and discussed in more detail later in the chapter, changes in the wording of these screen questions can affect respondent recall and alter subsequent estimates of victimization derived from the survey.
Incident reports in the NCVS involve a series of questions about the particular crime event, the offending parties, and the consequences of the crime. For each separate incident identified in the Basic Screen Questionnaire, respondents are asked, for example, whether the crime was reported to the police; whether the offense was completed or merely attempted; whether the offender was identified or known to the victim; the demographic (race, gender, age) characteristics of the offender, if known; whether there was a weapon used in the crime; whether the offender was a member of a gang or under the influence of drugs or alcohol at the time of the incident; whether the victim resisted; and the amount of monetary loss or physical injury, or both, that resulted from the victimization.
The NCVS is rigorous in terms of data collection procedures and processes. NCVS interviewers receive extensive training prior to conducting interviews, with explicit and detailed instructions about how the questionnaire is to be administered, adherence to question wording, and the use of probes to elicit answers from respondents. Quality control is further enhanced by periodic monitoring of the interviewers by supervisors, office edits of completed work, and verification of the data through re-interviews of some individuals. The use and refinement of these procedures have served to enhance the reliability of the NCVS data collection activities.
The 1992 Redesign of the NCVS
Recall that one of the major reasons for the development of the NCVS was to provide an alternative measure to official data of the extent and nature of crime in the United States, a measure that would also allow for comparisons over time. Researchers and staff involved with the NCVS have been reluctant to implement major changes in the design of the survey, fearing that this would compromise the over-time comparisons. However, as victimization surveys were subject to methodological critiques and as advances occurred in areas related to survey methodology more generally, it became increasingly clear that some changes were necessary in the procedures and practices underlying the NCVS. In the early 1980s, a consortium of experts in the fields of criminology, survey design, and statistics was organized to reexamine all aspects of the survey, including questionnaire design, sampling strategies, administration, errors, dissemination, and utilization of the NCVS data (Biderman & Lynch, 1991; Lehnen & Skogan, 1984; Taylor, 1989).
Three separate phases were identified in the possible redesign of the NCVS. The first phase was directed at immediate improvements that could be made in the survey. The second phase emphasized the development of so called near-term changes (e.g., alterations in the use of proxy interviews, incident form changes, the use of computer assisted telephone interviewing, and cost-saving changes) that could improve the NCVS without incurring significant financial costs or disrupting the time series. The third phase involved more fundamental, long-term changes that could dramatically increase the quality of the data or reduce the costs of data collection or both.
As described by Biderman and Lynch (1991), the Crime Survey Redesign Consortium proposed the following set of recommendations for implementation in the near term:
Screening and Scope Changes
Include vandalism in the NCVS, and interview 12- and 13-year-olds directly instead of by proxy.
Expanding Incident Descriptions
(a) Revise place of occurrence codes so that there are consistent distinctions regarding the “publicness” of places or their exposure, (b) add codes to specifically identify crimes occurring in the respondent’s town, (c) obtain information on victim-offender interactions, and (d) expand information on the outcomes of victimization incidents, such as the response of the criminal justice system and other agencies.
Expanding Explanatory Variables
(a) Place supplements in the survey that can be used to distinguish victims from non-victims, and (b) collect more information on the perceived motivation of offenders, including the role of substance use
Changing Crime Classification and Reporting
(a) Use the current collection period for preliminary estimates that can be disseminated in a more timely fashion, (b) adjust annual estimate rates for the major sources of measurement error, and (c) increase the power of statistical tests used in the NCVS. (p. 19)
After various types of design work and field-testing by the Census Bureau, most of these recommendations were accepted by the Bureau of Justice Statistics and were subsequently introduced into the NCVS design in 1986. However, they were limited to those changes that “would not significantly affect the amount or type of crime measured by the survey” (Rennison & Rand, 2007, p. 34); in addition, the scope of crimes covered in the NCVS was not expanded to include vandalism, primarily because it was believed that such a change would disrupt the series and cause difficulties in comparing victimization data over time.
The Redesign Consortium also recommended various changes in the NCVS to be implemented over the long term. These recommendations focused on the design of the survey and carried substantial implications for survey costs and data quality.
Quality Enhancements
(a) Make the NCVS a longitudinal survey of individuals rather than housing units, (b) use a four-month instead of a six-month reference period to reduce the underreporting of victimization events, (c) use interview-to-interview recounting to simplify the recall task rather than recounting to the beginning of the month in which the interview is conducted, (d) employ more productive short-cue screen questions to encourage more complete reporting of victimizations, and (e) use centralized telephone interviews to enhance control over interviewers.
Cost Reducing Changes
(a) Maximize the use of telephone interviewing, which is less expensive than in-person interviews, and (b) use data from bounding interviews for estimation purposes. (Bounding interviews are the first interviews conducted with a household in which questions about victimization experiences are asked, but there is no specific reference period to the previous interview.)
Some of these long-term recommendations have been phased into the NCVS. For example, in 1988, centralized telephone interviewing was initiated at the same time as the use of the new survey instrument, and computer assisted telephone interviewing (CATI) technology is now used in five of the seven waves of the NCVS interviews. However, due to cost considerations, the six-month reference period rather than the recommended four-month period is still used. Given the importance of maintaining continuity in the NCVS series, the 1992 redesign was structured to assess the impact of the various changes in the survey instrument and procedures on inflating or deflating national estimates of victimization. That is, for 1992 through the first six months of 1993, data from half the sample were collected using the NCS methodology, and data from the other half were collected using the redesigned NCVS methodology (Rennison & Rand, 2007). Changes in the NCVS procedures that have had minimal effects on estimated victimization rates include modifications in the wording of several existing questions, expansion of the list of questions in the survey to include perceived drug and alcohol use by offenders, self-protective measures taken by victims, police actions, victim contact with the justice system, the location of the crime, and the victim’s activity (Bachman & Taylor, 1994).
Research comparing pre-redesign and post-redesign data indicates that changes in the nature and coverage of screening questions, which was one of the most important changes to the NCVS; changes in the definition of series crime; the increased use of telephone interviewing; and changes in the classification of crimes have substantially altered the recall of victimizations. In fact, when changes in the NCVS were implemented in 1992, the number of crimes reported by survey respondents increased by 50% to 200%, depending on the type of crime (Cantor & Lynch, 2000). Most of these changes have been viewed as positive improvements in that the enhanced screening questions are thought to better stimulate respondents’ recall of victimizations. These questions serve to clarify crime victimization incidents and diminish the effects of respondents’ subjective interpretation of survey items. In addition, the enhanced questions and inquiries about experiences of domestic violence, rape, and sexual attacks are believed to provide better estimates of these victimizations, which are often difficult to measure. The new screen questions also expand cues that assist respondents in recalling an incident, such as items that ask about being a victim of a violent crime committed by someone the victim knows (such as co-workers, neighbors, and family members) and questions for burglary regarding how the offender entered the structure. The following consequences have been observed in studies on the impact of these procedural changes (Bureau of Justice Statistics, 1994; Kindermann, Lynch, & Cantor 1997).
CATI and Use of a Centralized Phone Facility
These procedures are believed to help standardize the interviewer respondent interactions, leading to the greater reporting of victimizations and more realistic crime rates. The use of CATI has increased the reporting of crimes of violence, crimes of theft, and household larceny by approximately 15% to 20% and burglary by about 20%. CATI’s effect on the reporting of motor vehicle theft has been negligible.
Changing Definitions of Series Crimes
Series crimes are similar but separate crimes that the victim is unable to recall individually or describe in detail to an interviewer. Older versions of the NCVS used three crimes as the minimum limit for a series, but the redesign changed the number to six similar offenses. Under this change, if a respondent reports three to five similar incidents to an interviewer, data on each incident are collected. For most types of crime, it is estimated that this change in the definition of series crimes increases the rate of crime by only 1% to 5%. However, for assaults, especially situations of domestic abuse, and some types of theft, the increase in crime rates may be in the 10% to 15% range.
Reporting Crimes to the Police
A lower percentage of crimes identified in the redesigned NCVS are now being reported to the police than in previous versions. This change is attributed to expanded cuing of less serious crimes (which are less likely to be reported to the police) in the redesigned survey.
Changes in Crime Classification of Personal and Household Larceny
Under the older versions of the NCVS, larceny was defined according to the location in which it occurred, with household thefts involving stolen items on the grounds of the home and personal thefts involving items stolen someplace away from the home. Under the redesign, all thefts are classified as household thefts unless there was contact between the victim and offender. Accordingly, the number of household thefts increased and the number of personal thefts decreased as a consequence of the redesigned coding procedures.
Overall Effects on Victimization Estimates
Kindermann et al. (1997) indicated that the impact of the redesign varies by the type of crime. In particular, the redesigned NCVS yielded higher estimates of crime rates for the following offense types: personal crimes (increase of 44%), crimes of violence (increase of 49%), rapes (increase of 157%), assaults (increase of 57%), property crimes (increase of 23%), burglaries (increase of 20%), and thefts (increase of 27%). No substantial differences were observed for rates of robbery, personal theft, and motor vehicle theft.
Redesign Effects on Select Population Subgroups
The redesign procedures had different effects on the victimization rates for particular subgroups. For crimes of violence, the redesigned NCVS elicited more recounting of victimizations for whites than for blacks, for 33- to 44-year-olds than for other age groups, for persons with household incomes of $15,000 or more than for lower-income persons, and for suburban residents more than urban residents. Rates of household crimes were recounted more for suburban than rural residents through the use of the new procedures, and higher rates of burglary were elicited from black than white respondents in the redesign (Kindermann et al., 1997).
These research findings indicate that the continuity of the NCVS series was compromised by changes in the screening questions and classification procedures, which leads to difficulties in comparing victimization rates over time. As is done in many published reports using NCVS data, it is possible to make adjustments to the pre-redesign and post-redesign series to increase their comparability. However, it is also likely that a number of these changes have complex interaction effects that vary across particular combinations of offense, victim, and method attributes. If these interaction effects are not fully incorporated in the estimation procedures, current adjustments in the NCVS data may not necessarily enhance the comparability of the two data panels.
National Academy of Sciences
Assessing the utility and methodology of the NCVS did not stop after the 1992 redesign. Recently, the Bureau of Justice Statistics commissioned the National Academies’ Committee on National Statistics (in cooperation with the Committee on Law and Justice) to consider alternative options for conducting the NCVS (Groves & Cork, 2008). In response, several preliminary recommendations were made, including the following:
Changing from a six-month reference period to a 12-month reference
Streamlining the incident form (either by eliminating items or by changing their periodicity)
Using advanced statistical methods to construct and disseminate sub-national estimates of major crime and victimization rates
Developing, promoting, and coordinating subnational victimization surveys through formula grants funded from state or local assistance resources
Investigate the introduction of mixed mode data collection designs (including self-administered modes) into the NCVS
Since the Academies’ report, due to budget constraints, three major changes to the NCVS have occurred: (1) data from the first interview— previously withheld as a bounding case—began being used in annual estimates; (2) The Bureau of Justice Statistics implemented a 14% sample cut, as a balance for using the bounding first interviews; and (3) the Bureau of Justice Statistics suspended all CATI from Census Bureau call centers. (However, field interviewers may still use the telephone to conduct their scheduled interviews.) Phase-in of these and other minor changes resulted in a break in series between 2006 and previous years that prevents annual comparisons of national crime victimization rates (Rand & Catalano, 2007).
VICTIMIZATION RATES AND CHARACTERISTICS OF THE VICTIMS, OFFENDERS, AND INCIDENTS
One basic indicator of crime prevalence used in the first 20 years of summary reports of NCVS trends was the proportion of households touched by crime. From 1975 to 1992, the estimated proportion of U.S. households that experienced any type of victimization in the previous year decreased steadily from about 32% to approximately 23% (Zawitz et al., 1993). In 2005, the estimated proportion of households experiencing any type of victimization was only 14%. Only about 1 in 36 households in the United States experienced one or more violent crimes in 2005 (Klaus, 2007).
Examining the NCVS data from 1973 to 2006,2 it is clear that rates of criminal victimization in the United States have exhibited patterns of stability and change over time. Victimization rates for crimes of violence (e.g., assaults, robberies, and rapes) hovered around 50 per 1,000 persons age 12 or older in the late 1970s to the early 1980s, decreased somewhat during the mid- to late-1980s, increased until the mid-1990s, and steadily declined from 1994 to 2005 (see Exhibit 5.3). As noted above, the Bureau of Justice Statistics recommends that 2006 NCVS data not be used when making yearly trend comparisons.
NOTE:
1973–1991 data adjusted to make data comparable to data after the redesign. Estimates for 1993 and beyond are based on collection year while earlier estimates are based on data year. Due to changes in methodology, the 2006 National Crime Victimization rates are not comparable to previous years and cannot be used for yearly trend comparisons. However, the overall patterns of victimization at the national level can be examined. Property crime rates based on the NCVS data have exhibited a steady decrease over the last 30 years (seeExhibit 5.4). The most common property crimes experienced in the United States are household thefts, followed by residential burglary and motor vehicle thefts. Property crime rates have decreased from 520 per 1,000 households in 1973 to 160 per 1,000 households in 2006. Among specific property crimes, thefts from the household decreased more than twofold, from 391 to 122 per 1,000 households between 1973 and 2006. Burglary rates in 2006 were almost three times lower than their rate in 1973, and rates of motor vehicle theft are more than two times lower over this period.
NOTE:
1973–1991 data adjusted to make data comparable to data after the redesign. Estimates for 1993 and beyond are based on collection year while earlier estimates are based on data year. Due to changes in methodology, the 2006 National Crime Victimization rates are not comparable to previous years and cannot be used for yearly trend comparisons. However, the overall patterns of victimization at the national level can be examined. For additional information about the methods used, see Criminal Victimization 2006.Findings from the NCVS indicate that the risks of victimization are not uniform across different demographic subgroups (see Exhibit 5.5). With the exception of rape or sexual assault, men are victims of violence at significantly higher rates than women. On the basis of comparisons with NCVS data in the 1970s and 1980s, the magnitude of gender differences in the risk of violent victimization has exhibited little change over the last 30 years.
*Includes American Indians, Alaska Natives, Asians, Native Hawaiians, and other Pacific Islanders.
Blacks experience violent victimization at higher rates than any other singular racial group for every violent crime measured by the NCVS. While only 1% of the U.S. population identified itself as being of more than one race in 2008, these individuals were victims of violence at rates 2 to 3 times that of any other race. Persons of Hispanic origin experience violence at slightly lower rates than do non-Hispanics (Rand, 2009).
In general, there is an inverse relationship between age and violence. That is, as age increases, rates of violence decrease. The highest rates of simple assault, for example, involve juveniles between the ages of 12 and 15 and are significantly higher than among persons age 25 or older (Rand, 2009). Over the last 10 years, NCVS data indicate that rates of violent victimization for younger teenagers (aged 12–15) have increased more rapidly than for any other age group. As a group, teenage black males are especially vulnerable to violent victimization (Zawitz et al., 1993).
Major demographic differences also are apparent when property victimization is considered (see Exhibit 5.6). For example, households headed by blacks experienced property crimes at rates significantly higher than households headed by any other single racial group. Households headed by Hispanics had higher rates of property victimization than non-Hispanic households. Rates of property victimization also decreased as household income increased. The higher risks of property victimization for each of these demographic groups are also found across specific types of property crimes.
*Includes American Indians, Alaska Natives, Asians, Native Hawaiians, and other Pacific Islanders.
NCVS data provide the additional opportunity to examine particular characteristics of criminal offenses and those who commit the crimes. As shown inExhibit 5.7, these offense and situational characteristics for violent crimes include whether the act was completed or merely attempted, the number of offenders involved during the incident, the victim-offender relationship, the time of day, whether a weapon was used, whether the incident was reported to the police, and the victim’s perception of their attacker’s sex, race, age, and drug or alcohol use (Bureau of Justice Statistics, 2010).
*Includes attempted rape and verbal threats of rape only.
**Based on incidents where only one offender was present during the victimization.
***Simple assault, by definition, does not involve the use of a weapon.
Detail may not sum to 100% due to rounding.
The vast majority of violent offenses derived from the national victimization data involve attempted or threatened rather than completed offenses. (Note: Assaults are not classified as attempted or completed but as incidents with or without injury.) Most robberies and sexual assaults, for example, involve completed rather than attempted offenses. Violence involving multiple offenders is the exception in violent crimes reported in the NCVS. In 2007, about 8 out of every 10 violent victimizations involved a single offender.
The most common interpersonal relationship between the victim and offender in violent crimes depends on the particular type of offense. For all violent offenses combined in the NCVS data, the majority of victims (51%) report that the offenders are strangers. Offenses committed by strangers are most common in robberies (80%) and aggravated assaults (58%). The proportion of violent victimizations that involve nonstrangers is the highest among rapes or sexual assaults (58%), followed by simple assaults (55%).
When an incident occurred, whether a weapon was involved, and how a victim responded during violent crime are also important components of violent situations that can be better understood by examining data produced by the NCVS. For example, while most simple assaults occur during the daytime (i.e., 6 a.m.–6 p.m.), most rapes or sexual assaults, robberies, and aggravated assaults occur in the evening hours (i.e., 6 p.m.–6 a.m.). In addition, about two thirds of all violent victimizations in 2007 did not involve the use of a weapon, which was especially true of rapes or sexual assaults. More victims of violence take some sort of self-protective measure (i.e., fighting back, shouting for help, etc.) during the incident than do not. This is true for overall violence in general and for each particular type of violent crime.
Victims of direct-contact crimes are sometimes able to provide demographic information about their attackers. Unless the suspect is thwarted in the attempt or subsequently apprehended, victims of property crime are typically unable to provide this type of information. According to 2007 NCVS data on single-offenders of violent incidents, the vast majority (76%) are identified as males by their victims; this rate for male offenders was highest for rape or sexual assault (95%) and lowest in cases of simple assault (71%). Most offenders are more likely to be identified as white by their victim than any other race. And persons under 30 years old are more commonly identified as the offender than older persons for all types of violent incidents.
Although many victims are not able to be certain, when victims can ascertain the state of an offender, victims perceive them to be under the influence of either drugs or alcohol in approximately half of all violent incidents. Rates of perceived substance use are highest in rape or sexual assaults (37%) and lowest during robbery incidents (18%).
As a measure of the dark figures underlying official data, NCVS data from 2007 reveal that about half of all violent crimes are not reported to the police. Most rapes or sexual assaults (58%) as well as most simple assaults (58%) were not reported to police in 2007. Despite this level of unreported crime, the trend in crime reporting for both overall violent and property crime appears to be fairly stable but increasing somewhat over the last two decades (see Exhibit 5.8). For example, on average, between 1992 and 1993, 43% of all violent crimes and 33% of all property crimes were reported to police, according to the NCVS. In contrast, between 2006 and 2007, crime victims indicated that 48% of all violent incidents and 38% of all property crimes were reported.
Different factors are associated with the relative likelihood of crimes being reported to police. In particular, the likelihood of reporting crime is higher for the following factors: (a) completed acts versus attempted acts, (b) crimes involving injury versus those without injury, (c) crimes committed by strangers versus nonstrangers, and (d) when a weapon is present. Particular groups of people also have higher reporting rates than others. For example, violence against females is more likely than violence against males to be reported to the police for both violent and property crimes. Violence against black victims for both types of crimes is slightly more likely to be reported than is violence against white victims (Hart & Rennison, 2003).
Reasons for not reporting crimes to the police vary according to the type of offense. The most commonly given reasons for not reporting violent offenses are that “the crime was a personal or private matter” and that “the offender was not successful.” For property offenses, the most common reasons for not reporting were that “the object was recovered,” “the offender was unsuccessful,” “the police would not want to be bothered,” and “lack of proof” (Baumer & Lauritsen, 2010; Hart & Rennison, 2003; Lauritsen, 2005; Rennison & Rand, 2007).
OTHER VICTIMIZATION SURVEYS
In addition to national studies, research in the last four decades has included a diverse array of smaller-scale victimization studies, usually focused on particular types of crime within specific jurisdictions. Surveys of victims of domestic violence and sexual assault are widely recognized as an important measurement strategy due to the significant underreporting of these crimes in official data sources. College campus surveys, statewide surveys of quality of life, and local surveys of neighborhood revitalization and development often also include measures of victimization experiences. In addition, Gallup polls and national surveys such as the General Social Survey, conducted by the National Opinion Research Center, also frequently include items on victimization; the National White-Collar Crime Center has conducted multiple surveys of individuals over the last several years about their experiences as victims of white-collar crime (Kane & Wall, 2006); and recent supplements to the NCVS have captured information related to cybercrime experienced by businesses (Rantala, 2008).
Although useful for their particular purposes, small-scale victimization surveys are often less comprehensive than national surveys, and they are usually based on smaller samples. Low response rates and selective sampling frames also limit the generalizability of sample estimates from such studies.
INTERNATIONAL VICTIMIZATION SURVEYS
In addition to national and subnational victimization surveys, there is a growing interest in victimization surveys in other countries. These surveys vary in both size and specific design features (see Exhibit 5.11). For example, unlike the NCVS, victimization surveys conducted in Australia, Canada, England and Wales, Sweden, the Netherlands, Scotland, Switzerland, and Ireland use a 12-month reference period and do not use bounding techniques to reduce telescoping. In addition, among these countries, only England and Wales, Sweden, Scotland, and Ireland interview respondents in person. In contrast, Australia and the Netherlands rely on self-administered questionnaires to collect their victimization data.
Variation in international victimization survey design, crime definitions, and legal codes makes cross-national comparisons of victimization estimates produced from these surveys difficult. Nevertheless, experts have attempted to produce compatible information from these surveys for certain types of crimes (Farrington, Langan, & Tonry, 2004). For example, results from international victimization surveys from the countries listed in Exhibit 5.9 show that between 1980 and 2000, Australia consistently had the highest burglary rate, while Switzerland and Sweden were the countries with the lowest(see Exhibit 5.10). Canada and the Netherlands were the countries whose surveys produced the highest estimates for robbery, compared to Scotland, which until the mid-1990s, had the lowest rate of robbery victims (see Exhibit 5.11).
PROBLEMS WITH VICTIMIZATION SURVEYS
Large-scale public surveys of victims are widely regarded as an alternative measure of the true extent of crime in a jurisdiction because they provide estimates of both reported and unreported offenses in a particular time period. Similar to official data and self-reports of criminal behavior, however, victimization surveys are limited by basic restrictions on their scope and are susceptible to major conceptual and methodological problems that contribute to their mismeasurement of crime. Several of these issues are addressed in the sections that follow.
Limitations on the Scope of Crimes Covered
One immediate problem with victimization surveys as a measure of the distribution and nature of crime is that they can only capture criminal offenses involving victims. By definition, victimless crimes—such as drug and alcohol violations, prostitution, and gambling—are excluded from victimization surveys.3 Other criminal offenses—such as illegal weapon possession, tax evasion, murder, and crimes in which a business or commercial establishment is the victim (e.g., nonresidential burglary, bank robbery, employee theft, corporate collusion, and industrial theft), consumer fraud, possession of stolen property, and a host of public order offenses (e.g., trespassing, disorderly conduct, breach of peace, curfew violations)—are also excluded from these surveys.
The restricted scope of crimes covered in victimization surveys becomes problematic because the included crimes represent only a small minority of all criminal offenses that may be of interest to criminologists and policy makers. For example, based on official data on crime in the United States, the most common arrests involve drug- and alcohol-related crimes (e.g., possession of a controlled substance, public drunkenness, liquor law violations, driving under the influence of alcohol), and a sizable proportion of robberies (27%), burglaries (37%), and larcenies (12%) are crimes committed against the property of businesses rather than individuals (Biderman & Lynch, 1991). By excluding these major and frequently occurring forms of crime, existing public surveys of victims are limited to only a relatively small subset of crimes.4
Conceptual and Definitional Problems
Even among the subset of personal and property crimes included in victimization surveys, this measure of crime suffers from conceptual ambiguity regarding how crimes are defined by the researcher and the respondent. Differential perceptions of crime across individuals that derive from competing conceptualizations of criminal acts contribute to measurement error in the coding and counting of victimizations.
One serious problem in victim surveys that limits their comparability with official counts of crime involves the basic definition of crimes used in each data source. Specifically, victimization surveys use a potentially more inclusive definition of some types of crime than police reports because victim surveys include incidents that may be legally justified (e.g., self-defense assaults) and incidents lacking the basic necessary elements for legal culpability (e.g., criminal intent, particular injuries, or monetary loss). By simply counting as violent crime “any attack or threat or use of force by anyone at all” without an examination of the context of the event, victimization surveys may provide us with a distorted image of the prevalence of particular types of crimes. The tendency for victimization surveys to include many noncrimes and trivial offenses is well documented (Biderman & Lynch, 1991; O’Brien, 1985; Skogan, 1981).
Different definitions of crime across cultures and social groups are another fundamental problem with victimization surveys. Although the magnitude of bias in these surveys from differential interpretations of questions has not been empirically assessed, there is undoubtedly much variation in the meaning of particular words and phrases for members of different demographic groups. For example, the new screening questions in the NCVS use words such as attacked or threatened to cue memories about victimization experiences, but the subjective meaning attached to these terms varies widely. Is the act of brandishing a firearm or knife a threat of violence? Is someone attacked when it is a situation of mutual combat? How do respondents in victimization surveys interpret situations of grabbing, punching, or choking done in the context of either male or sibling roughhousing or of physical banter among peers or spirited athletic contests (like football,hockey, and basketball)? Is it reasonable to assume that no major gender, age, race, social class, or cultural differences exist in the interpretation of what constitutes a threat or attack? Similarly, wording for the property offense questions such as burglary (e.g., Has anyone broken in or attempted to break in your home?) and motor vehicle theft (e.g., Has anyone stolen or used without permission your vehicle?) are also subject to differential interpretations. Under these conditions, estimates of the prevalence of violent or property crimes are likely to be distorted.5
By failing to include reference to the particular context in which threats or attacks take place, most victimization surveys further compound measurement error stemming from differential interpretation of questions on the part of respondents. The NCVS redesign has attempted to deal with this problem by including screening cues about the offender or place of the crime (e.g., attacked by someone at work or school, a neighbor or friend, a relative or family member, while riding in a car, on the street or in a parking lot). Unfortunately, these contextual cues are still not necessarily standardized across different groups because the meaning that should be attached to words and phrases such as attack, threaten, grab, punch, have something stolen from you, break in, and use without permission that underlie questions about an individual’s victimization experiences is not addressed. Regardless of how refined the objective meaning attached to these terms is by researchers, they remain prone to varied subjective interpretations by respondents.
Methodological Problems
In addition to conceptual and definitional limitations, current victimization surveys suffer from numerous methodological problems that further call into question the accuracy of estimates of victimization rates, subgroup variation in these rates, and the measurement of the characteristics of offenders, victims, and crime incidents. These methodological problems involve both simple and complex issues of sampling (e.g., sampling error, sampling bias, characteristics of nonrespondents), survey research (e.g., interviewer effects,telephone vs. personal interviews, social desirability, reference period), and technical procedures used in the calculation of rates (e.g., appropriate numerators and denominators, series incidents).
Sampling Issues
National victimization surveys use the responses of a sample of residents to estimate rates of victimization for the entire population. Unfortunately, whenever samples are used to represent populations, there is always the possibility of a discrepancy between the sample estimates and the true population parameters. When this discrepancy is due entirely to the properties of random sampling, it is referred to as sampling error. The discrepancy is referred to as sampling bias when it derives from sources other than random sampling. Both sampling error and sampling bias are characteristic of victim surveys.
Sampling error results in fluctuations in estimates of national victimization rates. For example, the reported 2000 NCVS rate of violent victimization of 28 per 1,000 persons 12 years of age and older is our best single guess of the true rate of violent victimization in the United States. However, we cannot be certain of the absolute accuracy of this estimate because it is based on a sample, rather than the entire population. It is quite possible that another random sample of U.S. households for the same period would yield a markedly different estimate of violent victimization.
As discussed inChapter 4, as a strategy for correcting the effect of sampling error, statistical theory about probability sampling tells us that in the long run, these sample estimates will converge on the true value in the population. Information from the sample and estimates of sampling error can then be used to develop a range of values in which the true population parameter is likely to fall. Unfortunately, even with the construction of such confidence intervals, there is no guarantee that the estimates derived from a particular sample necessarily reflect the true population values. Of course, these are issues associated with survey research in general and are not specific to victimization surveys.
All other things being equal, large samples are preferred over small samples because sampling error decreases as sample size increases. Given the relatively large size of NCVS samples (approximately 60,000 households), we have far greater confidence in their estimates than other victimization surveys.
Several sources of sampling bias have been identified in victimization surveys. For example, particular groups of people are less likely to participate in victimization surveys than others, and the excluded groups tend to be more prone to victimization. In the NCVS, homeless persons, young males, and members of minority groups are less likely to be included, and each group has higher risks of victimization than their older, female, and nonminority counterparts (Skogan, 1978). At the other extreme, the very wealthy are probably under represented in victimization surveys because of their ability to isolate themselves from interviewers (Garafalo, 1990). Nonrandom differences in response rates in surveys across social groups (e.g., lower response rates among minority and inner-city residents compared to other groups) is another source of sampling bias in victimization research. For the NCVS, nonresponse rates are highest for young non-white youth, the population subgroup with the highest victimization rate. This confounds this issue of producing unbiased estimates for this and other subpopulations with high nonresponse rates (see Exhibit 5.12). The exclusion of victimization experienced by businesses and crimes against the government in household victimization surveys can also be interpreted as a source of sampling bias that dramatically lowers estimates of national victimization rates. Although adjustments for sampling bias are sometimes made in national estimates, there is no universally accepted method of adjusting for this source of error, and many of the correction factors that are used are based on rather dubious assumptions about the nature of the excluded cases.
Survey Research Issues
Survey research is an ideal data collection strategy for victimization studies because surveys are best designed to describe a characteristic in a population. Unfortunately, survey responses are affected by a wide variety of factors that alter the accuracy of estimates of victimization rates. These problems with survey research include differences across the mode of administration of surveys, question wording and reference periods, and the basic limitations of human judgments.
One basic issue in victimization surveys involves whether to collect data through a telephone or face-to-face interview. Telephone surveys have the advantage of being cheaper and quicker to implement. When the interviews are conducted by reading the survey questionnaire from the CATI and are monitored in a central facility, telephone surveys provide greater assurances of uniformity and standardization. Greater anonymity for respondents is also provided through telephone interviewing, which may generate more truthful answers to sensitive questions. In contrast, face-to-face interviews are believed to provide higher response quality because trained interviewers can maximize the use of various visual and nonverbal cues to ask more complicated questions and to determine whether the respondent understands the questions. Both telephone and face-to-face interviews have been used in national and international victimization surveys. For example, only the first interview of the head-of-household respondent surveyed for the NCVS requires a face-to-face interview. (Note: Although not required, if available the other household members also will complete a face-to-face interview.) For the remaining interviews with the head-of-household respondent and with all others residing in the sampled household, the interviews are conducted via the telephone if the respondents are agreeable and have a telephone.
In terms of the accuracy of information and eliciting victimization incidents, several general statements can be supported from previous research comparing telephone and face-to-face interviews. First, there is no convincing evidence that telephone surveys provide less accurate information about crime victimization than personal interviews in the NCVS (Biderman & Lynch, 1991). However, differences across methods in the NCVS projects are probably smaller than in other surveys because of the extensive training and monitoring that is done in the NCVS for both telephone and face-to-face interviewers. Second, the use of CATI from a centralized telephone facility has been found to increase the number of reported crimes for at least some offenses. As mentioned earlier, the use of CATI increases estimates of the rates of crimes of violence, crimes of theft, and household larceny by approximately 15% to 20% and burglary by about 10%, but it has only a marginal impact on reports of motor vehicle theft (see Bureau of Justice Statistics, 1994). CATI is presumed to yield higher and more realistic estimates of crime rates in victimization surveys by enhancing administrative control over the interview process. Under these conditions, differences across studies in the type of survey method utilized and changes over time in the increased use of telephone interviewing makes rather dubious many comparisons of the estimates of victimization rates over time.
Another major issue in survey research involves question wording and response formats. This issue has been raised most pointedly in victimization surveys within the context of the type and nature of screen questions as well as the reference period for the reporting of victimization experiences.
Both incident rates and subgroup variation in victimization risks are affected by the particular screen questions used to elicit reports of victimization experiences. Short screen questions may cue a respondent’s recall of only a small subset of incidents that involve the most serious or frequent violations, whereas longer screens encourage the recounting of a fuller range of experiences across various contexts.
When compared to results using the pre-redesign NCS instrument, the redesigned survey (which includes new screens and enhanced questions) yields substantially higher estimates of victimization rates for particular crimes. Specifically, changes in the survey wording resulted in a dramatic increase in the estimated rates of personal crimes (44% increase), crimes of violence (49% increase), assaults (57% increase), and rapes (157% increase). However, the redesigned survey did not substantially affect estimated rates for robbery, personal theft, or motor vehicle theft (Kindermann et al., 1997). The new method also had a significant impact on estimates of crime committed by nonstrangers, attempted acts, and those offenses that were not reported to the police. As mentioned previously, the recalling of violent crimes in the redesigned survey was higher for the following groups: whites, mid-aged residents (35–44 years old), persons with higher incomes, and suburban residents.
Estimates of victimization rates are also affected by the length of the reference period used in the survey. Intuitively, longer time periods (e.g., asking about victimization experiences in the previous five years) will elicit more incident reports than a shorter time period because of the greater time at risk for victimization. However, survey respondents who are asked retrospective questions may also report an incident as occurring earlier than it actually did. Although this telescoping of the reference period may be due to faulty memory or an unconscious effort to please interviewers, it is a serious problem in any survey that attempts to elicit information about past events.
Surveys that use a reference period of one year or more are susceptible to forward telescoping (i.e., remembering events as occurring more recently than they actually occurred). The six-month reference period used in the NCVS makes this survey prone to backward telescoping (i.e., remembering incidents as having occurred in a more distant past). However, historically, both types of telescoping were minimized in the NCVS data through the process of the bounding interview, in which the first interview of a household serves as a baseline for anchoring the recall period. When re-interviewed after six months, NCVS respondents were asked about incidents since the last interview, and repeated incidents could be filtered out. Incident reports from the first interview of a household in the NCVS panel were not used in the estimation of national rates because they are unbounded and susceptible to telescoping. Biderman and Cantor (1984) suggested that the failure to bound incidents in the NCVS would increase the number of estimated victimizations by almost 50%. Recently, however, the initial, unbounded interviews have been included in the NCVS annual victimization estimates; and advanced statistical procedures suggest the impact of including unbounded interviews is less severe (Addington, 2005; Rand & Catalano, 2007)
This bounding procedure may be a partial solution to the problem of telescoping, but it does not correct several other potential response effects often found in panel studies. For example, and unlike cross-sectional surveys, subjects in panel surveys are interviewed repeatedly. Their responses to survey items may be at least partially dependent on the previous interview experience (Lehnen & Reiss, 1978). However, recent studies suggest that repeated exposure to multiple waves of NCVS interviews does not lead to more people refusing to participate in the survey (Hart, Rennison, & Gibson, 2005).
Decisions regarding which reference period to use in victimization surveys are often based on balancing the issues of telescoping, sample size, and financial costs. Forward telescoping is minimized by a shorter recall period, but this choice also requires the use of larger and ultimately more expensive samples to uncover a sufficient number of individuals who have recently experienced a victimization. Unfortunately, the use of different recall periods and bounding procedures limit the ability to make over-time comparisons of large-scale victimization surveys such as the NCVS.
In addition, because victimization surveys rely only on the report of the victim, the data may be distorted by variations in how respondents define crime. In the 1976 survey, for example, persons with college degrees recalled three times as many assaults as those with only an elementary education (Gove, Hughes, & Geerken, 1985). It is possible that persons with lower levels of education may see a certain act as a normal aspect of daily life, whereas individuals who have had very little experience with physically assaultive behavior may view the same act as one of criminal violence. Alternatively, these differences in reporting of victimization across educational levels could be due to differential respondent productivity; that is, people with higher levels of education may be better able to recall incidents of victimization.
Another issue is related to interviewer and interviewer-respondent interaction effects: Different interviewers may elicit different accounts from the same individual because, for example, they prompt respondents more or less or appear more or less open to certain responses. Clarren and Schwarz (as cited in Gove et al., 1985) concluded that “the upper bound for the number of crimes that could be elicited is limited only by the persistence of the interviewer and the patience of the respondent” (p. 461). In the context of the British Crime Surveys, Coleman and Moynihan (1996) noted that respondents, not wanting to disappoint the often persistent interviewers, may recall incidents experienced by friends or neighbors rather than by themselves. It is also possible, they suggested, that with the crime problem so high on the media’s agenda and thus ingrained in peoples’ minds, respondents may fabricate incidents in the hope that this will somehow lead to policy changes.
Victimization surveys are also an imperfect measure of crime because of the inherent fallibility of human information processing and judgment. People experience lapses in memory, selectively perceive and misperceive particular actions, and interpret actions and events from their own perspectives. In the case of reports of victimization, people may overestimate or underestimate their experiences through outright deception, exaggeration, embarrassment, or misinterpretation. The not uncommon perceptions that lost items were stolen, that open doors and windows are evidence of attempted break-ins, as well as the misunderstanding of particular words and phrases such as threats and fighting words are simple examples of how victimization surveys may provide seriously distorted estimates of the true amount of crime.
The reliability of victimization data can be ascertained through comparisons of survey data with official records, but the results from the limited number of studies that have made such comparisons are not overly encouraging. For example, Turner (1972) found that only 63% of the cases of robbery, assault, and rape from police records were reported on victimization surveys, and there were important differences according to the relationship of the victim to the offender. When the offender was a stranger, 76% of the incidents were reported to the interviewer on the victimization survey; when the offender was known to the victim, 57% of the incidents were reported; and when the offender was a relative, only 22% of the incidents were reported. In a similar record-check study in Baltimore, Murphy and Dodge (1981) found that only 37% of the assaults—compared to 75% of the larcenies, 76% of the robberies, and 86% of the burglaries—uncovered in police records were reported by respondents in victimization surveys.
A second type of record check involves forward record checks (O’Brien, 1985), which involves examining crimes that respondents in victimization surveys claim to have reported to the police. Apparently, the only study of this type was conducted by Schneider (1977, as cited in O’Brien, 1985) in Portland, Oregon, who found that only 45% of the crimes that respondents claimed to have reported to the police were listed in police records.
Technical and Procedural Issues
A number of technical issues associated with victimization surveys also place limits on their utility as measures of crime. These issues focus on the numerator (i.e., the number and type of crimes) and the denominator (i.e., the relevant population base) used in the calculation of crime rates and trends. Changes in technical aspects of national surveys have further eroded the comparability of victimization estimates across jurisdictions and over time.
Changes in the definition of series victimizations and how they are treated is a major technical problem with current victimization surveys. A series involves multiple incidents that are very similar in detail but for which the respondent is unable to recall specific dates and details well enough to report the incidents separately. They are ongoing, with no clear starting or stopping point. For example, many cases of spouse abuse or bullying involve repeated attacks or threats of attack on a number of occasions over the reference period, but a victim cannot recall the particular dates or details of each incident. These details are important in that they are what are used to ascertain if a crime occurred, and if so, what type of crime occurred. Without these details, this simple counting task cannot be accomplished.
National surveys vary widely in their definition of series victimizations and how these are handled in estimation procedures. For example, the NCVS defined a series as involving “three or more criminal acts” prior to the redesign in 1992, and since that time they have changed the crime threshold to six incidents.
Although some reports using NCVS data count series crimes as one victimization, series victimizations are excluded in rates presented in the annual crime bulletin. It is estimated that this change in the definition of series crimes will result in only a small (1% to 5%) increase in the rates for most crimes, but the increase may be as large as 10% to 15% for rates of assault and some types of theft (Bureau of Justice Statistics, 1994). Aside from decreasing the overall estimated rates of victimization, the exclusion of series incidents also artificially deflates the victimization risks for women and other subgroups that are more susceptible to these crimes.
Another technical issue that affects the counting of incidents for rate calculation involves the incomplete bounding of interviews in the NCVS data. Specifically, NCVS procedures dictate that only the first rotation of a housing unit in the survey be treated as a bounding interview, excluding victimization data from that housing unit gathered in the first contact period. However, unbounded data occurs when (1) a new person(s) moves into an eligible housing unit, (2) an eligible respondent was not successfully contacted in the previous interview, (3) a respondent ages into eligibility (i.e., they were 9–11 years old at the start of the time-in sample), or (4) a respondent provides personal interviews but it is followed by proxy interviews. Nevertheless, the data are still used for calculating victimization rates. Thus, by bounding the housing unit but not the individuals within it, NCVS estimates remain susceptible to telescoping and overestimation of victimization risks. The seriousness of this problem is illustrated in a study by Biderman and Cantor (1984), who found that approximately 18% of the total interviews used to generate NCVS estimates in the 1970s were first unbounded interviews. The inclusion of these data increased the number of victimizations used for published estimates of national trends by almost 50%. The replacement of households that leave the panel because they move may also lead to lower estimates of victimization; individuals in such households generally have higher rates of victimization than people who remain at the same address.
As sample data used to estimate population values, national counts of victimizations are derived from various types of weighting procedures and imputations for missing data. Although based on sound statistical theory, these adjustments in practice involve making assumptions about the behavior of nonrespondents and the homogeneity of classes or subgroups. For example, the weighting of the British Crime Survey data to adjust for oversampling of inner-city and minority respondents may be of limited value simply because it does not take into account the differential response rates across these subgroups and their differences in victimization risks. By making unrealistic assumptions that errors in measurement and sampling are random (rather than correlated with other factors), the complex weighting and adjustments used in the NCVS are also subject to debate.
When moving from a consideration of victimization incidents to victimization rates, other technical issues arise that may lead to a distortion in the interpretation of results. For example, Bureau of Justice Statistics’ publications of NCVS data trends compute rates of victimizations per 1,000 persons or households by taking the total number of incidents and dividing by the respective number of persons or households. The resulting rate, however, does not translate into a proportion of persons or households because multiple victimizations are included in the calculations. For instance, a burglary rate of 100 per 1,000 households does not mean that 10% of households experience a burglary because it is possible that one household may report an enormous number of victimizations. What it means is that there are 100 burglaries per 1,000 households. Unfortunately, by spreading these multiple victimizations of a particular household across all households, a somewhat misleading image of risks may be assumed by the consumer of these calculated rates. Under these conditions, a measure such as proportion of households touched by crime may be a better barometer of victimization risks (Klaus, 2007).
An assortment of other technical and procedural issues affects the number of victimizations estimated from these surveys. The following additional factors have been found to influence the counting of victimization incidents:
• Using a proxy to report victimizations of other household members results in lower numbers of incidents being reported than when household members report their own experiences. The NCVS used a proxy for all 12- or 13-year-old household members (until 1992), non-English or non-Spanish speakers, and those temporarily absent or unable to be interviewed.
• Response rates vary across national surveys, and those who refuse to participate or are undercounted in household enumerations (e.g., younger persons, the poor and homeless, ethnic minorities, and frequent movers) generally have higher victimization risks than survey respondents. Although the underrepresentation of these high-risk groups will obviously decrease estimates, the impact of differential response rates across subgroups may either inflate or deflate the number of recorded incidents, depending on whether groups with the highest response rates have high or low risks of victimization.
• Various types of violent behaviors and thefts are seriously under-counted in victimization surveys. These include crimes committed by family members and intimates, homicides, robberies and thefts from commercial establishments, rapes and sexual assaults, and all crimes committed against tourists and other nonresidents.
• Changes in procedures utilized in the NCVS studies over time (e.g., more extensive screens, greater use of telephone interviews, changes in the definition of series incidents, decreased sample sizes) also influence the number of incidents recorded in yearly samples. All else being equal, reductions in the size of NCVS samples over time increase sampling error and the subsequent accuracy of the estimates of the numbers and rates of victimization (Lauritsen, 2005).
• The number of reported victimizations decreases through successive interviews in the NCVS rotation panels (Garafolo, 1990). In other words, the number of recalled incidents decreases consistently between the first and seventh interview. Given that the proportion of persons in the NCVS who are being interviewed for all seven rotations has decreased over time (due to increased population mobility), there has been (a) an increase in the number of persons who receive a smaller number of interviews (e.g., one to three interviews) and (b) a subsequent increase in the apparent number of victimizations due to this time-in-sample problem. Changes in the average time-in-sample affects estimates of the number of incidents and the comparability of the NCVS victimization rates over time.
• Many of the incidents reported in victimization surveys are trivial and may not even qualify as a crime from a legal perspective. Most violent crimes in the NCVS involve simple assaults without injury to the victim. The redesigned NCVS yields more incidents of violent crime, but the new method has a greater impact on estimates for violent offenses by nonstrangers, attempted crimes, and violent crimes not reported to the police.
The level of victimization risks in national surveys depends in large part on the denominator used in the calculation of estimated rates. Property victimization rates for each national survey are calculated as an incident rate (or victimization rate—both are possible in the data) per 1,000 households. Rates of violent victimization (or violent incidents—both are possible in the data) are often expressed as a victimization rate per 1,000 population 12 years of age and older. The measurement of victimization risks, however, is in many cases better served by a different base for rate calculation, using for the denominator the entity most at risk for that particular victimization. For example, the calculation of motor vehicle theft per household is probably a less accurate measure of one’s vulnerability to this crime than a motor vehicle theft rate expressed per 1,000 households with motor vehicles or thefts per 1,000 motor vehicles. Similarly, the calculation of rape rates per 1,000 persons ignores the fact that women are the victims of this crime in more than 90% of the cases. Under these conditions, computing rape rates per 1,000 females is a more meaningful barometer of victimization risks, and this is often what is produced in many reports published by the Bureau of Justice Statistics.
It is possible to compute victimization rates on a wider variety of population bases that correspond to risky groups and settings. These include, for example, (a) the rate of stranger assaults per 1,000 contacts with strangers, (b) mugging rates per 1,000 hours spent in public places, (c) home burglary rates per 1,000 households with burglary alarms, and (d) violent crime rates per 1,000 college students between 18 and 24 years of age. Although numerical data for each of these particular base comparisons may not be readily available in all cases, the use of rate calculations that directly incorporate risk factors may be a better reflection of one’s chances of particular types of victimization than measures of victimization rates that are not adjusted for differential exposure and vulnerability.
SUMMARY AND CONCLUSIONS
National victimization surveys have been widely used as an alternative measure of the prevalence and distribution of crime in the United States. The major advantage of these surveys is that they provide a profile of criminal incidents that are both reported and not reported to the police. Who is better able to enumerate the nature and distribution of crime incidents and the consequences of crime than those who experience it?
Unfortunately, all victimization surveys have four inherent problems that limit their utility as accurate measures of criminal activity. First, victim surveys cover only a small range of criminal acts—excluding victimless and public order violations, homicides, commercial and business victimizations, and many white-collar crimes against consumers—and seriously undercount incidents of domestic violence and other crimes among known parties. Second, victimization surveys are based on sample data and not population counts, making them subject to serious distortion because of sampling error and sampling bias. Third, these surveys are based entirely on victims’ perceptions without independent confirmation that the offenses they claim to have experienced actually occurred or would qualify as a crime from a legal perspective. Victims may also either under- or overreport their experiences because of factors such as forgetfulness, misinterpretations of events, embarrassment, fear of getting in trouble, trying to please interviewers by giving socially desirable answers, and deliberate distortion or manipulation. Fourth, the number of victimizations uncovered in surveys depends on how the questions are worded and numerous technical elements associated with the survey itself. The use of different procedures over time renders problematic any comparisons of estimated victimization rates from these surveys.
The problems with victimization surveys, however, are neither more nor less serious than the problems with official data and self-report measures of crime. In fact, problems of definitional ambiguity, limited coverage, reporting biases, and various sources of measurement error plague each method of counting crime. Nonetheless, a comparison of the results across these three primary methods of counting crime reveals several common themes about the prevalence of crime, its spatial distribution, and the correlates of crime. The common themes across these methods and some concluding thoughts about crime measurement are addressed in the final chapter.
Article
Sexual Abuse: A Journal of
Research and Treatment
22(4) 387 –401
© 2010 Association for the Treatment
of Sexual Abusers
Reprints and permission: http://www.
sagepub.com/journalsPermissions.nav
DOI: 10.1177/1079063210372142
http://sajrt.sagepub.com
The Recidivism Rates
of Female Sexual
Offenders Are Low:
A Meta-Analysis
Franca Cortoni1, R. Karl Hanson2,
and Marie-Ève Coache1
Abstract
This study examined the recidivism rates of female sexual offenders. A meta-analysis
of 10 studies (2,490 offenders; average follow-up 6.5 years) showed that female
sexual offenders have extremely low rates of sexual recidivism (less than 3%). The
recidivism rates for violent (including sexual) offences and for any type of crime
were predictably higher than the recidivism rates for sexual offences but still lower
than the recidivism rates of male sexual offenders. These findings indicate the need
for distinct policies and procedures for assessing and managing the risk of male and
female sexual offenders. Risk assessment tools developed specifically for male sexual
offenders would be expected to substantially overestimate the recidivism risk of
female sexual offenders.
Keywords
female sexual offenders, recidivism, meta-analysis
Although tremendous advances have been made in the understanding of the recidi-
vism rates of adult male sexual offenders, similar knowledge is still extremely limited
for female sexual offenders. Like men, women convicted of sexual offenses are sub-
ject to social control policies (e.g., Canadian Dangerous Offender Provisions, U.S.
Sexually Violent Predator laws). Without an empirical basis for risk assessment, the
1Université de Montréal, Montréal, Quebec, Canada
2Public Safety Canada, Ottawa, Ontario, Canada
Corresponding Author:
Franca Cortoni, Université de Montréal, PO Box 6128, Downtown Branch,
Montréal, Quebec, Canada H3C 3J7
Email: franca.cortoni@umontreal.ca
388 Sexual Abuse: A Journal of Research and Treatment 22(4
)
assessment of these women remains as problematic as the assessment of male sexual
offenders was 20 years ago. Reliable estimates of the recidivism base rates of female
sexual offenders would be a valuable aid to applied decision makers. Providing these
estimates is the primary goal of this study.
Prevalence of Sexual Offending by Women
The prevalence rate of female sexual offending is difficult to ascertain. Some authors
believe that sexual offending by females is relatively common but that its extent is
unknown because of the lack of reporting or because these women tend to be diverted
from the criminal justice system (Vandiver & Walker, 2002). Others suggest that
sexual offending by women is likely to be underidentified because of societal and
cultural stereotypes of female sexual behavior, including professional biases (Denov,
2003, 2004; Giguere & Bumby, 2007).
In efforts to provide more systematic information about the prevalence of female
sexual offenders, in comparison with male sexual offenders, Cortoni and Hanson
(2005; Cortoni, Hanson, & Coache, 2009) estimated the proportion of sexual offend-
ers who are women from two general sources of information. The first source of infor-
mation was official police or court reports that detailed the gender of the offender. The
second source of information was victimization surveys. For both sources, information
was available for Australia, Canada, New Zealand, the United Kingdom, and the
United States. Results from the updated 2009 review were consistent with the earlier
2005 findings. Based on official records, the proportion of all sexual offenders who
were female ranged from 0.6% in New Zealand to 8.7% for nonrape sexual offenders
in the United States. When these numbers were averaged across all countries in the
study, women constituted 4.6% of all sexual offenders. Based on victimization stud-
ies, the proportion of sexual offenders who were female ranged from 3.1% for New
Zealand to 7.0% for Australia, an average of 4.8%.
In summary, available data indicate that women constitute approximately 5% of all
sexual offenders. To place this number in a more concrete societal context, it is useful
to estimate their proportion in real terms. To establish an overall international figure of
the prevalence of child sexual abuse, Pereda, Guilera, Forns, and Gómez-Benito (2009)
conducted a meta-analysis of its prevalence in 22 countries. Their results showed that
nearly 8% of men and 20% of women had been sexually victimized prior to age 18. If
4% to 5% of all these victims were sexually abused by women, this would mean that
1.4% of all child victims were sexually abused by women. These findings indicate that
sexual offending by women is significant enough to warrant systematic attention.
It is important to note, however, that despite the increased recent attention paid to
sexual offending by women, we cannot say that sexual offending by women is actually
a growing phenomenon. For example, in Canada, between 1994 and 2003, the yearly
rate of women accused of sexual assault has consistently been between 1% and 2% of
all accused of sexual offences (Statistics Canada, 2007). Instead, sexual offending by
women appears to have been a long underrecognized issue, which is finally coming to
Cortoni et al. 389
the forefront in the field. The increased attention to female sexual offenders motivates
the need for empirical evidence to inform the assessment, treatment, and management
of these women.
The Importance of Base Rates
The evaluation of risk of recidivism requires knowledge of static and dynamic risk
factors that have been empirically linked to sexual offending. Much is known about
risk factors among male sexual offenders (e.g., Hanson & Morton-Bourgon, 2005),
but very little is known about the factors linked to sexual offending among women
(Hedderman, 2004; Kemshall, 2004). To establish this knowledge, systematic infor-
mation about the recidivism rates of the population is required.
Base rates are the proportion of the population that exhibits the phenomenon of
interest. Understanding the base rates of recidivism is fundamental to the evaluation
of risk of future offending (Hanson & Bussière, 1998; Quinsey, Lalumière, Rice, &
Harris, 1995). Recidivism rates vary according to factors such as jurisdictions, types
of crimes being measured, length of time of follow-up, and how they were measured.
Among male sexual offenders, research has shown that recidivism rates, with a
follow-up period of 5 years, are 13.5% for new sexual offenses, 25.5% for violent
(including sexual) offenses, and 36% for any type of recidivism (Hanson & Morton-
Bourgon, 2004).
After years of neglect, research into the recidivism rates of female sexual offenders
has started to receive attention. Cortoni and Hanson’s (2005) review found that the
recidivism rates of female sexual offenders are generally low. The number of female
offenders included in that review, however, was small (total of 380); a number of large
sample studies have appeared since that review was complete. Also, Cortoni and Hanson
(2005) did not provide a meta-analytic summary of recidivism rates, such that it was
impossible to know whether the variability across studies was significant. Conse-
quently, the current study provides an updated, meta-analytic review of the empirical
literature concerning the recidivism rates of female sexual offenders.
Method
Selection of Studies
Studies included conference presentations, government reports, official recidivism
data drawn from websites or through direct communication with government agencies,
and reports of unpublished studies obtained directly from the researchers. Recidivism
studies were included if they identified the gender of the offenders and provided a
follow-up period. As necessary, clarifications of the data were obtained by directly
contacting the authors of the studies included in this review. For example, to ensure
accurate coding of recidivism rates of the Sandler and Freeman (2009) and the Vandiver
(2007) studies, we verified whether reported violent reoffense rates included sexual
390 Sexual Abuse: A Journal of Research and Treatment 22(4)
offenses or not. There were times, however, that such verifications were impossible.
In these circumstances, only clearly identifiable recidivism rates were included in the
study. As a result, not all types of recidivism were present in every study.
For this review, recidivism was defined as being arrested, charged, convicted, or
incarcerated for a new offense. Sexual recidivism included a new charge, conviction, or
reincarceration for a sexual offence. Violent recidivism was defined as a new violent
charge, conviction, or incarceration for a new violent offense (including sexual offences).
Any recidivism was defined as any new charge, conviction, or incarceration. Conse-
quently, the categories of recidivism are cumulative rather than mutually exclusive.
The search yielded two published studies (Broadhurst & Loh, 2003; Sandler &
Freeman, 2009), two government reports (Hanson, Harris, Scott, & Helmus, 2007;
Minnesota Department of Corrections, 2007), four conference presentations (Peterson,
Colebank, & Motta, 2001; Vandiver, 2007; Wijkman, Zoutewelle-Terovan, & Bijleveld,
2009; Williams & Nicholaichuk, 2001), and two official sources of recidivism data
(Holley & Ensley, 2003, Florida State, United States; Home Office, 1998-2003,
United Kingdom). Table 1 provides a summary of these studies; additional comments
about these studies are provided below.
Broadhurst and Loh (2003) examined the probability of rearrest for sexual offend-
ers in the state of Western Australia between 1984 and 1994. Recidivism for the
female sexual offenders was reported in Footnote 1 (p. 134).
Hanson et al.’s (2007; Harris & Hanson, 2003) Dynamic Supervision Project was a
prospective study designed to test the validity of a system of risk assessment for sex-
ual offenders on community supervision (probation or parole). Assessments were con-
ducted between 2001 and 2004, with recidivism information provided on an ongoing
basis by the officers supervising the cases (up to March 2007). The full study exam-
ined 997 sexual offenders from Canada and two U.S. states, of which 6 were female
(1 from New Brunswick, 2 from Iowa, and 3 from Newfoundland).
In 2003, Holley and Ensley produced a government recidivism report on inmates
released from Florida prisons between 1995 and 2001.
Home Office Reports to the U.K. Parliament: The Home Office provides informa-
tion on the reconviction rates of offenders released from prisons in England and
Wales. The data used in this review cover the period from 1994 to 1999.
The Minnesota Department of Corrections published a report in 2007 on the recidi-
vism rates of sexual offenders released from a Minnesota Correctional Facility
between 1990 and 2002.
The women in Peterson et al. (2001) had been or continued to be in treatment for
their sexually offending behavior. Recidivism was coded from official Kentucky
Court records.
Sandler and Freeman (2009) examined the recidivism patterns and risk factors of
registered sexual offenders in the State of New York. The study included by far the
largest sample ever reported in a recidivism study of female sexual offenders (N = 1,466).
Recidivism was coded from computerized criminal history files in New York State
between January 1, 1986, and December 31, 2006.
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392 Sexual Abuse: A Journal of Research and Treatment 22(4)
Vandiver (2007) conducted a follow-up of the 2001 cohort of registered sexual
offenders in Texas. Recidivism was coded from criminal records and included any
registerable sexual offense in the State of Texas. These offenses include compelling
prostitution, offenses related to possession or distribution of child pornography, kid-
napping, and board/court ordered registration (Donna Vandiver, personal communica-
tion, October 14, 2008).
Wijkman et al. (2009) conducted a latent class analysis to investigate specialization
versus generalization in the patterns of criminal behavior of 132 female sexual offend-
ers. Data were coded from complete official criminal convictions records of the
women from 12 years to August 2008 (Catrien Bijleveld, personal communication,
February 3, 2009).
Williams and Nicholaichuk (2001) conducted a follow-up of 72 female sexual
offenders who received federal sentences (2 years or more) in Canada between 1972
and 1998. Because of deportation or continued incarceration, recidivism data could be
obtained only for 61 of the cases. Recidivism was coded from Royal Canadian
Mounted Police records, a national database that contains all charges and convictions
on every offender in Canada.
Aggregation of Findings
The basic effect size indicator was p, the proportion of recidivists (i.e., the number of
recidivists divided by n, the sample size). Although raw proportions are easily inter-
preted, they have certain limitations as effect size indicators for meta-analysis. Using
the standard formula, the variance of p is estimated as p(1 – p)/n (Fleiss, Levin, &
Paik, 2003). This variance is small in two quite different circumstances: (a) when the
same size is very large and (b) when sample size is so small that there are no recidi-
vists. This formula also assumes that the variance decreases as the proportions
approach zero, which has the effect of giving the most weight to studies with the
smallest recidivism rates.
Given the problems with analyzing raw proportions from different studies, variance
stabilization transformations are recommended (Cohen, 1988; Eisenhart, 1947; Fleiss
et al., 2003). The most common variance stabilization transformation for proportions is
the arcsine transformation, which we will denote by Ă, defined as Ă = 2 arcsin√P, with
a variance of 1/n. In other words, the variance of Ă depends only on the sample size and
not on the size of the proportion. Consequently, analyses were conducted using both the
raw proportions and the transformed proportions. All results were reported as propor-
tions, however, because Ă in its original units (radians) is not easily interpreted.
To analyze studies in which there were no recidivists for certain categories (Broadhurst
& Loh, 2003; Hanson et al., 2007; Peterson et al., 2001), the recidivism rate (p) was
estimated as 1/4n (i.e., Bartlett’s adjustment, see Eisenhart, 1947; Cohen, 1988).
The magnitude and consistency of recidivism rates across studies were calculated
using both fixed-effect and random-effects models (Hedges & Vevea, 1998). Each
approach asks slightly different questions and neither approach has won universal
Cortoni et al. 393
acceptance (Whitehead, 2002). On a conceptual level, the conclusions of the fixed-
effect analyses are restricted to the particular set of studies included in the meta-analysis.
In contrast, the random-effects model aims for conclusions that apply to the population
of studies of which the current sample of studies is a part. In practical terms, the random-
effects model includes an additional between-study error term representing the unex-
plained variation across studies (a constant). Compared with the fixed-effect model,
the random-effects model has higher variance estimates (wider confidence intervals),
and the differences in sample size across the studies is given less importance. Conse-
quently, the random-effects model gives relatively more weight to small studies than
does the fixed-effect model (approximating unweighted averages).
When the assumptions are violated, the fixed-effect model is too liberal and the
random-effects model is too conservative (Overton, 1998). The results of the random-
effects and fixed-effect models converge as the amount of between-study variability
decreases. When the variation between studies is less than would be expected by
chance (Q < degrees of freedom, using Cochran’s Q statistic; Hedges & Olkin, 1985),
both approaches yield identical results. To test the generalizability of fixed effects
across studies, the Q statistic was used:
Q =
k
Σ
i=1
wi (pi – P.)2,
where pi is the observed proportion in each of k studies and p. is the weighted average.
The Q statistic is distributed as a c2 with k – 1 degrees of freedom (k is the number
of studies).
A significant Q statistic indicates that there is more variability across studies than
would be expected by chance. In such cases, further examinations of the data were
conducted to establish whether an outlier could be identified. An individual finding
was considered to be an outlier if (a) it was an extreme value (highest or lowest), (b) the
Q statistic was significant, and (c) the single finding accounted for more than 50% of
the value of the Q statistic. When an outlier was detected, the results are reported with
and without the exceptional case.
Fixed-effect estimates of recidivism rates were calculated using the formula and
procedures presented in Hedges (1994). Random-effects estimates were calculated
using Formulae 10, 12, and 14 from Hedges and Vevea (1998). Hand calculations or
SPSS syntax was used for all analyses. Both fixed-effect and random-effects models
were estimated for both the raw proportions (p) and the transformed proportions (Ă).
Results
A total of 2,490 offenders with an average follow-up time of 6.5 years were included in
this review. Sexual, violent, and any recidivism were examined separately in the analy-
ses. Table 2 presents the weighted averages of recidivism rates across studies. Table 3 and
Figure 1 show the results of the meta-analysis of both raw and transformed proportions.
394 Sexual Abuse: A Journal of Research and Treatment 22(4)
Table 3. Random and Fixed Effects Estimates of Recidivism
Random Fixed
% 95% C.I. % 95% C.I. Q N k
Sexual P 2.43 0.82, 4.03 1.24 0.81, 1.68 52.86** 2,416 9
W/o Van 1.00 0.56, 1.45 1.00 0.56, 1.45 6.92 1,945 8
Ă 2.33 0.47, 5.55 2.43 1.86, 3.09 80.34** 2,416 9
W/o Van 1.28 0.83, 1.83 1.28 0.83, 1.83 5.63 1,945 8
Violence P 7.57 3.40, 11.75 4.41 3.57, 5.25 55.62** 2,260 6
W/o Van 4.64 2.13, 7.15 3.65 2.78, 4.52 12.00* 1,789 5
Ă 7.43 3.17, 13.29 5.81 4.89, 6.82 68.50** 2,260 6
W/o Van 5.54 2.87, 9.01 4.08 3.21, 5.05 13.33* 1,789 5
Any P 23.82 14.47, 33.17 22.35 20.73, 23.97 130.93** 2,406 8
W/o Van 19.79 15.00, 24.59 18.96 17.22, 20.70 18.61* 1,935 7
Ă 23.30 14.40, 33.59 23.89 22.21, 25.61 136.38** 2,406 8
W/o Van 20.17 15.50, 25.28 19.40 17.66, 21.19 18.12* 1,935 7
Note: P = raw proportions; w/o Van = without Vandiver (2007); Ă = arcsine transformed proportions; CI = confidence
interval; k = number of studies.
*p < .05. **p < .01.
Sexual Recidivism Estimates
For sexual recidivism, the observed recidivism rates ranged from 0% to 10.8%, with a
median value of 1.5%. In the nine studies reporting sexual recidivism rates involving
2,416 female sexual offenders, there were 77 sexual recidivists (3.19%). Fixed-effect
analyses of the raw proportions and the transformed proportions produced estimates
of 1.24% and 2.43%, respectively. Random-effects analyses produced estimates of
2.43% and 2.33%. The analyses showed a greater variability of recidivism among
studies than would be expected by chance, and Vandiver (2007) was identified as
an outlier. Once Vandiver was removed, the variability between studies was no
more than would be expected by chance (Q < df; see Table 3). Without Vandiver,
Table 2. Weighted Average Recidivism Rates of Female Sexual Offenders
Type of Recidivism Average
Follow-Up
Sexual Violent Any (Years)
All studies 3.19% (77/2,416) 6.46% (146/2,260) 24.52% (590/2,406) 6.5
Without 1.34% (26/1,945) 4.25% (76/1,789) 19.54% (378/1,935) 5.9
Vandiver
(2007)
Male sexual 13.7% 25.0% 36.9% 5.5
offendersa
Note: N = 20,000; Hanson and Morton-Bourgon (2004).
Cortoni et al. 395
P
er
ce
n
ta
g
e
(%
)
Sexual Violent Any
Random Random RandomFixedFixed Fixed
0
5
10
15
20
25
30
35
P
W
/O
V
an Ã
W
/O
V
an P
W
/O
V
an Ã
W
/O
V
an P
W
/O
V
an Ã
W
/O
V
an P
W
/O
V
an Ã
W
/O
V
an P
W
/O
V
an Ã
W
/O
V
an P
W
/O
V
an Ã
W
/O
V
an
Figure 1. Percentages and confidence intervals of aggregated estimates of recidivism:
Random and fixed effects
fixed-effect and random-effects estimates were the same: 1.00% for the raw propor-
tions and 1.28% for the transformed proportions.
Violent Recidivism Estimates
For violent recidivism, of the seven studies involving 2,260 female sexual offenders,
there were 146 violent recidivists (6.46%). The observed violent recidivism rates
ranged from 1.2% to 16.6%, with a median value of 9.3%. Fixed-effect analyses of the
raw proportions and the transformed proportions produced estimates of 4.41% and
5.81%, respectively. Random-effects analyses produced estimates of 7.57% and
7.43%. There was greater variability in the violent recidivism rates across studies than
would be expected by chance, and Vandiver (2007) was again identified as the outlier.
When the fixed-effect analyses were repeated without the Vandiver study, variability
among studies dropped considerably but remained significant (Q = 12.00 and 13.33,
respectively, df = 4, p < .05; see Table 3). Without Vandiver, the fixed-effect analyses
of the raw proportions and the transformed proportions were 3.65% and 4.08%,
respectively. Random-effects estimates were 4.64% and 5.54%, respectively.
Any Recidivism Estimates
For any recidivism, of the eight studies involving 2,406 female sexual offenders, there
were 590 recidivists (24.42%). The observed rate for recidivism ranged from 11.1% to
396 Sexual Abuse: A Journal of Research and Treatment 22(4)
45.0%, with a median value of 23.5%. Fixed-effect analyses of the raw proportions
and the transformed proportions produced estimates of 22.35% and 23.89%, respec-
tively. Random-effects analyses produced estimates of 23.82% and 23.30%. There
was greater variability across studies than would be expected by chance, with Vandiver
(2007) being the sole outlier. When the fixed effects analysis was repeated without the
Vandiver study, variability among studies dropped considerably but remained signifi-
cant, Q = 18.61 (raw proportions)] and 18.12 (transformed proportions), df = 6, p < .01;
see Table 3. Without Vandiver, the fixed-effect analyses of the raw proportions and
the transformed proportions were 18.96% and 19.40%, respectively. Random-effects
estimates were 19.79% and 20.17%, respectively.
Discussion
This meta-analytic review found that the recidivism rates of female sexual offenders
were much lower for all types of crime than the comparable rates for male sexual
offenders. Specifically, the women had extremely low rates of sexual recidivism
(between 1% and 3%), regardless of the studies included or the method of analysis.
Violent (including sexual) recidivism rates were higher but still low: Depending on
whether fixed or random effects were examined, violent recidivism rates ranged from
4% to 8%. In contrast, rates for any type of recidivism were higher, ranging from 19%
to 24%. These results provide clear evidence that female sexual offenders, once they
have been detected and sanctioned by the criminal justice system, tend not to reengage
in sexually offending behavior. Most female sexual offenders are not convicted of any
new crimes, and of those who are, they are 10 times more likely to be reconvicted for
a nonsexual crime than a sexual crime (≈20% vs. ≈2%).
The low recidivism rates of the female sexual offenders are consistent with previ-
ous findings showing that, compared with men, women are less likely to be involved
with any type of crime (Barker, 2009; Blanchette & Brown, 2006; Kong & AuCoin,
2008; Langan & Levin, 2002). Depending on the jurisdictions, women constitute
approximately 17% to 23% of all adult offenders, although they constitute only about
10% of all violent offenders and 5% of all sexual offenders (Blanchette & Brown,
2006; Cortoni et al., 2009). Similarly, women also have lower recidivism rates than
males. For offenders released from the Correctional Service of Canada during the
1990s, the 2-year reconviction rate for male offenders ranged between 41% and 44%,
compared with rates of 23% to 30% for the female offenders (Bonta, Rugge, &
Dauvergne, 2003). The rate of violent recidivism for the women was half that observed
for the men in the Correctional Service of Canada samples (6.7% vs. 13.2%). In the
United States, 39.9% of the women had been reconvicted for a new offense versus
47.6% of the men in a 3-year follow-up of 272,111 offenders, including 23,674 women
(Langan & Levin, 2002).
Women’s involvement in crime is generally low. The reasons for this are unclear—
but the fact is well established (e.g., Blanchette & Brown, 2006), and it is particularly
true of female sexual offenders (Giguere & Bumby, 2007). Despite low numbers,
Cortoni et al. 397
women are increasingly coming to the attention of the criminal justice system for sex-
ual offenses, thereby increasing the need for appropriate assessment practices. The
accumulating evidence suggests that females have particular vulnerabilities that are
linked to their sexually offending behavior. Specifically, social and psychological
alienation, along with extensive histories of victimization, are particularly common
among female sexual offenders (Comack & Brickey, 2007; Gannon, Rose, & Ward,
2008; Johansson-Love & Fremouw, 2006; Pollock, Mullings, & Crouch, 2002; Sommers
& Baskin, 1993; Wijkman & Bijleveld, 2008). For these women, it is likely that their
offending is related to early experiences of severe physical and sexual abuse in combi-
nation with biological (e.g., genetic factors; Quinsey, Skilling, Lalumière, & Craig,
2004) and social learning variables (e.g., socialization; Campbell, Muncer, & Bibel,
2001). The precise etiological mechanisms mediating the relationship between victim-
ization and subsequent offending are unknown, as of yet.
In the overall collection of studies included in this meta-analysis, there was greater
variability than would be expected by chance. Much of this variability could be
explained by the high recidivism rates observed by Vandiver (2007). Vandiver’s
(2007) study was the only one in which the sexual recidivism rates were virtually
identical for the male and female sexual offenders (11.4% vs. 10.8%, respectively).
Vandiver (2007) counted as sexual recidivism any offense that led to the registration
of the woman as a sexual offender, as defined by the State of Texas. This definition
not only included the sexual offences typical of males, such as child molestation, but
also included other types of offences, such as compelling prostitution, kidnapping,
and Court or Board ordered registration (D. Vandiver, personal communication,
October 14, 2008). The inclusion of prostitution-related offenses likely inflated the
rate of sexual recidivism among the female sexual offenders as this type of offences
was only present for the women in the study. Consistent definitions facilitate cumula-
tive knowledge. In the male sexual offender literature, there have been sustained
efforts to adopt consistent definitions of what constitutes a sexual crime (e.g., Hanson
& Morton-Bourgon, 2004; Harris, Phenix, Hanson, & Thornton, 2003; Quinsey et al.,
1995). In the current study, both the Vandiver (2007) and the Sandler and Freeman
(2009) data sets included females who were actually only convicted of prostitution-
related offenses. In contrast, males with only prostitution-related offenses are typi-
cally not viewed as sexual offenders. Future research on female sexual offenders
would do well to consider standardizing the definitions of sexual offending by
women. In particular, researchers should separate prostitution-related offences com-
mitted by females from sexual offences involving sexual acts directed toward victims
unable or unwilling to consent (i.e., the sexual offences typical of contemporary sam-
ples of male sexual offenders).
This study demonstrated the value of meta-analysis in summarizing the recidivism
rates across studies. Although it is possible to create averages by simply dividing the
aggregated total of recidivists by the aggregated total sample size, meta-analysis pro-
vides estimates of the stability of the results. Evaluators and policy makers can have
the most confidence in results that are consistent across studies. When there is
398 Sexual Abuse: A Journal of Research and Treatment 22(4)
meaningful variation across studies, meta-analysis can identify statistical outliers and
moderator variables. Furthermore, meta-analysis will have an essential role in the
identification of recidivism risk factors for female sexual offenders. Given the low
recidivism rates, very large samples are needed to identify factors that distinguish the
recidivists from the nonrecidivists, samples that can most easily be obtained by accu-
mulating female sexual offenders from different settings.
Implications for Applied Risk Assessment
The low base rates of sexual recidivism among female sexual offenders means that
risk assessment tools for male sexual offenders will overestimate the recidivism risk
of female sexual offenders. Consequently, they should not be used in applied decision
making. Given that general (i.e., nonsexual) recidivism is much more common among
female sexual offenders than sexual recidivism, evaluators should consider the use of
tools validated to assess risk of general and violent (nonsexual) recidivism among
these women (e.g., Level of Service Inventory–Revised; Andrews & Bonta, 1995).
Even the use of general risk assessment tools, however, requires an understanding of
the general research on risk factors and recidivism among female offenders (e.g.,
Blanchette & Brown, 2006; Folsom & Atkinson, 2007; Holtfreter & Cupp, 2007;
Manchak, Skeem, Douglas, & Siranosian, 2009).
If the evaluation question specifically concerns the risk for sexual recidivism (e.g.,
Sexual Violent Predator laws in the United States), then the risk factors must be so
blatant that they overcome the presumption of low risk for sexual recidivism implied
by the observed base rates. The risk factors for sexual recidivism among females are
unknown but could plausibly include the same three general factors generally identi-
fied for males (i.e., sexual deviancy, antisociality, intimacy deficits). Research to date,
however, indicates that the ways in which these factors manifest themselves in female
sexual offenders are different from the typical patterns found in male sexual offenders
(see Cortoni, in press, for a review). In addition, the extent to which these factors actu-
ally play a role in sexual recidivism among women remains an open question.
Authors’ Note
The views expressed are those of the authors and are not necessarily those of Public Safety Canada.
Acknowledgment
We would like to thank Catrien Bijleveld, Naomi Freeman, Jeff Sandler, and Donna Vandiver
for providing data and responding to our queries. Kelly Babchishin’s help in preparing the
article is much appreciated.
Declaration of Conflicting Interests
The author(s) declared no conflicts of interest with respect to the authorship and/or publication of this.
Funding
The author(s) received no financial support for the research and/or authorship of this article.
Cortoni et al. 399
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