Methods of Uncovering the Dark Figure of Crime
The dark figure of crime describes undiscovered crimes committed in society, which have failed to be included within official statistics. The main methods utilized to uncover the ‘dark figure of crime’ include self-reporting surveys, victimization surveys, geospatial analysis and the Enforcement Pyramid (Coleman and Moynihan 1996). There are examples of the effectiveness of these methodologies. However, these methodologies have several practical issues. This essay will discuss the effectiveness of the ways in which hidden crimes can be discovered.
Since the 1940s, self reported studies have been a method utilized to uncover the ‘dark figure’ of crime. These studies involve asking individuals about their involvement in criminal and other forms of law breaking activity through a self completed questionnaire or interview (Coleman and Moynihan 1996). The survey works by attempting to create a safe and free environment in order to gain an accurate result (Coleman and Moynihan 1996).
Throughout history, there have been examples of the effectiveness of self surveys to uncover the dark figure of crime. Murphy’s 5 year study of American adolescent males illustrates this. From the 6416 infringements reported in the study, half of the infractions ended up in official criminal statistics (Murphy 1946). Portfield’s study of youth and students also developed a similar result. The survey uncovered hidden crimes of a pastor (Portfield 1946). In addition, the survey exposed an unreported murder. Furthermore, improvements to self-reporting have increased its dependability (Portfield 1946). In the late 1980s, James Short and F. Ivan Nye created a number of reliability checks. This increased the ability of self-reported surveys to uncover the ‘dark figure of crime.’ Their improvements included the introduction of social desirability variables (Short and Nye 1988). This resulted in increased statistical accuracy by discarding responses pertaining to those respondents who stated that they never committed marginal criminal behavior. Further, it disqualified exaggerations of crimes and inconsistence responses (Short and Nye 1988). This demonstrates that the dark figure of crime can be uncovered in surveys.
While self-reporting surveys have been useful tool in uncovering hidden crimes, there are methodological issues. The problem with self-reporting surveys is that they focus on trivial crimes. According to Box, trivial crimes are unlikely to produce a formal response from the criminal justice system particularly with adolescents (Coleman and Moynihan 1996). Therefore this produces a skewed result in which official figures are considered inaccurate. It is also important to note that some valid items have a tendency to produce high rates of trivial acts (Coleman and Moynihan 1996). A prime example occurred in the National Youth Survey. It was a longitudinal survey based on households of youths aged 11-17. The survey was notorious for the vast majority of initial responses being trivial, indicating the need to be careful about the wording of items and to have follow-up questions about the exact nature of incidents (Coleman and Moynihan 1996).
Non-response in self-reporting surveys is problematic as it can result in the under-representation of key groups. The main problem is individual’s willingness to engage with the survey (Coleman and Moynihan 1996). Hinderlang discovered that contact with the sample groups was easier with non-criminals, with a 1.3% non-location rate, as apposed to criminals, which consistently had a non-location rate of approximately 48.5% (Hinderland 1976). However, police classified delinquents were the most likely group to agree to participate in the research once contacted with rates of participation ranging between 41.1% and 83.8% of those located. Junger-Tas reports a sliding scale of response rates, more or less according to the degree of the contact with the criminal justice system, ranging from 60% for those with no contact, to 34% for those with recorded police contact (Junger-Tas 1989). The conclusion that can be attained from these statistics is that self-reporting surveys are unable to produce an accurate figure of uncovered crime as it under-represents certain groups.
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victimization surveys attempts to uncover hidden crime by surveying a representative sample of a chosen population over crimes committed against them (Coleman and Moynihan 1996). Unlike self-reported studies, victimization surveys survey the victim rather than the perpetrator. Those who utilize this technique are aiming to capture crimes, which do not enter official statistics as they are unreported. If similar surveys are carried out over intervals of time, then crime trends can be discovered (Coleman and Moynihan 1996). There are three main types of victimization surveys: local, national and international. Local surveys are small scale and geographically focused. They concentrate on a particular vulnerable social group (Coleman and Moynihan 1996). National surveys, such as the British Crime Survey, examine a larger group of individuals to gain an overall idea of the extent of crime. They are conducted in partnering countries, which are then compare results (Coleman and Moynihan 1996). Victimization surveys have produced impressive results in uncovering the dark figure of crime. However, there are a number of problems associated with it (Coleman and Moynihan 1996).
The history of victimization surveys demonstrates its success in uncovering the dark figure of crime. The British Crime Survey (BCS) is a prime example. Through victim surveys, a disparity was found between the reported and unreported crimes in England and Wales (Coleman and Moynihan 1996). During 1991-1993, the official statistics witnessed a 7% increase. However, this is juxtaposed by the results of the BCS that reported an 18% increase (Coleman and Moynihan 1996). In 2001, the BCS estimated that 56% of the comparable subset was recorded. Therefore, through the BCS, it is evident that victimization surveys are a strong method to uncover the dark figure of crime. In 2006, the Central Statistics Office (CSO), part of the Quarterly National Household Surveys, surveyed 39,000 households in Ireland. The CSO concluded that 4.6% of households had been a victim of crime. Approximately 30% of burglaries, 40% of thefts and 48% of assaults were not reported. This demonstrates the effectiveness of victim surveys. Kinsey, Lea and Young (1997) provide additional reason to why data provided by victimizations studies maybe useful in uncovering the dark figure of crime. They argue that inter-city communities have a high level of discontent and lack of faith in the local police as they have a fear reprisals from criminals(Coleman and Moynihan 1996).Therefore they more willing to respond positively to a victimization survey and thus victimization surveys are effective.
While victimization surveys are an effective method of uncovering the dark figure of crime, there are problems. The major issue is that victimization surveys only measure crimes with identifiable victims. Undiscovered crimes, such as environmental degradation, are impossible to uncover in victim surveys. The surveys also do not cover ‘victimless’ or ‘consensual’ crimes where a complainant is non-existent. These include activities where the main impact is on the perpetrator like illicit drug use and prostitution. It also includes other crimes against the state where there is no direct victim such as trafficking and importation of illegal drugs, sale of pornography, illegal gambling, immigration crime, intellectual property crime, piracy, terrorism and organised crimes.
Sample size can also negatively impact uncovering the dark figure. As crime is a relatively rare event, the sampling size must be sufficiently. This can demonstrated in the 1992 BCS survey where 45% of respondents recalled being victims of crime. Furthermore, the sample must demographically represent the population, which can be difficult due to non-respondents. Mayhew argued that non-respondents include a disproportionately high number of victims. In contrast, Crawford disagrees. He contends that the incentive for victims to participate is substantially higher than non-victims. This means that in order to discover the dark figure of crime, criminologists must rely upon informed speculations gathered from studies of known victims, as it is not clear why there are non-respondents. Furthermore Sparks says female victims of violence tend to refuse to be interviewed more often than male victims (Sparks 1977).
Inaccurate survey responses from victims can have a bearing on the reliability of results. As crime is considered a relative salient event, it was thought individuals would be able to recall incidents of victimization. However, victims memories decayed at a faster rate than criminologist had anticipated with respondents forgetting their victimizations. This is found by an initial pilot study, which outlined that 60% of the worst crimes were reported as occurring in the last three years. According Hindelang this is a far greater number than expected. Recall periods had forward and backward telescoping issues. Forward telescoping is when the victim’s recollection period is brought forward. This contrasts with backward telescoping, which occurs when victimization period is shifted back. Concealment and fabrication is another ptoblem, which compromises the factualness of the victimization survey. Walklate argues that those crimes which are less likely to be reported to the authorities are also unlikely to be recorded by the surveys. This is exemplified in the Merseyside Crime Survey, which failed to record any sexual offences. Very little is know about the degree of fabrications within surveys, but Levine suggests that it is a methodological issue. It is conceivable that respondents fabricate some issues in order to not disappoint the interviewer. Inaccuracies can also be developed as the surveys quite often fail to report on particular groups such as prisoners and children.
During the last twenty years, geospatial analysis has been a method used to uncover the dark figure of crime. The analysis involves plotting crime incidents by location and formally comparing the incidence of events by their spatial distribution to identify hotspots of criminal activity (Attewell 2001). Incidence of crime is plotted on a map, which allows for hotspots of criminal activity to be uncovered. This is either done for individual incidents (point based) or for aggregate data in pre-defined geographical units (area based) (Attewell 2001). The development of geospatial analysis in the fighting of crime occurred in New York City with the development of Compstat. On a weekly basis, the NYPD compile a summary of the week’s crime complaints, arrests and summons activities, as well as a written recapitulation of significant cases. This data is then placed into the city wide database.
Compstat has been successful in reducing the crime rates and uncovering the dark figure of crime (Attewell 2001). Once accurate data has been collected, officers’ can focus their effort on the ‘hotspots’ of crime. It allows strategies to be created and delegated to specific subordinate command personnel. It also allows officer’s to “think outside the box” to ensure that problems are addressed in an optimal fashion (Attewell 2001). Sufficient resources must be used in those particular areas of high crime in order to prevent further crime and uncover undiscovered crime. This may have attributed with a 66% decline in crime since in the inception of Compstat in 1994.
The most significant criticism of geospatial analysis, especially in Compstat, is that it may discourage officers from taking crime reports in order to create a false appearance of a reduction of community problems. According to journalist Radley Balko, "some recent reports from New York City suggest the program needs some tweaking to guard against the twin dangers of unnecessary police harassment and underreporting of serious crimes” (Balko 2010). This is also evident in David Chen’s article in the New York Times who stated, “An anonymous survey of "hundreds of retired high-ranking police officials . . . found that tremendous pressure to reduce crime, year after year, prompted some supervisors and precinct commanders to distort crime statistics” (Chen 2010). In addition, the severity of crimes may be downplayed in order to manipulate the data. The issue was further publicized in 2010 when NYPD officer Adrian Schoolcraft released recordings of his superiors urging him to manipulate data (Long and Hayes 2010).
The prosecution of white collar offenders, especially high-placed managers and directors, is likely to have a salutary effect. Criminologists believe that individuals of high wealth are considered to sufficiently deterred by criminal and regulatory forces as apposed to general street criminals (Marmo, De Lint, Palmer 2011). Therefore, John Braithwaite’s Enforcement Pyramid is often seen as an adequate method to uncover the dark figure of crime and prevent future crimes from occurring (Marmo, De Lint, Palmer 2011). The pyramid utilizes informal and formal approaches the actions ranging from persuasion to criminal penalty and license revocation (Marmo, De Lint, Palmer 2011).
The utilization of both punishment and persuasion is a positive method of uncovering white-collar crimes. According to Ayres and Braithwaite, persuasion should be the strategy of first choice because preserving the perception of fairness is important to nurturing voluntary compliance (Murphy 2004). Sociologists believe that individuals and firms will regard tough enforcement action as more procedurally fair after persuasion has been used. It is also imperative that regulatory forces punish rule breakers, which is only able to occur if regulators actively devote their resources to uncovering hidden crimes and therefore treating them appropriately. Ayres and Braithwaite (1992) argue that the greater the heights of tough enforcement to which an agency can escalate (Braithwaite 1992). The more effective the agency will be at securing compliance and the less likely that it will have to resort to tough enforcement (Braithwaite 1992).
The effectiveness of the Enforcement Pyramid in uncovering hidden crime is often challenged due to the way in which white-collar criminals utilize embedded laws and regulations to escape prosecution (Marmo, De Lint, Palmer 2011). This is particularly the case with limited liability companies, which allows individuals to escape the responsibilities involved in investing (Marmo, De Lint, Palmer 2011). In addition, the concept of capitalism entices companies to cut corners in order to establish higher levels of profits (Marmo, De Lint, Palmer 2011). Quite often government’s will fail to resolve these issues in order to avoid an anti-business image being formed.
The dark figure of can be found through self-reporting surveys, victimization surveys, geospatial analysis and the Enforcement Pyramid. However all these methodologies have problems associated with them and therefore can produce inaccurate results. Therefore despite their success they are unable to uncover all the dark figures of crime.
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