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RECENT SOCIAL STATISTICS
Research Paper: An Analysis of Repeat Imprisonment Trends in Australia using Prisoner Census Data from 1994 to 2007, Aug 2010
Research Paper: An Analysis of Repeat Imprisonment Trends in Australia using Prisoner Census Data from 1994 to 2007, Aug 2010 (cat. no. 1351.0.55.031) was released on 30 August 2010.
Reducing the number of prisoners who are repeatedly imprisoned is one of the goals of any correctional system. However, while a period of imprisonment may deter some people from re-offending, in others it may foster further criminal behaviour. This paper presents the results of a study based on a longitudinal dataset constructed from 14 successive Prisoner Censuses between 1994 and 2007 to follow, over time, two cohorts of people who were 'released' from prison (where 'release' is a proxy measure derived from the absence of a prisoner's record in a subsequent Prisoner Census). This paper expands on an earlier study by the Australian Bureau of Statistics by using logistic regression models to examine the factors associated with repeat imprisonment and assess whether or not the propensity for reimprisonment has increased over time. This paper also examines trends in criminal career development using descriptive methods, looking at patterns of specialisation, and of movements from one type of offence to another.
The study finds that reimprisonment is strongly associated with being young, being Indigenous, or having been previously imprisoned (that is, being a prisoner who had already served time in prison). In all jurisdictions except Queensland, the rate of reimprisonment in recent years was higher than in the mid-1990s.
Understanding Data Quality - Helping You Make Better Decisions
The National Statistical Service (NSS), a community of government agencies led by the Australian Bureau of Statistics (ABS), encourages the use of statistical frameworks, principles and resources, which can help data providers and users to realise the benefits of good data management through its DATAfitness program. DATAfitness encourages the use of statistical frameworks, principles and resources which can help data providers and users to realise the benefits of good data management.
Over the past few years, the call has been put out for public policies to be informed by good evidence. Statistical information is now answering that call. Statistical information has long been recognised as being good evidence, which places it at the heart of evidence-based policy.
As part of its DATAfitness program, the NSS has developed Data Quality Online (DQO), an easy-to-use online support system for data collectors, providers and users.
DQO is the first assistant of its kind in the world and provides clear and simple support to those involved in understanding data, and using it to make decisions.
DQO helps users to draft data quality statements, and can now be used to compile general purpose quality statements for a variety of data sets (e.g. administrative data, survey data) whilst continuing to support users to draft tailored, indicator-driven quality statements for the Council of Australian Governments (COAG) performance reporting.
The NSS officially launched the DQO in August 2010, in conjunction with the ABS. DQO is based on the nationally recognised ABS Data Quality Framework, which provides a consistent standard for describing the quality of data.
For more information on DQO and DATAfitness, either visit the NSS website, visit www.nss.gov.au/DataQuality or email <firstname.lastname@example.org>.