Have you ever made note of crime statistics in your community? These days, this information is readily available online. This information is often used when people consider moving into a new neighborhood or when they are trying to assess property values.To prepare
Access the Crime Mapping website listed in this module’s Learning Resources.
Explore the capabilities of this tool by selecting several major cities where crime rates are likely to be higher.
Select one city, 2–3 crimes, and a 7-day time frame.
(Note: Not all cities in the United States report crime data to this site, so you may need to try more than one city.)
Save a screenshot of the map that is created by your selection.
Upload a copy of the map screenshot you saved in your search. In a minimum of 150 words, discuss the city chosen, 2–3 of the highest crime occurrences, and whether the crimes you selected seem to be grouped closely together or spread out. Explain how law enforcement might use this type of technology. Specifically identify how this technology may be used to prevent crime.
READ Materiel for assignment
Dowsley,F.,& Hart ,T.C,(2017) crime and Justice data. In A. decker & R.Sarre (Eds.), The Palgrave handbook of Australian and New Zealand criminology ,crime and justice (pp.65-80).Cham, Switzerland :Palgrave MacMillan.
Crime and Justice Data
Fiona Dowsley and Timothy C. Hart
Crime remains one of the most challenging social constructs to measure. It is elusive. It wishes to remain hidden. It is in the interest of the offender, in most instances, for their crime to remain undiscovered. A victim may also have many reasons for not wishing to disclose that a crime has occurred. Such reasons include fear, guilt, embarrassment, fear of other interventions, and lack of faith in authorities. As a result, it is impossible for criminologists and policy makers to answer accurately seemingly fundamental questions about how much crime occurs; how many victims of crime there are; and how many offenders commit crimes within our society.
The criminal justice system has extensive powers to surveil, detain, adju- dicate, imprison, and curtail the liberties of the citizenry. Many programmes are implemented to improve community safety. Comprehensive information about the operations and impacts of the criminal justice system, however, can also be challenging to obtain. Data may be sought to illustrate the individual’s experience of the criminal justice system, which is not collected routinely by institutions or cannot be easily compiled. Gaining access to information about individuals can further involve clearing significant hurdles in the form of ethics and authorisation processes and privacy frameworks, which can differ across jurisdictions. The emergence of new areas of criminological focus and
F. Dowsley (&)
Crime Statistics Agency, Melbourne, Australia e-mail: firstname.lastname@example.org
Griffith Criminology Institute, Brisbane, Australia e-mail: email@example.com
© The Author(s) 2017 65 A. Deckert and R. Sarre (eds.), The Palgrave Handbook of Australian and New Zealand
Criminology, Crime and Justice, DOI 10.1007/978-3-319-55747-2_5
66 F. Dowsley and T.C. Hart
the expansion of criminal and regulatory activities can also create demands for additional data and information about new crimes and criminal justice processes.
Despite these challenges, there are various aspects of crime and criminal justice administration that can be observed through a range of sources. Knowing which sources exist, are available to use, when they can be most relevant, and the questions they can best answer is crucial for researchers and policy makers alike. This chapter describes the main forms of crime and criminal justice system data available in Australia and New Zealand, the strengths and limitations of some of these sources. It explores the future challenges and opportunities for advancing the development of crime and justice data.
Crime and Justice Statistical System
Viewed in a global context, Australia and New Zealand’s crime and justice statistical systems have good coverage across the UN’s model criminal justice statistics system (UN Department of Economic and Social Affairs 2003). In both countries, quantitative information about the prevalence of crime, char- acteristics of victims and offenders, and the basic function of the criminal justice system is accessible. National statistical collections have often been adminis- tered by the ABS and Statistics New Zealand, meaning the collections tend to be produced regularly and are inexpensive to access. Furthermore, oversight by national statistical agencies reflects a commitment to integrity and objective data administration. Modern statistical systems are complex. An increasing number of entities collect, produce, and disseminate data relating to crime and justice institutions and related fields that can be used in criminological research. Such institutions include justice system entities; health and social services institutions; specialised data and research centres such as the AIHW, AIC, and the Centre for Social Research & Evaluation in New Zealand; various state-based entities in Australia; academic institutions and partnerships; not for profit entities; and service providers. In a dispersed statistical system, researchers can struggle to identify all extant, relevant data sources.
History of Official Crime and Justice Data Sources
Crime and justice statistics were collected from the establishment of the Australian colonies (Forster and Hazelhurst 1988). Despite data collection since European settlement,1 neither Australia nor New Zealand’s data support
comparisons over time. Too many changes to legislation and justice system business processes, along with technology, terminology, and counting rule changes, have transpired to make this possible (Graycar and Grabosky 2002).
Since federation, government statisticians who attempt to compile national data have bemoaned the lack of uniformity and comparability between states and territories (ABS 1908). As the states and territories have developed dif- ferent legal systems and institutions, collating a complete and comparable national view of crime and justice remains an aspiration. Serious efforts at compiling uniform Australian crime statistics have been undertaken since the 1960s (Wyman 1970), with both ABS and AIC compiling selected offence data from states and territories, albeit without achieving comparability (Mukherjee et al. 1987).
Development of contemporary Australian recorded crime statistics began in the late 1980s when the National Uniform Crime Statistics Committee (1989, 1) reported that “Australian national crime statistics lag far behind statistics available in other areas of social concern … and compare unfa- vourably with other developed countries”.2 To address these challenges, joint initiatives between the ABS and the Commonwealth, states, and territories were established. These joint initiatives include the National Crime Statistics Unit (NCSU) established in 1990, the National Criminal Courts Statistics Unit (NCCSU) established in 1994, and the National Corrective Services Statistics Unit (NCSSU) also established in 1994 (ABS 1994). The NCSU and NCCSU established the current national statistical collections, while the NCSSU adopted the publication of two statistical collections, which had previously been produced by the AIC, that is, the annual prisoner census and the quarterly corrective services collections. Development of statistical infrastructure, including standard offence classifications from the early 1980s to the current Australian and New Zealand Standard Offence Classification (ABS 2011a), and national counting rules such as the National Crime Recording Standard for police statistics, has supported comparability efforts. Despite this, comparability issues still exist within the national police-recorded crime collections, in particular.3
The AIC has established a number of statistical programmes between 1981 and 2007. This includes data on juveniles in detention; the aforementioned prisoner census and corrective services series; and national monitoring pro- grammes such as those relating to homicide, deaths in custody, firearm theft,
5 Crime and Justice Data 67
68 F. Dowsley and T.C. Hart
armed robbery, fraud against the Commonwealth, and human trafficking. Other evolving national collections include the AIHW Juvenile Justice National Minimum Dataset, which was developed in 2000.
In 1978, the NZ Police commenced electronic recording of crime using the Law Enforcement System (LES), which has also been used by criminal courts and the NZ Department of Corrections since 2003 and 2005, respectively. This enabled the production of modern crime statistics. Despite intervening system and legislative changes over the years, recorded crime statistics gen- erated from 1978 to 2014 remained largely comparable (Knight et al. 2016). Statistics New Zealand has published data relating to courts from 1980 in the current time series, despite changes in the source used to generate these data. It changed from LES to the Ministry of Justice’s Case Management System from 2004 and from the Department of Corrections’ Integrated Offender Management System from 1999 (Statistics New Zealand 2016).
NZ Police, in collaboration with Statistics New Zealand, have recently undertaken a significant overhaul of the nation’s official recorded crime statistics. The redevelopment has included adopting a National Recording Standard for Crime, based on the Australian National Crime Recording Standard. It also involved undertaking a quality improvement project from 2009, redeveloping underlying data warehousing, revising the nation’s key official crime statistics to expand information relating to victims, and moving towards greater alignment to Australian counting rules (Knight et al. 2016). Similarly, the Ministry of Justice’s redevelopment of criminal court and prison information has moved New Zealand towards an integrated justice sector data warehouse, allowing exploration of system-wide justice data (Statistics New Zealand 2013a). The Australia and New Zealand Standard Offence Classification developed by ABS has been adopted by New Zealand, as have the counting rules used in generating recorded crime statistics (Statistics New Zealand 2015a, b). Unfettered by the challenges of compa- rability arising in Australia from the federated model where states and terri- tories have different justice systems, New Zealand as a single jurisdiction has been able to focus efforts into data improvement. Cross-government part- nerships and the Integrated Data Infrastructure and Information Sharing Project are unlocking opportunities for sophisticated analysis between justice and other key government datasets.
5 Crime and Justice Data 69 Key Contemporary Data Sources
There are two primary types of crime and justice data generally available to both criminologists and policy makers, namely administrative by-product data and survey-generated information. While project-specific or one-off data collections can also be undertaken, this chapter focusses on major data sources available for use by criminologists.
Administrative Data Sources
Administrative by-product data are generated as part of the daily business practices and transactions of an institution or entity. In the criminal justice system, information collection may serve an evidentiary or justice adminis- tration process; support operations; drive planning and effective management of the justice system; or acquit reporting requirements to an oversight mechanism. Administrative by-product data represent a low-cost source of information. Furthermore, it is highly relevant to the justice process and comprises a census of all documented activities within it. However, depending on the level of rigour applied during collection, data quality may vary considerably. Moreover, the scope of data collection can be restricted to include only that which is required for the business of justice to take place. Both of these challenges represent noteworthy limitations to administrative by-product data.
A seamless view of the criminal justice system cannot be generated. Transitions between institutions of the justice system are challenging to observe in data collections. For example, police-recorded crime and court data may not align due to alterations during the intervening prosecution stage for which data are not published. Most states and territories in Australia struggle to track individuals or business entities throughout the justice system, requiring statistical linkage techniques to integrate data from disparate infor- mation systems. New Zealand’s more comprehensive unique identifiers— primarily the Personal Record Number as established through the Justice Sector Unique Identification Code 1998—may assist in criminal justice system anal- yses. Where datasets remain consistent over time and contain personal iden- tifiers, administrative data can support longitudinal analysis. The longitudinal analysis supports exploration of criminal trajectories, pathways through the justice system, and desistance, especially when augmented with other data sources (Stewart et al. 2015).
70 F. Dowsley and T.C. Hart
Criminal justice agencies release data directly to researchers and the public. They also provide information to national data collections about crime recorded by states and territories,4 about criminal court finalisations, and about people in the custody or under the supervision of corrective services. These collections are primarily published by the ABS, AIHW, AIC, or Statistics New Zealand. Information about operations—such as costs or personnel numbers—are published to a limited extent by the Productivity Commission in their Report on Government Services in Australia, and need to be sourced directly from agencies, or become available through annual reporting obligations. Statistics New Zealand publishes a range of Tier 1 statistics—designated as the most important statistics to inform decision-making—from data provided by the criminal justice system (Statistics New Zealand 2013b).
Table 5.1 Key administrative crime and justice sources in Australia and New Zealand
Collection type Police
Examples of topics covered
Defendants; cases; adjudication; sentencing
Prisoners; people under supervision; remand prisoners; expected time to serve; prior imprisonment; breaches and escapes
• Recorded crime,
victims (ABS cat.
• Recorded crime,
cat. no. 4519.0) • Criminal courts
(ABS cat. no.
4513.0) • Federal
defendants (ABS cat. no. 4515.0)
• Prisoners in Australia (ABS cat. no. 4517.0)
• Corrective services (ABS cat. no. 4515.0)
• Juveniles in detention (AIC)
• National juvenile justice national minimum dataset (AIHW)
• Deaths in custody (AIC)
• Crime and
• Integrated data infrastructure
Table 5.1 (continued)
5 Crime and Justice Data 71
Collection type Coronial
Hospital and emergency admissions
Examples of topics covered
Homicide victims; alleged
Perpetrators; circumstances of death
Injuries and poisonings with external cause
Attendances; injury; overdose
Characteristics; notifications; substantiations
examples examples National coronial information system
• Causes of death (ABS cat. no. 3303.0)
• National homicide monitoring program (AIC)
National hospital morbidity database (AIHW)
State and territory data sources
Child protection national minimum dataset (AIHW)
• Mortality data (Ministry of Health)
• deaths (Statistic NZ)
Various Ministry of Health data
Serious injury outcome indicators (Statistics NZ)
• Integrated data infrastructure (Statistics NZ)
• Substantiated abuse findings (Child, Youth and Family)
Coronial court data and causes of death data collections are vital sources for homicide researchers and include rich details of individuals and events. Non-criminal justice datasets of interest include those generated by emer- gency services and health institutions. These datasets can support exploration of injury arising from violence, which may be unreported to criminal justice authorities or drug-related harm information. Table 5.1 summarises key contemporary administrative crime and justice datasets.
Survey Data Sources
Survey data collected by institutions, commercial research companies, or researchers directly from respondents can provide insights into experiences with crime and into attitudes of the general community or specific sub-populations to safety, crime, and justice. There are several key advantages of survey data. It can produce estimates of crime prevalence in the community and the proportion of crime reported to justice authorities. Respondents can disclose experiences in a confidential survey setting without fear of
72 F. Dowsley and T.C. Hart
consequences. Surveys can collect more detailed information about experiences with and perceptions of crime, impacts on victims, and responses to crime by authorities. Interactions between feelings of safety, trust in institutions, and experiences with crime and other factors in a person’s life can be explored. Surveys can reach those who are less likely to access the justice system, and surveys of offenders, in particular, can provide unique understandings of their experience of the justice system and factors contributing to offending.
Key limitations in survey data include issues around recall, fatigue, honesty, and the simplification of complex concepts to enable data collection. Moreover, surveys are limited to offences that an individual or entity has knowingly experienced. It can be challenging to obtain sufficiently large samples through survey methodologies to provide reliable estimates for small groups or sub-populations and for rare crimes. Finally, surveys can be expensive to conduct, and response rates are in decline.
Household victimisation surveys collect respondents’ experiences of selected crimes against the persons and households. They are crucial for determining the reporting rate for key offences—the proportion of crime that becomes known to police—and for validating police-recorded crime statistics (ABS 2011b). Such surveys can produce attitudinal measures such as feelings of safety, per- ceptions of social disorder, trust in the justice system, as well as self-protection and security measures. Similar surveys can also be conducted with businesses and other entities as respondents. Self-report surveys ask respondents to disclose antisocial or criminal behaviours. They have a long history in criminology, particularly to explore more low-level delinquent offending and to gather information about patterns of respondents’ illicit drug usage.
In recent decades, Australia has run a higher number of national victimi- sation surveys than other comparable countries (UN Office on Drugs and Crime 2010). This is, arguably, a sensible course of action given the ongoing lack of comparability in administrative crime data. Table 5.2 summarises key crime and justice surveys.
Australia has been a world leader in the collection of high-quality data about the sensitive topics of intimate partner and family violence and sexual violence through the development of the Personal Safety Survey (PSS). The precursor survey, the Women’s Safety Survey (WSS), was run by the ABS in 1996, followed by the 2005, 2012, and 2016 PSS, which added men to the survey sample. The PSS surveys maintained significant continuity, allowing exploration of an underreported and often overlooked area of victimisation over time. The strength of this survey comes from the methodology employed. Face-to-face interviews are conducted in a private setting by experienced interviewers. The International Violence against Women Survey
5 Crime and Justice Data 73 Table 5.2 Key surveys relating to crime and justice in Australia and New Zealand
Type of survey
Examples of topics covered
• prevalence of
crimes within the
• Crimes reported to
• Number of
• Actions taken by
victims of crime • Prevalence of crimes within
• Crimes reported to
police or regulators • Number of
• Actions taken by
• Industry and
• Delinquent and
• Illicit drug use
• Feelings of safety in specific locations and at specific times
• Perceptions of social disorder
• Perceptions of and trust in institutions of the criminal justice system
• Personal, household, or business security measures taken
• Costs incurred
• Crime victimisation (ABS cat. no. 4530.0)
• General social survey (ABS cat. no. 4159.0)
• National Aboriginal and Torres Strait Islander social survey (ABS cat. no. 4714.0)
• Personal safety survey (ABS cat. no. 4906.0) • Personal fraud survey
(ABS cat. no 4528.0)
• Crimes against business
survey (Walker 1994)
• Retail crime and safety
Prevention Unit 1998) • Crimes against small
business survey (Perrone
NZ crime and safety survey (NZCASS) (Ministry of Justice 2014)
Retail theft and security survey (Guthrie 1999)
Attitudes and perceptions
• Drug use monitoring
Various private sector surveys whose
availability is unknown
• Illicit drug reporting system (IDRS) (NDARC) • National drug strategy
• Crime victimisation (ABS
cat. no. 4530.0)
• General social survey
(ABS cat. no. 4159.0) • Personal safety survey (ABS cat. no. 4906.0)
• National community attitudes to violence against women survey (NCAS) (VicHealth)
Home safety and security survey, WA (ABS cat. no. 4526.5.55.001)
Cannabis use (Ministry of
NZ crime and safety survey (NZCASS) (Ministry of Justice 2014)
74 F. Dowsley and T.C. Hart
conducted by AIC in 2002/2003 allowed some international comparisons on this topic, albeit through a different telephone-based interview methodology. Other regular victimisation surveys have included the ABS Crime and Safety Survey, which ran irregularly from the 1970s and evolved into the annual Crime Victimisation Survey, which has been conducted since 2008/2009. The Crime Victimisation Survey format has allowed exploration of additional modules exploring social disorder and feelings of safety, for example. Regular national survey data in New Zealand are available from the Crime and Safety Survey conducted by Statistics New Zealand. Australia and New Zealand both participated in several waves of the International Crime Victimisation Survey in the past, allowing some international comparisons: Australia in 1989, 1992,
2000/2001, and 2004/2005 and New Zealand in 1992 and 2004/2005. Surveys of crime against businesses are more often conducted by private companies and professional services firms, and an exception was an AIC small
business criminal victimisation survey in the 1990s.
Major self-report studies include the AIC’s Drug Use Monitoring in
Australia (DUMA) survey, querying respondents in police custody about illicit drug use and its relationship to criminal activities combined with uri- nalysis components since 1999 (Coghlan et al. 2015). The AIHW National Drug Strategy Household Survey is another example (AIHW 2014), pro- ducing crucial estimates of illicit drug usage and harms across the community. In New Zealand, similar data are collected through the NZ Ministry of Health (2010, 2015).
Gaps in Core Crime and Justice Data Collections
ABS and Statistics New Zealand undertook consultations in the 2000s to identify the key data development requirements in the national crime and justice collections. The ABS published its findings and future directions in the National Information Development Plan for Crime and Justice Statistics (2005). Statistics New Zealand published its findings in the Review of Crime and Justice Statistics (2009). Key gaps and areas of deficiency require data development activity and investment to meet the needs of researchers and policy makers. This includes: (1) more comprehensive and complete crime and justice data relating to Aboriginal and Torres Strait Islander peoples, particu- larly given the historical lack of inclusion of Aboriginal and Torres Strait Islanders in justice statistics until the latter part of the twentieth century (Graycar and Grabosky 2002), and growing overrepresentation as both victims and offenders; (2) data relating to the experience of specific groups, such as
culturally and linguistically diverse communities or people with disability as offenders and victims; (3) data relating to stages of the justice system not currently included in the national statistical collections, such as prosecution processes and post-corrective services release activities; (4) measures of family violence—beyond surveys providing community prevalence and incidence estimates—which effectively demonstrate engagement with justice institu- tions, government social service systems, and third sector service providers; (5) technologically enabled cybercrime or electronic crime as well as many related variants of transnational crime; (6) terrorism-related offences and other Commonwealth offences that are only visible from courts system onwards in many cases; (7) any crime groupings which are based not upon offence type, but upon the context in which the crime occurs, for example, crimes related to organised crime which can only be determined sometimes after the fact, or gang-related activity; and (8) drug-related crime and the involvement of drugs and alcohol in criminal offending and victimisation. It should be noted that many of these shortcomings in existing national data collections remain exceptionally difficult to overcome, due to conceptual difficulties and limita- tions inherent in the jurisdiction of different justice institutions.
Challenges for Researchers
This chapter has outlined a number of data challenges for criminologists, such as gaps and limitations in quality, quantity, breadth, depth, and coverage on specific topics of interest. Further challenges for researchers working in Australasia may include the cost of accessing information; the cost of data production; gaining approval to access data sources, particularly for researchers who seek to negotiate with institutions whose main remit is not the release of data; and issues around ethics, confidentiality and privacy (Israel 2004). The latter may prove particularly challenging for researchers who look to work across different institutions and jurisdictions, where procedures, policies, and practices may vary.
While limitations exist, there are emerging opportunities for data-driven criminologists to explore which will lead to new perspectives on observable crime and justice issues. The increasingly affordable range of analytical tools
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76 F. Dowsley and T.C. Hart
available—combined with pushes towards open data releases by governments —will transform quantitative research opportunities.
Location-related data are playing an increasingly important role in crimi- nology. A growing number of spatially referenced datasets are becoming available and at no cost. Street network and address point data, administrative boundary files, and location-based socio-demographic information are now easily accessible. The backbone of this work finds itself in initiatives such as the Geo-Coded National Address File (G-NAF) that provides accessible and comprehensive address and boundary data on state, suburb, street, number, and geographic coordinates for street addresses. Similarly, the Administrative Boundaries dataset—which the government released via PSMA Limited in 2015—contains ABS boundaries, electoral boundaries, state and territory boundaries, local government areas, suburbs, wards, and town points. Every year, Statistics New Zealand releases geographic data that can be linked to boundaries files; that can be used to define mesh-blocks, area units, wards, or regional council areas; and that can be joined with other spatial or non-spatial data. These regularly updated resources, combined with crime data, support place-based criminological studies.
Data linkage techniques have been used in the social sciences for some time. Crime and justice research in Australia and New Zealand has been slow to take advantage of emerging techniques, which have, for example, flour- ished more readily in the health fields (Ferrante 2009). Given the discon- nected information systems proliferating across criminal justice in Australia and New Zealand, data linkage provides the only readily available method for conducting research about the pathways individuals take through the criminal justice system, enabling sophisticated studies of recidivism, criminal careers, and trajectory studies. Due to the granular level of data required for linkage, agencies located within or adjacent to criminal justice agencies have a par- ticular advantage in developing data linkage studies. Collaborative arrange- ments between the academy and government entities will open up greater opportunities to produce knowledge.
Developments in big data analysis are yet to fully impact upon criminology. Crime and justice data have traditionally been contained to datasets generated through set research activities such as surveys or has been created as citizens interact with the criminal justice system. As we are unquestionably moving into the so-called big data information age, opportunities will emerge for criminologists and data scientists—or indeed, quantitative criminologists—to reimagine the current methods and uses of criminal justice data. These new approaches may assist us to overcome some inherent limitations in current data, and create new ways of studying crime, perceptions of crime, and impacts
on individuals and the community. As the increasingly digital interactions that individuals have with the world create new data sources, such as social media data or sensor information, new prospects for analysis emerge. Many of the techniques that were historically the purview of intelligence analysts may now increasingly be useful to researchers. Through the application of big data tools and techniques, researchers are able to identify patterns, trends, and rela- tionships in large, unstructured datasets. As new digital landscapes open up to both criminality and the practice of justice and regulation, so criminologists must follow, taking advantage of new tools and techniques.
Today, Australian and New Zealand researchers and policy makers have access to more administrative crime and justice data than ever before. Detailed information about crime victims, offenders, and offences can be gleaned from crimes recorded by police. Similarly, criminal court data provide insight into the adjudication of criminal cases and the sentencing of those convicted. Finally, corrective services data contain details of prisoners and those under correctional supervision. Other administrative data such as hospital and emergency admissions are also available and can be used to develop a more comprehensive picture of crime and justice in Australia and New Zealand.
A growing number of survey datasets have also emerged over the years. For example, victimisation data, as well as data on attitudes and perceptions of crime, are available from national surveys such as Australia’s General Social Survey and New Zealand’s Crime and Safety Survey. Other self-reported survey data are available from the Drug Use Monitoring in Australia (DUMA) Survey and the National Drug Strategy Household Survey.
Despite existing administrative and survey datasets in Australia and New Zealand, there are clear deficiencies in some areas. For example, more information about cybercrime and terrorism-related offences is needed, and the interconnectivity of extant datasets also needs to increase. Whether these needs will be met in the future is uncertain, but what is clear is that as new sources of data emerge in Australia and New Zealand, so does the opportunity to discover and develop new ideas and ways of thinking about crime and crime-related issues.
5 Crime and Justice Data 77
78 F. Dowsley and T.C. Hart Notes
1. SeehistoricalYearBookspublishedbyABSandStatisticsNewZealandforcrime, criminal courts, and prison statistics dating back to the nineteenth century.
2. For a detailed account of 1960–1980 attempts at national uniform crime
statistics, see Mukherjee et al. (1987).
of comparability challenges within the national recorded crime collections.
4. The national recorded crime collection excludes matters dealt with AFP and
Commonwealth law enforcement agencies.
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Matthew Willis. 2015. Drug Use Monitoring in Australia: 2013–14, Report on
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Development of Official Statistics. In ABS Year Book Australia, 1988. Cat. no.
1301.0. Canberra: ABS.
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Criminal Justice. In The Cambridge Handbook of Australian Criminology, ed. Adam Graycar, and Peter Grabosky, 7–26. Port Melbourne: Cambridge University Press.
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Knight, Gavin, Anand Krishnan, and Ange Bissielo. 2016. The Transformation of NZ Police Crime Statistics: New Measures and Trends. Wellington: NZ Police.
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80 F. Dowsley and T.C. Hart
Fiona Dowsley is founding Chief Statistician of the Victorian Crime Statistics Agency, a Director of the Victoria Sentencing Advisory Council, and former Director of the ABS NCCJS. She led the measurement of national progress and social trends analysis and contributed to the global UNODC task force on the development of an international classification of crime.
Timothy C. Hart is a Senior Lecturer at Griffith University. He received his PhD in criminology from the University of South Florida. His research focusses on applied statistics, survey methodologies, and geographic information systems. Tim has worked for the BJS and the DEA. He is the co-author of Space, Time and Crime and The Mismeasure of Crime.
Mapping Common Crime
Jason L. Payne and Fiona Hutton
Public perceptions of crime and safety are shaped by a number of factors, not least the extent to which crime statistics are publicised across a range of media formats. In a national survey, more than 8 in every 10 Australian adults rated television and newspapers as very or fairly important sources of their infor- mation about crime (Roberts and Indermaur 2009), while in a more recent New Zealand survey, an equivalent proportion of respondents also considered TV news and hard copy or online newspapers to be reliable sources of information about crime (Colmar Brunton 2014). Although there remains some debate about whether traditional and social media actually portray an accurate picture of crime, there nevertheless exists some compelling evidence of disproportionate, inaccurate, and often sensationalised media coverage of atypical crimes, including offences such as homicide or acts of sexual violence carried out by strangers in public places (Duffy et al. 2008; Garvey 2003).
Coupled with a reliance on the media as a principal source of information about crime, the potential misuse and misinterpretation of official crime statistics can have significant consequences. As Davis and Dossetor (2010) argue, the inaccurate reporting of specific criminal incidents or crime statistics
Jason L. Payne (&)
Australian National University, Canberra, Australia e-mail: firstname.lastname@example.org
Victoria University of Wellington, Wellington, New Zealand e-mail: email@example.com
© The Author(s) 2017 113 A. Deckert and R. Sarre (eds.), The Palgrave Handbook of Australian and New Zealand
Criminology, Crime and Justice, DOI 10.1007/978-3-319-55747-2_8
114 Jason L. Payne and F. Hutton
can play an important role in shaping community misperceptions about crime. Their study shows that the overwhelming majority of Australians held incorrect views about national crime trends, with 9 in 10 respondents con- vinced that crime was increasing or stable over a period of time when crime was actually in considerable decline. In New Zealand, similar issues have been noted. Nearly three-quarters of respondents believed that violent crime and youth crime had increased (Colmar Brunton 2014; see also Paulin et al. 2003) despite youth crime being at its lowest level for 20 years (Ministry of Justice 2013), and the fact that overall recorded crime rates have decreased since 1996 from 477,596 recorded offences in 1996 to 350,389 in 2014 (NZ Police 2015). This overestimation of crime is also somewhat at odds with the fact that most New Zealand residents considered the crime problem of their local community to be less concerning than the national crime problem (Bradley et al. 2010). In the 2014 New Zealand Crime and Safety Survey (NZCASS), 69% of respondents did not think that crime was a problem in their own neighbourhood (Ministry of Justice 2015).
With the general public holding distorted perceptions about crime, there is a real risk of inappropriate policy prioritisation and the misguided targeting of resources. Fear of crime has the potential to be as big a threat as crime itself, with public (mis)perceptions fuelling fears about particular types of crimes and offenders (Sparks 1992). Underpinning these complex debates is a series of important questions about the nature and scope of crime reporting, in particular, the preparation, publication, and presentation of crime statistics, and the stories they tell about common and infrequent crimes. Through a critical lens, this chapter explores those crimes depicted in Australia and New Zealand as the most common in officially recorded police statistics. Using illustrative examples and case studies, it is suggested that greater caution is needed to ward against an overreliance on official crime estimates as the principal vehicle for public and policy debate in both countries.
Although there is no universally agreed definition of common crimes, information about crimes which are apparently common has never been more accessible to the general public. With widespread access to the Internet, a simple search for crime statistics will identify a source for the most recent, publicly available information. In New Zealand, national data are available through both the NZ Police and Statistics New Zealand. In Australia, the complexities of federation mean that while state—and territory-specific data may be reported by the relevant police agencies, the compilation of national
crime data is solely undertaken by the ABS. In both countries, these data are reported either as a unique count of offenders or of victims of crime. Both data sources are needed, since not all crimes involve personal victimisation— for example, drug offences—and not all incidents of victimisation result in the identification and apprehension of an offender.
For offender counts, two data sources are available. The first counts the number of unique offenders according to the most serious or principal offence for which they were apprehended. There were 411,686 unique offenders in the financial year 2014–2015. The four crime types for which there was the highest number of unique offenders were illicit drug offences, acts intended to cause injury, public order offences, and theft offences (ABS 2015a) (Fig. 8.1).
Rather than counting unique offenders, the second data source presents a count of the number of times each unique offender is proceeded against, either through court or non-court action such as diversion. This data set is only compiled for six of the eight states and territories, excluding the Northern Territory and Western Australia. In the financial year 2014–2015,
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Illicit drug offences Acts intended to cause injury Public order offences Theft Offences against justice Miscellaneous offences Property damage Fraud/deception Prohibited/regulated weapons Unlawful entry with intent Sexual assault Abduction/harassment Robbery/extortion Dangerous/negligent acts
Fig. 8.1 Unique offenders (number) by offence type (Australia, 2014/2015). Source Adapted from Recorded Crime: Offenders, Australia (ABS 2015a)
3,162 2,109 06
116 Jason L. Payne and F. Hutton
Theft Illicit drug offences Public order offences Acts intended to cause injury Offences against justice Miscellaneous offences Property damage Unlawful entry with intent Fra ud/d ec ept ion Prohibited/regulated weapons Sexual assault Abduction/harassment Robbery/extortion Dangerous/negligent acts Homicide
Fig. 8.2 Offenders proceeded against (number) by offence type (Australia, 2014/2015). Note Data excludes Western Australia and the Northern TerritorySource Adapted from Recorded Crime: Offenders, Australia (ABS 2015a)
a total of 585,453 offenders were proceeded against by police, and the three most common offence types were theft, illicit drug, and public order offences (ABS 2015a) (Fig. 8.2).
Other theft Unlawful entry with intent Motor vehicle theft Sexual assault Robbery Kidnapping/abduction Blackmail/extortion Homicide and related offences
Fig. 8.3 Victims of crime (number) by offence type (Australia, 2014/2015). Source Adapted from Recorded Crime: Victims, Australia (ABS 2015b)
550 527 421
As indicated earlier, victim data provide a rich and alternative insight into the nature and extent of crime in both countries. Unlike offender counts, victim data exclude offences for which there was no victim but include those crimes for which there was a victim report of victimisation. An incident of victimisation may be counted for any person, premises, organisation, or motor vehicle against which an offence was committed and reported. In 2014, there were a total of 717,281 victimisations, with theft far outnumbering the victims of sexual assault and robbery (ABS 2015b). Of the theft victims, the largest subgroup was the victims of ‘other theft’, followed by burglary (Fig. 8.3).1
In New Zealand, the way common crimes are counted has recently changed. Until 2014, national police statistics were reported twice a year. These statistics reported on recorded offences, that is, matters reported to or dis- covered by police where it was believed an offence was likely to have taken place (NZ Police 2015). The most common crimes under this system are noted in Table 8.1.
There are some interesting issues to note about the crimes that make up these most common categories of offending recorded by NZ Police. The category theft and related offences includes a large number—approximately 50,000 offences—of motor vehicle thefts. The property damage and environ- mental pollution category is almost exclusively made up of property damage offences such as vandalism and graffiti with only few offences relating to environmental pollution. The illicit drugs offences category is largely made up of possession offences. All of the crimes recorded in this category are what is referred to as ‘drug defined crimes’: crimes that are committed because the use, possession, manufacture, cultivation, dealing, and trafficking of some drugs are
Table 8.1 Recorded offences New Zealand 2012–2014
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ASOC division Description
Theft and related offences
Unlawful entry with intent/burglary,
break and enter
Property damage and environmental
Acts intended to cause injury Public order offences
Illicit drugs offences
Source Adapted from NZ Police (2015, 5)
Recorded Recorded 2012 2013 119,476 121,035 52,937 52,247
40,851 39,447 42,522 35,850 20,792 16,069
Recorded 2014 119,323 53,265
39,944 26,751 16,543
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illegal under the law (Coomber et al. 2013). Furthermore, proactive policing campaigns focussing on particular crimes can affect the official statistics with a larger number of crimes than usual being recorded. For example, in 2008, New Zealand introduced the STOP (stop tagging our place) strategy with both media and police focussing on graffiti and tagging offences.
From 2014, NZ Police changed the way they recorded offences. Under this system, Recorded Offender Statistics (RCOS) count how many times police take action against offenders, that is, charges, warnings, court action, etc. Each separate occasion that the police proceed against an offender is recorded in the RCOS. The most common crimes under this new system were traffic —and vehicle-related offences, acts intended to cause injury, and theft and related offences (Statistics New Zealand 2016).
In 2014, NZ Police also introduced a new method of counting victims of crime, using Recorded Crime Victim Statistics (RCVS), which are based on the Australian system. However, the recent introduction of RCVS makes it difficult to compare data from previous years. RCVS exclude those offences that police record for charging purposes. For example, in a murder case where only one victim was killed, two offenders could be charged with different offences: murder with a firearm and murder with a knife. The new RCVS system counts ‘1’ for each broad offence type so that victims are counted only once, regardless of the number of offenders (NZ Police 2016). Under this new system, the most common victimisations were theft and related offences; unlawful entry with intent, burglary, and break and enter; and assault (Statistics New Zealand 2016). In the RCOS, however, traffic and related offences are the most common with theft and related offences counted as the third most common. Therefore, depending on what set of statistics are used, a different count of common crimes is arrived at. Gaining an accurate picture of the most common crimes is a complex undertaking. It could be argued, however, that separating out victims and offenders in this way can give a more accurate picture of crime and victimisation.
It is also important to note that the RCVS exclude ‘victimless’ crimes such as drug and public order offences (NZ Police 2016), while these offences are still included in the RCOS. Excluding these offences from the RCVS is said to make crime counts and crime trend analyses more reliable. This is because statistics on drug and public order offences were mostly affected by proactive policing operations, rather than representing an actual increase in reporting (NZ Police 2016). Therefore, trends in policing may determine any increase or decrease of certain crime types. Due to the numerous complexities and difficulties in counting common crimes, the picture painted by official statistics in terms of common offences is often partial and incomplete.
8 Mapping Common Crime 119 The Complexity of Crime and the Problem
of Official ‘Bias’
Although accessing official data about common crimes in both countries has never been easier, what remains is the often complex and difficult challenge of understanding what the data represent about individuals who commit crime and the communities in which these crimes occur. First, it must be acknowledged that there is no single or simple definition of crime. For some scholars, crime ought to be unproblematic, best defined as acts which con- stitute a direct contravention of existing criminal laws and codes. For others, crime is an elusive concept often used as a catch-all term to describe a broader continuum of acts, of which only some are legally defined as crimes. As Sampson and Laub (2003) note, the key challenge for criminology is not the counting of crime but rather in deciding what ought to be counted, when, and how best to interpret this data in the absence of any clear definition of crime and criminality. Labelling theorists such as Becker ( 1973, 8–9) also note that crime and deviance were not fixed categories, and that these labels are socially constructed: ‘Social groups create deviance by making rules whose infraction creates deviance, and by applying those rules to particular people and labeling them as outsiders. From this point of view, deviance is not a quality of the act the person commits, but rather a consequence of the application by other of rules and sanctions to an “offender”. The deviant is one to whom that label has been successfully applied; deviant behavior is behavior that people so label’. What counts as crime is, therefore, not as straightforward as it might first appear, and these scholarly contributions act as important and timely reminders that crime is, at the very least, socially undesirable behaviour for which there is no perfect method of quantification.
Those who commit crime—however defined—typically spend much of their time trying to avoid formal detection and official apprehension. At best, therefore, official records likely represent only a very small and skewed subset of all crimes that are actually committed (Sampson and Laub 2003). Alternative methods, such as self-report surveys of offenders, might appear to offer a promising alternative with a range of new insights, but even these methods are themselves plagued by significant limitations (see Payne and Piquero 2016). What is important, therefore, is to recognise that those crimes identified as ‘common’ in official statistics are biased in a number of ways.
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Underreporting of Crime
Commonly recorded crimes in official data are heavily biased towards those crimes that are frequently reported to police. Only a small fraction of all crimes are happened upon by police during their general duties. Consequently, underreported crimes may never appear as common as they might actually be. Family, domestic, and sexual assault, for example, are notoriously underreported by their victims (Carbone-Lopez et al. 2016; Moore and Baker 2016); often out of fear of retribution by the perpetrator or because such matters are deemed too private, trivial, or unable to be acted upon by police (Ministry of Justice 2015). Crime that is reported to the police is often referred to as the ‘tip of the iceberg’, with the majority of crime unreported and hidden from view. This is commonly referred to as the dark figure of crime (Radzinowicz and King 1977).
Weighed against this apparent underreporting of sexual and other inter- personal crimes are the comparatively high rates of reporting for property crimes such as home burglary and motor vehicle theft. Unashamed of their status as a victim of property crime (Bowles et al. 2009) and often motivated by insurance companies’ requirement to file a police report for financial compensation (Myers 1980), victims of property crime are far more likely to report their experience to the police and have their experience as victims counted in official statistics. This is not to say that all victims of property crime report to police, only that these crimes are disproportionately reported. Hence, they might appear more common relative to other unreported crime types. For example, the 2013 NZCASS noted that 68% of crime was not reported to the police and 41% of incidents were not considered crimes by the victim (Ministry of Justice 2015). So, whatever the crime type, under- standing of what is common and what is not is limited to that which is reported to police. Without doubt, most crimes, but in particular interper- sonal crimes, are more common than indicated by official statistics.
Operational and Administrative Issues
Official data are collected from the administrative systems of police and other criminal justice agencies. These systems are designed to meet operational needs above all others, to facilitate and streamline police activity. Crime statistics extracted from these systems inherit some degree of operational bias. Here, the term ‘operational bias’ is used to describe the many ways in which officially recorded data reflect the operational imperatives and decisions of
their collection practitioners. This includes priorities and directives of Police Commissioners and on-the-spot decision-making by frontline officers about where to police, what to target, and whom to apprehend. At a very rudi- mentary level, crimes are typically recorded and counted with reference to the date on which each matter was reported or processed, not necessarily the date on which the actual crime occurred. In the vast majority of crimes, these dates are not the same, and for some crime types, such as sexual assault, the date of reporting and processing can be many years apart. At the more complex end, there are those policing strategies, such as ‘hot spot’ targeting, which also have the potential to influence what is counted as common, especially when comparing specific geographical locations and policing areas. Proactive efforts to target specific crime types or offenders will likely increase the apparent frequency of specific crimes or the apprehension of specific types of offenders, such as happened during the ‘war on drugs’ in the USA (Stevens 2008).
In Australia, the implications of these operational practices have been most consequential for the measurement of physical assault. At the time of writing, national victimisation statistics still exclude crime counts for common or aggravated assault. This is largely due to the significant operational differences which prevent compilation across different data sets and limit reliable inter-jurisdictional analysis. Specifically, in Victoria, a victim report is usually only recorded where an investigation has been conducted and where it has been determined that a crime was committed. Similarly, in Queensland, assaults are not recorded unless the victim consents to the matter being investigated, whereas in most other jurisdictions, victimisation records are created for every victim report, irrespective of the eventual outcome.
The important issue of Indigenous overrepresentation in the justice system sits as yet another reminder of the potential for operational bias to influence who and what gets counted in official crime statistics. In New Zealand, Māori make up approximately 15% of the general population, but over 50% of the prison population (Department of Corrections 2009). For particular offence categories, this overrepresentation is glaring with Māori being three times more likely to be arrested and convicted for cannabis use than non-Māori (Fergusson et al. 2003), as well as being more likely to be prosecuted and convicted of possession or use of an illicit drug or drug utensil. Racial and ethnic disparities are a common theme in the crime statistics of many countries (Eastwood et al. 2013; Human Rights Watch 2008). For the specific case of New Zealand, the UN has urged the government to address this human rights violation it regards as arbitrary detention (UN News Centre 2014). Māori are also more likely to be imprisoned than receive a community sentence and also receive longer prison sentences for similar P
PaYne,J.L.,Hutton,F.(2017)Mapping common crime. In A.DECKERT &R.Sarre(Ed’s.), The PLAGRAVE HANDBOOK of Australia and New Zealand criminology, crime and Justice(pp.113-129). Cham,Switzerland : Palgrave MacMilan.
committed by non-Māori (Quince 2007). Most scholars agree that these apparent differences result, in part, from the way in which certain minority populations are policed (Cunneen and White 2007). This is a significant issue that should be noted when considering the processes involved in counting crime, particularly in settler-colonial jurisdictions such as New Zealand and Australia.
Apart from recording biases that concern data input, data output biases can also affect our understanding of common crimes. Data output bias concerns the methods and techniques used by analysts to extract and make sense of data. Such techniques are often described as counting rules and represent a set of standardised parameters designed to maximise the degree of consistency between multiple data recording systems. In Australia, recorded crime data sets are collated individually from each of the eight states and territories and combined into a single system for analysis. This ‘bringing together’ of dif- ferent data systems—each developed for distinct operational environments, and subject to different organisational practices—necessarily requires a pro- cess of standardisation, and the application of consistent counting rules. With a single police service in New Zealand, the complexities of amalgamating statistics from different jurisdictions are less apparent, and as a non-federal state, New Zealand does not face the same issues noted in the Australian context.
The consequences of this standardisation process are many and varied, often described in technical appendices and notes, and not easily digested by the lay reader. In Australia, each offender is counted only once per annual period, meaning that where a single offender is responsible for multiple crimes in any one year, only the principal crime is recorded, which is determined according to the severity scale of the Australian National Offence Index (NOI).2 The most serious crime of each year is recorded even if such behaviour is infrequent in an offender’s overall offending pattern. Consequently, crimes committed by repeat offenders are significantly undercounted, while their seriousness is overstated. Further, crimes committed by co-offenders are counted once for each co-offender. Consequently, some incidents—such as a home burglary committed by three co-offenders—may be double or triple counted. This potentially leads to the overrepresentation of crime types where co-offending is typical.
For victimisation data, a different set of counting rules applies. Unlike offender data, victimisation data are counted for each unique crime category and for each instance of victimisation throughout the year. This means that each unique victimisation is recorded, even if the same individual is vic- timised multiple times, but it also means that a single crime may be double counted in situations where a single incident involves more than one offence category or more than one victim. For example, a victim of kidnapping who was later physically and sexually assaulted would be counted three times—one each for kidnapping, assault, and sexual assault—even though the three offences were essentially the product of the same criminal incident at the hands of the one individual.
Finally, what counts as an incident of victimisation will largely depend on how the matter is reported and subsequently recorded by police. This relates to the so-called grey figure of crime, that is, crime which is reported to the police but either not recorded or recorded inaccurately. Whether an incident is recorded as one crime or multiple crimes depends on the victim recalling and reporting each specific victimisation. For example, for victims to properly enumerate cases of sexual assault over many months or years would require them to recall and report each single event. More commonly, such series of victimisations are reported as a single overall experience and are thus often counted as one crime.
As previously noted, there is no single definition of crime, and there is no single appropriate method to quantify crime and crime types. At best, the systems used to identify the most common crimes can only approximate the real rate of crime and—despite best efforts of national statistical agencies—these data systems remain challenged by various biases that have significant consequences for interpretation and use. Consequently, what is presented as ‘common’ might not readily forewarn of the most pressing concerns, but instead reflect issues of current—and perhaps misplaced—interest. Prioritisations in policy and policing activities have the potential to skew crime counts in favour of those crime types for which there is some pre-existing concern. The targeting of specific offence types potentially increases their apparent prevalence. This justifies not only the initial targeting but also warrants future targeting and expenditure to combat what is now characterised as an emerging problem. Hence, common crimes are not only those that are the most numerous, but
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also reflect those that have attracted some operational prioritisation. Common crimes not only demand increased attention from government and police, but they are also officially noted as crimes as a result of any increased resourcing and attention that is given to ‘common’ offending behaviours.
Of course, not all new policing priorities result in more frequent crime recording and, perhaps, the single largest contemporary concern for national crime data compilation is the rigidity and insensitivity of data input systems to emerge areas of criminological interest. In particular, there is reason to believe that earlier efforts to standardise both the input and output of recorded crime data have rendered those same systems inflexible to more nuanced context-specific characteristics of crime for which additional and detailed reporting is sorely needed. As has been the case in Australia recently, the quantification of family and domestic violence as a specific subset of other interpersonal violence demonstrates this problem. Physical assault, for example, is singularly recorded as either ‘common’ or ‘aggravated’ irrespective of the circumstances. Domestic violence assaults—a crime type considered by many to be both common and warranting independent quantification—are therefore unable to be meaningfully identified as a distinct subset, despite a growing public concern about the scourge of domestic violence, and despite significant financial and political investment in prevention programmes.
Crimes not Reported
Perhaps the most significant criticism of the statistical collecting of crime concerns the undercounting of crimes that are committed but never come to the attention of recording authorities. The rate of underreporting is higher for some crime types than others, in particular, personal crimes such as assault and sexual assault. For this reason, both Australia and New Zealand have continued to invest in victimisation surveys in an effort to shed some light on these hidden experiences.
In Australia, the Crime Victimisation Survey was last conducted in 2014–2015 by the ABS, implemented as an addendum to the telephone-administered Multi-Purpose Household Survey (ABS 2016). The limited capacity of the survey restricted its breadth to three personal crimes (assault, sexual assault, and robbery) and five household crimes (break and enter, motor vehicle theft, theft from a motor vehicle, other theft, and malicious property damage). Data are reported as estimates of population prevalence; for example, the proportion of the population that has experi- enced motor vehicle theft in the last 12 months. Nationally, the crime type
with the highest victimisation rate was assault with an estimated 840,500 victims, which is 4.5% of the population. Of these, 2.9% experienced threatened assault and 2.1% suffered physical assault. Of household crimes, malicious property damage was the most common, with 511,400 households or 5.7% of all households experiencing victimisation, followed by ‘other’ theft, theft from a motor vehicle, and burglary. Due to the different counting units of persons and households, a direct comparison of crime types is impractical. However, there are more individuals who experience assault (both physical and threatened) than are recorded in official statistics, and there are considerably more assault victims than there are households that experience any single form of property crime.
Attempting to access the dark figure of crime, New Zealand has under- taken the NZCASS in 2006, 2009, and 2014. The survey is conducted face-to-face with a sample of 7000 randomly selected residents. A diverse range of crime types is explored, including six household and nine personal crime types. Of the personal crimes, physical assault was recorded as having both the highest prevalence and the highest incidence with 196,000 victims and 512,000 incidents; followed by threats of violence or force with 175,000 victims and 401,000 incidents; and sexual offences with 74,000 victims and 186,000 incidents. Of the household crimes, the most common was burglary with 136,000 households and 203,000 incidents; followed by household damage with 78,000 households and 119,000 incidents; and vehicular damage with 58,000 households and 74,000 incidents. Hence, the NZCASS reports the opposite of the official police statistics, meaning that crimes of violence—particularly sexual violence—are the most common. Police statis- tics report theft and property offences as the most common. In the 2014 NZCASS, 68% of crime was not reported to the police. Victims reported that they did not report crimes because they felt the crime was ‘too trivial’ (49%), it was a ‘private’ matter (24%), or that the police could not have done anything in response (22%) (Ministry of Justice 2015). This illustrates the problems in counting common crimes and trying to estimate with any degree of accuracy the amount of crime in any given country. What constitutes ‘common crimes’ depends very much on who is asked and in what context.
Notwithstanding, the differences in methodology and measurement, both the Australian and New Zealand victimisation surveys are generally consistent in their identification of both physical and threatened assault as the most common of all personal crimes, while property damage emerges as the most common of the property crimes experienced by households. That said, both surveys also offer an important and unique insight into why this data differ from that collected from administrative sources. In particular, crime
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victimisation surveys offer a rare glimpse into the dark figure of crime by estimating the prevalence of underreporting of different offence types. In both Australia and New Zealand, only a small fraction of victims report their most recent crime experience to the police. In New Zealand, for example, only 38% of household crimes and 24% of personal crimes are reported to the police. The crime types least likely to be reported to police in both countries were personal crimes such as assault and sexual assault. NZCASS noted that a large majority of respondents did not experience any crime (76% in 2013, and 63% in 2008), but also noted that particular groups such as young people and Māori are more likely to be the victims of crime, as are those who are unemployed and those who live in state housing. Moreover, the NZCASS demonstrates that the large majority of people do not worry about crime, but that particular groups such as women and ethnic groups fear crime the most; 43% of Asian people, 41% of Pacific peoples, and 17% of Māori worry about being harassed, intimidated, or assaulted because of their ethnicity/ indigeneity (Ministry of Justice 2015). This leads us to consider the conse- quences of the recognised over-policing of Indigenous and ethnic groups, and the under-policing of the same groups as victims of crime (Cunneen and White 2007). Note also that a small number of people experience most of the crime. Some 3% of people experience 53% of all crime (Ministry of Justice 2015), demonstrating that victimisation is uneven and often concentrated amongst the most vulnerable, disadvantaged populations.
Crime statistics are an important tool for monitoring the nature and type of offending that occurs. They make possible the ranking of different offence types by frequency, allowing the most common crimes to be identified and responded to by policy makers and law enforcement practitioners. Yet, for the many reasons highlighted throughout this chapter, an overreliance on offi- cially recorded statistics could have unintended consequences, focussing attention on crimes that appear common only because their victims are more likely to report, or because they are crimes that are administratively or operationally more likely to be identified. The clear conclusion is that public discourse about crime, and thus the decisions made by governments, must be informed by multiple data sources, using a triangulation of mixed methods data collection, for what is common in officially recorded crime statistics will potentially mask some more important social problems.
1. It is important to note here that due to a range of data comparability issues, the ABS does not yet report victimisation rates for common assault.
2. Knowledge of the NOI and its compilation is important for interpretation, as it relates to the counting preferences attributed to specific offence types. The offence of drug dealing or trafficking of non-commercial quantities, a charge often imposed for the possession of quantities greater than for personal use, is ranked 21 of 157 on the NOI—higher than aggravated robbery (NOI 24), common assault (NOI 28), and the trafficking of regulated weapons or explosives (NOI 47).
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Jason L. Payne is a Senior Lecturer in criminology at the ANU. His research focusses on drugs and crime, developmental criminology, and quantitative evaluation methods. In his former role as research manager of the AIC’s Violent and Serious Crime Monitoring programme, he was responsible for a wide range of research programmes such as the DUMA programme.
Fiona Hutton is a Senior Lecturer in criminology at the Institute of Criminology, VUW. Her research focusses on young people, gender, social networking sites and alcohol, alcohol and drug use, and harm reduction. She is author of Risky Pleasures? Club Cultures and Feminine Identities, and is currently critically exploring NZ’s drug policy, with a focus on legal highs.
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