ADR UK Research Fellows: Data First: Cross-justice system

Status: Active

This dataset contains de-identified data on an individual person- and case- level, from the start of criminal prosecutions in the magistrates’ courts and Crown Court, through to periods spent in prison custody or under supervision of the Probation Service. This data is now linkable to information on adults and children involved in family court cases dealing with child arrangements, divorce, or adoption, as well as people (and companies) involved in civil cases, for example, in relation to housing or debt, as claimants or defendants.

The Data First: Cross-Justice System dataset therefore offers a unique opportunity to explore how people experience and interact across different justice jurisdictions, from criminal prosecutions to civil and family court cases. These can provide insights into research questions that have not been possible before, such as to what extent people involved in the criminal justice system are also dealing with cases in relation to children, housing or debt in the civil and family courts.

By studying these patterns, research using the dataset can help to build a picture of how justice system interactions can shape broader social outcomes. These Research Fellows are using the linked criminal justice data in this dataset to explore ethnic inequalities, reoffending and offender rehabilitation. They will access the dataset via the Office for National Statistics (ONS) Secure Research Service.

Learn more about the Research Fellows and their projects below.

 

Dr Kitty Lymperopoulou 

Cumulative disadvantage in the criminal justice system

Kitty is a Senior Research Fellow at the University of Plymouth. Her project aims to generate evidence about how different forms of disadvantage combine and accumulate across different stages of the criminal justice system, and the ways they contribute to ethnic disparities.   

View project details

This project aims to explore the following research questions:

  1. How do individual (e.g. ethnicity gender, and age) and case (e.g. offence type and severity) characteristics intersect to create experiences of cumulative disadvantage within the criminal justice system?  
  2. Do earlier decision points in the criminal justice system, including plea and pre-trial detention, influence and potentially compound disparities at sentencing? 
  3. Do ethnic disparities persist post-sentencing? Are people from ethnic minorities more likely to serve longer sentences in prison and are they more likely to be recalled if they are released on licence compared to their white British counterparts?  
  4. Are cumulative disadvantages more pronounced for ethnic minority groups? What are the direct effects of ethnicity, on imprisonment, time served, and reimprisonment via pretrial detention, not guilty plea, and prior justice involvement?  

The methodology used in this study:  

  • This study will look at how disadvantage accumulates over time, focusing on both individual and combined effects of various factors on outcomes at different stages of the justice process. It will use multilevel modelling to examine decisions such as pre-trial detention (remand), plea proposal (not guilty plea), sentencing (imprisonment), time served in prison, and post-sentencing (re-imprisonment following recall). The models will explore how personal (e.g. ethnicity, gender, age) and case characteristics (e.g. offence severity or prior justice involvement) interact at each stage, showing how these factors may lead to disproportionately poorer outcomes.
  • A life course approach will be used to follow the trajectory of a criminal case, from pre-sentencing to post-sentencing outcomes. Structural equation modelling will be used to assess factors at different stages and identify possible pathways mediating the association between ethnicity and outcomes. The main hypothesis is that individuals from ethnic minority groups are more likely than white British individuals to face cumulative disadvantage through a combination of more punitive outcomes.

Funded value: £158,236 

Project duration: April 2024- March 2026


Dr Markus Gehrsitz

Understanding offender rehabilitation and supervision 

Markus is a Reader in Economics at the University of Strathclyde. His project studies the reoffending behaviour of previously incarcerated offenders and the role of supervision in offender rehabilitation.  

View project details

This project aims to explore the following research questions:

  1. How do reoffending and reconviction rates change over time and by sentence type? 
  2. Which groups of offenders are at high risk of reoffending?
  3. Are license conditions and offender supervision effective in reducing reoffending and reincarceration?  
  4. Do sanctions during probation periods act as a deterrent and thus improve public safety? 
  5. Which individual or contextual factors boost or diminish the effectiveness and deterrent effects of offender supervision? 

The methodology used in this study:  

  • This study draws on detailed offender-level data from magistrates’ and Crown Courts, a prisoner custodial journey dataset,  and probation data. The project combines these data sources to construct offender journeys through the criminal justice system.  
  • Using a descriptive approach, the project will plot average reconviction rates for former prisoners at different time periods after release. This graphical evidence visualises reoffending rates in general, and highlights patterns based on initial sentence, offence type, and socio-economic characteristics.
  • Next, it will estimate the impact of offender supervision by analysing a reform that introduced license conditions and close supervisions. This reform introduced supervisory arrangements only for some offenders - a second group of similar offenders was released unconditionally. Comparing the re-offending rates of these two groups will provide an estimate of the effect of supervision.
  • The study will also focus on how and when reconvictions happen, comparing across offenders with different license requirements, to examine the role of probation violation sanctions (particularly prison recalls).
  • Finally, it will use detailed demographic and geographic data to explore conditions that make supervision and rehabilitation more effective - for instance, areas with low unemployment and crime rates or easy access to public services - and assess whether supervision reduces reoffending, thus improving public safety.

Funded value: £158,381 

Duration: September 2024 – March 2026 

Categories: Research using linked data, ADR UK Research Fellows, ADR England, Office for National Statistics, Crime & justice, Inequality & social inclusion

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