Recidivism Rates Essay

Length: 8 pages Sources: 2 Subject: Criminal Justice Type: Essay Paper: #79290866 Related Topics: Forgery, Arson, Robbery, Parole
Excerpt from Essay :

Recidivism Rate

In the context of criminal justice, recidivism represents a relapse of criminal activity by a person after being convicted of some offense, punished, and corrected (seemingly) (Maltz, 2001). Recidivism emerges from a series of failures, namely, failure to meet the expectations of society or society's failure to support the person; the person's resultant failure to keep away from trouble; the individual's failure to escape capture and conviction, following committing of offense; individual's failure as a correctional-institute inmate to make the most of correctional interventions -- or the institute's failure to provide rehabilitation programs; and the person's additional failures in refraining from criminal activities following release from the institute (Maltz, 2001).

Recidivism Definitions

Recidivism, when taken from a correctional perspective, has a fairly explicit meaning. The term derives from Latin recidere, which implies 'falling back' (Maltz, 2001). Recidivists are individuals who are not rehabilitated following release from confinement (due to committing an offense). Instead, they fall back, i.e. revert, to their former behavior, committing further offenses. While the above conceptual definition for recidivism seems rather straightforward, a more operational one, which allows measurement, is somewhat complex (Maltz, 2001).

The data on which recidivism measurement bases itself is seldom comprehensive, and even in the event that complete information can be obtained, data analysis methods are inconsistent: substantial variation exists in recidivism measurement techniques (National Advisory Commission, 1973: 512).

2.1. Complete information

Firstly, let us consider recidivism measurement when comprehensive data is available. Complete information means that all offenses the individual in question has committed (whether or not arrested for all of them) are known to evaluators. This improbable condition also poses a challenge- the term 'crime' covers many things (Maltz, 2001).

A child-molesting individual, for instance, may be detained, found guilty, and sentenced to some correctional intervention designed exclusively for treating such offenders. He may, after release, be actually corrected, and may stop molesting kids (Maltz, 2001). However, if he turns to other forms of crime, say forgery or armed robbery, can he be considered a recidivist? If taken from one view, he may be labeled a recidivist as, after release, he engaged in criminal behavior. But, this crime is completely different; while the original offense has been curbed, he has resorted to some other harmful behavior. Must such an individual, who moves from one type of crime to another, entirely different one, be considered recidivist (Maltz, 2001)?

We can, of course, label an individual as recidivist if he/she only repeats the same type of offense for which he/she was found guilty originally (Maltz, 2001). This definition, however, suggests that offenders specialize in one crime -- a contradiction to the evidence available and emerging (Petersilia, 1980; Chaiken & Chaiken, 1982; Goldstein, 1982; Miller & Dinitz, 1982). Moreover, a separate recidivism category for individual offenses will correspondingly lead to less information on individual categories (Maltz, 2001). The four categories of crime - personal, white-collar, property, and public-order- may be considered. However, no well-defined lines divide these categories, as many crimes (for instance arson or robbery) may overlap, supersede or magnify the acts (Maltz, 2001).

In order to understand the full impact of 'return to crime' and the time in which the probability is highest, one needs to categorize the re-imprisoned convicts, the most probable reason and time in which such recurrence is seen and the gender influence of the phenomenon.

Four Measures of Recidivism

Langan and Levin (2002) performed analysis on data gathered from Bureau of Justice Statistics about female inmates released from state prison in 1994. In their research, they focused on four measures of recidivism namely re-arrest; reconviction; and resentence (with & without new sentence) (Deschenes, Owen, Crow, 2007). The sample size of 272,111, comprising both male and female prisoners, was used for research. Rigorous analysis of this sample showed that, within 3 years of prisoner's release (Deschenes, Owen, Crow, 2007):

67.5% were rearrested

46.9% were reconvicted

25.4% were resentenced

51.8% were sent back to prison due to new crime or technical violation.

These statistics of combined data set (both male and female) showed that the crimes which had highest re-arrest rates were (Deschenes, Owen, Crow, 2007):

Robbery (70.2%);

Burglary (74%);

Larcenists (74.6%);

Motor vehicle theft (78.8%);

Possession/selling stolen property (77.4%);

Charges due to some form of weapons (70.2%).

While lowest re-arrest rates were of the prisoners which...


Figure-1 shows that total percentage of females who were released in 1994 and were rearrested, reconvicted or returned to prison over a time span of 3 years (Deschenes, Owen, Crow, 2007). This study showed that, in an overall duration of 3 years, around 44% of all the females prisoners released in 1994 were reconvicted (Deschenes, Owen, Crow, 2007). Among all the female offenders rearrested in 3-year follow-up, 23.3% were rearrested in first 6 months and 34.5% in first year (Deschenes, Owen, Crow, 2007). This rate increased around 15% for second and third year. This shows that the highest risk time for re-arrest is year 1. Research on this sample showed that percentage of female recidivated was much less than male in four measures namely re-arrest, reconviction, resentence to prison and return to prison (Deschenes, Owen, Crow, 2007).

Figure 1. Time to recidivism for female prisoners for specified time intervals (Deschenes, Owen, Crow, 2007)

The inferences drawn from the figures above may give us an insight into the likelihood of the relapse to crime area and the most probable duration of susceptibility. Such an understanding would help create an intervention design, capability of anticipation and most chances of avoiding recidivism.

Correctional intervention's nature, to a considerable extent, governs recidivism's definition (Maltz, 2001). Revisiting the previous example of a child molester, the offender would be labeled 'recidivist' if the intervention under evaluation was, for instance, a study into the success of different bail caseloads, and not if it was intended to modify child molesters' behavior. Therefore, while defining recidivism, both program type and crime type have to be taken into account (Maltz, 2001).

2.2. Problems with incomplete criminal justice data

The usual assumption is that comprehensive information is available, regarding a person's relation to criminal justice; but, some information undoubtedly lacks. These dealings are reported by several different agencies; however, most states don't have only one, single criminal-data repository. This can partially be attributed to the involvement of numerous government levels and jurisdictions in a state's crime justice system (Maltz, 2001).

2.2.1. Enforcement Data

Enforcement agencies in a state can be found at every governmental level: local police at the municipal level, sheriff at the county level, and investigation bureaus and highway patrol's at state level. Centralized criminal and detention data reporting has started more than 50 years earlier, with expansion and improvements made over time (Maltz, 1977). Presently, it includes virtually every enforcement agency.

2.2.2. Prosecutorial and Court Data

Prosecutors' offices and criminal courts are essentially county-level agencies, though with some exceptions. They don't have any single data repository like the National Crime Information Center (NCIC) felony arrests program. Statistical Analysis Centers (SACs) are given the responsibility of amassing all data on criminal justice, however, their trial and prosecution data collection hasn't proceeded at the same quick rate at which data has been collected from enforcement bureaus (Maltz, 2001). Nevertheless, many larger prosecutorial offices are supported by the Department of Justice for setting up PROMIS (Prosecutor's Management Information System) (National Institute of Justice, 1977) or other similar IT-based systems for storing and retrieving information. When compared to other jurisdictions, these offices ought to provide more complete information (Maltz, 2001).

2.2.3. Correctional Data

Correctional information can be procured from county jails as well as state level prisons and halfway houses. However, only a few states currently incorporate information from jails into state correctional statistics. Again, here, developments are likely (Maltz, 2001). States have been funded by the Department of Justice to develop Offender-Based State Correctional Information Systems (or, OBSCIS) for compiling statewide correctional information from all levels. However, at present, only some states have the ability to keep a track on individuals, sentenced to jail, on a routine basis, with any guarantee of comprehensiveness (Maltz, 2001).

2.2.4. State-Specific Data

Even when complete statewide information is available for the purpose of analysis, it is still incomplete in case of offenders rearrested, put on trial, and/or condemned in some other state. Rates of recidivism can depend on geography if data only pertaining to the state carrying out the study is utilized (this is always the case when the recidivism marker is "return to imprisonment") (Maltz, 2001).

0. Data Problems In Controlling For Arrest Quality

Arrests need not be the only indicators of recidivism. One may try to decrease Type I errors (which arise from incorrect arrests) by examining subsequent criminal justice dealings following the arrest. If one describes recidivism as, arrest and subsequent affirmative…

Sources Used in Documents:


Chaiken, Marcia R. (1982). The Chicago Area Project and the Enigma of Delinquency Prevention: Some Exploratory Findings. Draft report. The Rand Corporation. Santa Monica, California.

D.A. Andrew, James Bonta and J. Stephen Wormith. (2006). The Recent Past and Near Future of Risk and/or Need Assessment 52(1) crime and Delinquency 7, 11.

Deschenes, Elizabeth; Owen, Barbara; Crow, Jason. (2007). Recidivism among Female Prisoners: Secondary Analysis of the 1994 BJS Recidivism Data Set.

Goldstein, Paul J. (1982). "Habitual Criminal Activity and Patterns of Drug Use."Paper presented at the 34th Annual Meeting of the American Society of Criminology, Toronto.

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