Offender/Offender Manager Relationships - image of paper people holding hands

Positive Relationships in Offender Management

We are delighted to welcome Prof Darrick Jolliffe, Professor of Criminology at the University of Greenwich as a guest blogger. Prof Jolliffe has worked with GtD on our offender management work and here he discusses the role of relationships in that work.

Positive relationships have the power to change us. This is not just the catchy slogan of the International Coaching Federation, but something that resonates with all of us.  The constructive relationships that we have, or have had with our parents, teachers, friends and colleagues not only define our interactions with them, but our interactions with all others, while defining who we see ourselves to be. Translating this ‘common sense fact’ into the management of those who have committed offences has an extensive history, and some would argue is the bedrock on which the probation service was founded. However, like many things that are common sense, such as we only use 10% of our brains, and carrots provide good eyesight, the suggestion that if ‘offenders’ have a positive relationship with those providing their supervision they will have more positive outcomes, the actual relationship might actually be a bit more complicated. 

I was invited by Get the Data Director Jack Catell to speak their event, Transforming Rehabilitation – Learning from the PbR results, about my experience of attempting to capture the evidence that positive relationships between offenders and offender managers results in definable benefits. This was something that I first worked on over a decade ago, having first been commissioned by the Home Office to develop an Offender Management Feedback Questionnaire, which was a series of questions that asked offenders about their engagement with their named offender manager. I was subsequently commissioned to work on revised versions, and also helped develop a mirror version which asked about how offender managers viewed the relationship that offenders had with probation.

Some findings fit with expectation, for example, female offenders consistently had more positive relationships with offender managers than males, and the longer that an offender had spent on probation the more they felt they had developed positive relationships and acquired useful skills.  However, some findings were very far from expected, for example, those who reported greater engagement with probation were not less likely to reoffend, and even more concerning, or at least confusing, those who reported greater acquisition of skills while on probation were significantly more likely to reoffend.

How do we reconcile these findings with what we know about the power of positive relationships?  Well, I don’t think there is an easy answer here.  I suspect that positive relationships with offender managers are important for offenders, but they may not be important enough to have an impact on a blunt measure such as reoffending over and above the other issues that many of these people are facing in their lives.  We put the finding, that those who reported greater acquisition of skills were more likely to reoffend, down to offender’s overly optimistic view of how easy it would be to continue to stay crime free.  When we looked more closely at the scores of the questionnaires, it was the items which referred specifically to acquiring skills which would reduce later reoffending that those who reoffended tended to endorse more strongly – almost as though they were trying to convince themselves of their ability to stay on the straight and narrow.

Reflecting back on this work, I am really proud of what we did achieve, despite not getting the common sense result we all expected.  I think there would be a lot of mileage in revisiting the offender/offender manager relationship as a potential desistence tool, and if I was going to do this again I would be looking to measure changes in relationships (so administering items more than once) and see how these changes might relate to more short-term outcomes (e.g., offender’s motivation), as well as longer-term outcomes (e.g., reconviction). 

Tape measure

The Data Revolution Will be Measured

“Innovation distinguishes between a leader and follower”, so said the late Steve Jobs. His words came to mind as I prepared to present to Gideon’s Promise’s Summer Session last month.  Gideon’s Promise asserts that a revolution is needed in how the criminal justice system treats indigent defendants. And as befits an organization that sees itself in the vanguard of that revolution, Gideon’s Promise has a radical vision of the impact of its work. For them it is less about increased efficiencies in case management or the effectiveness of sentencing. Rather it is about changing how the criminal justice system and society-at-large regard poor people caught up in the system’s net. To bring this about, Gideon’s Promise provides a community of public defenders who put their clients at the center of their practice. In doing so, they insure their clients’ stories are told and their humanity is revealed to the court. Or in the words of one member of the movement, “we need to think of this person as a human being and not simply a number in an orange jump suit”.

So how to measure a revolution? Over the past 18-months Gideon’s Promise has led an expert collaboration that has included Get the Data and another Atlanta-based organization, Techbridge. Together we have delivered a ground-breaking program of work that has produced innovative measures of both the public defenders’ values and their clients’ experiences of the client-centered approach. In developing those measures, GtD grounded our work on understanding the impacts that Gideon’s Promise strives to achieve and the resources at its disposal. Having articulated this theory of change, we were able to design the appropriate measurement instruments and subject them to cognitive, reliability and validity testing with samples of Gideon-trained public defenders and their clients. The next step was to collaborate with Techbridge to deliver a technological solution that will allow the instruments to be completed on-line and held in a database. This technology will be essential as the measurement work is rolled out across Gideon-affiliated offices. Finally, we designed a “Digital Dashboard” that Techbridge attached to the database and to report data by offices, public defenders and their clients.

“Innovative” is a word that can be overused or cliched, but in this case the program of work undertaken by the collaboration has truly been new and refreshing. Moreover, it provides the means by which Gideon’s Promise can measure its bold and revolutionary vision. The next steps will be to roll-out this program of work and then move to designing measures of the impact on the criminal justice system and ultimately society as a whole.

The revolution is coming, and the revolution will be measured.

Alan Mackie presenting about Data Driven Policy Development

Using Data to Shed the Cloak of Invisibility

Since time immemorial we have been fascinated by the power of invisibility. Plato used the “Ring of Gyges” to wrestle with the ethical and moral dilemmas it poses. Just think of H.G. Wells’ “Invisible Man”, Tolkien’s One-Ring, or Harry Potter’s Cloak of Invisibility.  Does invisibility free us from moral obligations, and if we possessed this power would we become corrupted or would we enjoy secretly righting wrongs?

Outside the realms of science fiction, “invisibility” is often an every-day problem for our fellow citizens. I am thinking of those whose problems just don’t make the 24/7 news cycle: the homeless woman sleeping in a shop doorway, the ex-offender walking through the prison gate with nowhere to go, the young man who has dropped out of school with no grades. Often we simply ignore those populations, or – to borrow from Harry Potter – throw the “cloak of invisibility” around them. To be out of sight is often to be out of mind.

The ‘invisibility’ of those with developmental disabilities was thrown into sharp relief during my recent visit to the U.S. Virgin Islands. I was invited by the VI Developmental Disabilities Council to present on ‘Data Driven Policy Development’. My audience was policy makers, including those standing for elected office. If I had any doubts about the relevance of my presentation, the audience quickly rose to the occasion. “How could the needs of those with disabilities be met in the absence of data?”, they demanded. Without data, this population was “invisible”, their needs unknown to those in charge of policy. Without data, those who advocated for better services were hampered in their arguments. Without data, practitioners lacked the evidence to seek funding for new services.

The US Virgin Islands are still recovering from the two hurricanes that devasted the territory last year. As they rebuild the fabric of their communities, it was clear to me that data were not a luxury or a ‘nice-to-have”. Rather, my audience recognized the value of data in throwing light on a population that had often been marginalized prior to the hurricanes, and whose needs had since become more acute. While there is much more work to be done in defining data and setting up systems to collect and analyze data, I suggest that their demand for data was a good one and a great call to action.

It might be fun to speculate what we would do if we had our own cloak of invisibility. In the real world, however, we need data to shine a light on social problems. Or to borrow again from Harry Potter, “Lumus Maxima!”

 

Make Social Impact Your Goal! - GtD and Street Soccer Academy

Make Social Impact Your Goal!

I am delighted to be working again with Street Soccer Academy (SSA) to put evidence of their social impact at the heart of their work with ex-offenders. This important work has been made possible by a grant from the Access Impact Foundation whose mission is to make charities and social enterprises more financially resilient and self-reliant, so that they can sustain or increase their impact. Without the generous funding from the Access Impact Foundation we would not able to provide Street Soccer Academy with our powerful data analysis.

Street Soccer Academy is a great client to work with. They use professionally organised sports-based programmes in the rehabilitation and reintegration of people from some of the nation’s hardest to reach groups, including ex-offenders. Our task is to prove that SSA’s pro-social models are affecting the attitudes and thinking of the men and women with whom they work, with particular emphasis on their relationships and roles in society.

In the coming months we will be using our rigorous social impact analytics to contribute to the knowledge of what makes ex-offenders desist from crime. Our previous evaluation of the academy’s prison to community service, produced evidence of SSA’s excellent engagement of ex-offenders into their programme. With the foundation’s funding we will build on that by using our advanced statistical analysis to identify who benefits from the programme, how and in what circumstances. These analyses will assist the academy to identify the most effective practice and allow it to develop its professional programmes. To ensure that it has the right information at the right time we will be building a dashboard to communicate this data to those delivering the programme, their managers and the funder.

Not only will this improve their practice, but it has important implications for government’s Transforming Rehabilitation agenda. That agenda depends on organisations like SSA being commissioned to deliver services through the private community rehabilitation companies. However, the participation of such organisations has been low as they struggle to demonstrate their impact on reoffending pathways and desistance from crime. Access Impact is helping to overcome those obstacles and by funding our work, will enable SSA to attract further funding and make the systemic changes that are essential to support men and women to desist from crime.

To find out more about our analytics services and how we can help your organisation demonstrate your impact definitively, contact us on 020 3371 8950 or email jack.cattell@getthedata.co.uk

Get the Data and Gideon’s Promise Team Up for Innovative Metrics

Over the past year, GtD has been proud to be work with Gideon’s Promise to develop measures of culture change that will transform the American criminal justice system. We are delighted to welcome Ilham Askia, Executive Director of Gideon’s Promise to guest blog about our partnership.

Ilham N. Askia
Executive Director
Gideon’s Promise

Gideon’s Promise is a U.S.-based, non-profit whose mission is to transform the criminal justice system by building a movement of public defenders who provide equal justice for marginalized communities. Gideon’s values-based approach uniquely trains public defenders to use a “client-first” method to defense practice. The impact that this approach can have on culture change in public defense will ultimately transform an entire criminal justice system. Since January 2017 we have been working with GtD to create an innovative approach to measure the effects of culture change in public defense systems.

While most experts focus on case outcomes and court processing to determine the effectiveness of a public defense system, Get the Data and Gideon’s Promise have designed a way to measure the effects of a values-based approach to training and supporting public defenders. Gideon’s Promise believes that, in order to have equity in the criminal justice system, the lawyers who represent the accused must be excellent in their profession but also care about the dignity of their clients. For over 80% of the people who are charged with a criminal offense, a public defender has the enormous responsibility to not only defend a charge but also illustrate the humanity of a defendant. If administrators of justice could view the accused more humanely, then the treatment of people warehoused in jails, prisons and courtrooms would be different. Because the criminal justice system does not effectively function to rehabilitate offenders, the dignity of the human spirit is stripped away as soon as an individual is accused of an offense. The culture of the system must change from viewing people as case numbers and files and more like human beings with lives that have value. Public defenders tell the stories of those who are deemed unworthy of support. Public defenders remind the system about the value of human lives.

Get the Data has designed metrics to discern whether the culture of an office, the confidence of a public defender, and environment play into how defendants feel about their representation. These metrics also measure whether the attitudes of Gideon’s Promise public defenders affect the public defender offices where they work, the courtrooms where they practice and the relationships they have with their clients. While no one else is measuring the impact of culture change in the criminal justice system, Get the Data and Gideon’s Promise are on the verge of a transformative approach to repairing a broken criminal justice system by using public defenders as anchors to reform and explaining their importance through quantitative data that measure qualitative relationships.

Although Gideon’s Promise is a national organization, it primarily focuses its work in the southeast region of the U.S. where the highest concentration of inequity exists. There are six public defender sites piloting these metrics. The Defender Value Spectrum Survey (DVSS) and the Client Evaluation Survey (CES) are being completed by a sample of Gideon’s Promise influenced public defender offices and clients who received services from those offices. Our goal is to conclude whether a values-based trained attorney positively correlates with how people view public defenders, clients and how both are treated in the court system. Are there sets of core values to public defense training and mentoring that systemically changes the culture? Is Gideon’s Promise’s curriculum aligning with the goal to transform the culture of public defense? Does a caring lawyer matter? These are all questions this study will answer. Our hope is that we can replicate this evaluative process across the country to not only inform Gideon’s Promise’s programming but also encourage public defense systems to adopt our model while providing data that our culture change model works. Caring, competent and committed lawyers are essential to true criminal justice reform.

This partnership is crucial to capturing a values-based approach to criminal justice reform. Gideon’s Promise is truly grateful to be working with Get the Data on this ground-breaking work.

Join our LinkedIn Transforming Rehabilitation Group

Join Our Transforming Rehabilitation LinkedIn Group

We have created a LinkedIn group dedicated to the topic of Transforming Rehabilitation. It is a forum for discussion, for individuals who work or have an interest in, the fields of probation, offender rehabilitation and Transforming Rehabilitation.

Our idea to set up the Transforming Rehabilitation LinkedIn group follows our recent Transforming Rehabilitation: Learning from the PbR results event, which was attended by professionals working across all aspects of the probation service. At the event, attendees were able to network, and share their experiences and learnings, which was highly beneficial. We wanted the discussions and new connections made, to continue beyond the event and the group is the ideal way to help facilitate this. Everyone working in this sector has valuable insights and their contributions to shared learning will ultimately help us all to improve the outcomes for those entering the justice system.

The first discussion topic is The importance of the worker-service user relationship

Establishing a good relationship between the offender managers and their clients/service users is an important part of quality offender management. Putting this into practice might be more difficult. Can you share some of your experiences of good practice in involving offenders in their sentencing planning, and what obstacles were in your way and how they were overcome?

Please do take a look at the conversation and comment if this is a topic on which you’re able to share some knowledge. We will regularly post questions, but also invite members to post your own questions for discussion. You can request to join via this link – Transforming Rehabilitation

Magnifying glass over the word analyse to illustrate analysis of TR PbR Figures

TR PbR Figures – Context and Drivers

This blog post summaries a presentation I gave at our recent event: Transforming Rehabilitation: Learning from the PbR results.

 

Overall results  

In this blog, I will discuss the data I presented at our recent event, ‘Transforming Rehabilitation: Learning from the PbR Results’. The event was held shortly after the publication of the first reoffending figures which showed that reoffending in the first cohort had been reduced by 1.9%. My colleague Jack Cattell has already discussed these figures in an excellent blog, so this blog is about the how external drivers across the criminal justice system might be affecting these results.  

By CRC? – PbR Figures, who is in control of reoffending? 

In order to make conclusions from these results, one must be aware that there are many factors that can influence reoffending. When faced with (improved or reduced) performance results – it’s too easy to fall into the trap of thinking that the reasons for this were outside of your control, or that the results were dominated by one particular driver.  

In understanding the reoffending rates by Community Rehabilitation Companies (CRCs), there are many possible drivers across the CJS, and they can be complex to understand. So, could the CRCs have achieved the difference in performance we have seen under TR? Internal factors such as CRC procedures and workflows, and offender profiles will have an effect.  But so too will a myriad of external influences from other agencies of the CJS, for example police positive outcome rates, court conviction rates and timeliness of police & court procedures. Since these factors are outside a CRC’s control, I wanted to investigate and determine whether any might have had an effecting change in the reported reoffending rates.  

National context 

Chart showing - No. of offences thousands

First off, it is important to bear in mind the national context for the period from baseline to first cohort results, which was a time when the total estimated crime fell and police recorded crime remained constant.

 Chart showing proportional change from 2011

Further, positive outcome rates, specifically charges and cautions had been reduced – in general police arrest rates were down and police had been using other disposals (such as community resolutions) to reduce the number of people – particularly young people – in custody.

 

Chart showing days from offence to completion

And individuals were being processed more quickly during the baseline: on average court processes are now taking 10-15 days longer.

Give this context, the national reoffending rate was reduced by 1.8%. That’s a surprisingly resistant figure, given the changes in context nationally. Large changes in this binary rate will not be seen regardless of policy or systematic change in CRCs.

Chart showing reoffending rate

(Of course, the full picture of the reoffending stats has the rate down, but the frequency up – suggesting a shrinking group of more prolific reoffenders. But that is for another post).

Differences in CRCs?

I will now look at these potential drivers of reoffending rates at the CRC level and determine if contexts really were different or helped to drive different performance. To highlight any of these potential differences, I will look at two CRCs who were at opposite ends of the reoffending rate changes.

What is surprising, is that there are no large, obvious differences between those two CRCs when comparing police outcome rates, court effectiveness and court timeliness measures. For example, the police positive outcome rates were reasonably different at the start of the period, but by the end of 2015 had converged to be broadly similar – the best performing CRC had reduced reoffending while police positive outcomes fell by a significant amount.

Chart showing positive outcome rate

Similarly, the lowest performing CRC had raised rates against the baseline despite court timeliness both increasing, and being higher than other CRCs.

So What?

We’ve seen that reoffending rates are complex measures dependent on many factors, from individual, to regional to national level, and the interaction between them. The rates don’t change very much, even though the contexts can differ wildly.

Even comparing the CRCs at either end of performance spectrum there were not huge differences in the police and court factors. This can be seen in different results for CRCs operating in widely similar contexts.

So, my advice is this: don’t fall into the trap of feeling the results are not within your ability to affect. Understanding the wider picture is helpful to contextualise local results. In the following blogs, my colleagues will be focusing on what is in your control, and my colleagues will be identifying what works and using that to inform good practice.

Get involved in the conversation by joining our LinkedIn group.

TR: PbR results - speakers who presented to Community Rehabilitation Companies and other justice sector employees

Community Rehabilitation Companies: PbR Results Event

Transforming Rehabilitation is the UK government’s programme of outsourcing probation services to new community rehabilitation companies. In a radical move, the government is now paying these new companies by the reduction in reoffending results they achieve. GtD is at the forefront of this by providing our cutting-edge social impact analytics to Sodexo Justice Services who manage a number of these new companies.

The first PbR figures were published last month and GtD has been active in informing the debate on their significance. As part of this debate, we recently hosted a sell-out event for senior management and practitioners working in community rehabilitation companies and the justice sector.

An expert panel comprising Prof. Darrick Jolliffe of Greenwich University (above left), Dr Sam King of Leicester University (above right) and GtD’s own Jay Hughes (above centre left), considered the initial findings and what to do next, with Jack Cattell (above centre right) setting out a new vision of how predictive analyses can be used by practitioners to improve performance.

Prof. Darrick Jolliffe – University of Greenwich

If you were unable to attend but would like to learn more about how GtD could support you in evaluating your social impact outcomes or for a free predictive analytic roadmap for your CRC, contact Jack Cattell  The event presentations can also be viewed via the link below:

Transforming Rehabilitation – Learning from the PbR results presentations

Dr Sam King – University of Leicester

 

Jack Cattell – GtD

 

We’ve also set up a LinkedIn group as a forum for shared learning and discussion, for individuals who work or have an interest in, the fields of probation, offender rehabilitation and Transforming Rehabilitation. Click here to request to join – Transforming Rehabilitation

Image to illustrate no data can mean no voice and no idea

No Data? No Voice, No Idea – The Importance of Data

The collection and analysis of data must never be allowed to fall by the wayside – it’s a founding stone, not a ‘nice to have’.

Of course, I would say that, wouldn’t I? But here are six concrete reasons why data is important, drawing on Get the Data’s recent work with the Advice Services Alliance (ASA) as a case study.

  1. Data Is the Great Persuader

There is no more powerful tool for influencing stakeholders than data, as I explained in more detail in this recent blog post on using data to influence stakeholders.

ASA works with its members – various associations who provide advice services – to capture and analyse data from the front-line. This gives weight to conversations with all of those who have an interest in ASA’s direction of travel, reassuring them that strategic decisions are being made in response to changing needs, and reinforcing the professionalism that underlies the work they and their partners do.

 

  1. Data Means Funding

In particular, data is invaluable in drawing in new sources of funding, and persuading potential funding providers. Faced with a choice of projects or programmes in which they might invest, with ever-tighter budgets, funding bodies will regard convincing data as a good reason to choose your work over others. ASA will use data to add weight to its funding applications for this reason.

 

  1. Data Gives You the Power to Lead the Debate

ASA seeks to lead thought, representing its members in national discussions by highlighting issues affecting the people who use advice services. The body of data and analysis to which ASA will refer confers authority and allows the organisation to direct the debate and steer collective thinking around youth issues.

 

  1. Data Defines Good (and Bad) Practice

Using data provided by its members ASA will be able to identify areas for improvement in front line practice and also to pinpoint what is working especially well so that good practice can be shared across the community. It informs training programmes, service improvements and helps determine how resources should be employed for maximum impact.

 

  1. Better data and measurement development 

Good data leads to better data. Use of data means we learn its limitations and how to outcome those. We also learn how to measure the right outcomes, better; particularly in how to measure informal outcomes along said formal attainment.

 

  1. Data Is Cheaper and Easier Than Ever

Cloud-based databases are cheap and easy to implement compared to the cumbersome systems of the past. They make it easier for people to enter data and share it. So there’s really no excuse for failing to collect and analyse data in this day and age.

If you would like to find out more about our cutting-edge approach to data capture and analysis please get in touch.

Scales of Justice representing Transforming Rehabilitation

Transforming Rehabilitation: Payment by Results Figures

Last week saw the release of the Transforming Rehabilitation (TR) Payment by Results figures for the October to December 2015 cohort.

The overall result was encouraging, and defy the view that Transforming Rehabilitation’s radical changes to probation, and the ensuing problems, would result in increased reoffending – though it is very important that I point out that this is just the first set of results of many and overall judgement should be reserved for at least a year. The reoffending rate for all CRCs was 45.6% compared to a 2011 baseline rate of 47.5%. I had to make some (conservative) assumptions to estimate the baseline rate but I think it is also safe to say that the difference was statistically significant, suggesting reoffending rates have reduced under TR. Please see the the note at the end of this blog to understand better how I completed the analysis.

 

Transforming Rehabilitation – CRC Performance

The chart below describes each CRC’s reoffending rate in relation to the baseline 2011 rate. The grey line represents the range of reoffending rates that would indicate no change from 2011 (the baseline confidence interval). If the CRC’s rate is outside this range, we are confident in statistically terms to state that the CRC’s performance was either better or worse than the reoffending rate achieved in 2011. The green bars represent the reoffending rates of CRCs that outperformed 2011, the orange bars represent those that performed the same as 2011 and the red bars present those that performed worse than 2011.

Chart to show CRC Performance

Source: Ministry of Justice Final Proven Reoffending Rates TR (Oct to Dec 2015 cohort).

Thirteen of the CRCs beat the baseline rate. The best performing CRC was Cumbria and Lancashire, which beat the baseline rate by 8.2% (49.9% to 41.7%). The nest best was Hampshire and the Isle of Wight which beat the baseline by 5.4% and the third best was Northumbria with a better rate by 4.3%. Two of the CRCs performed worse than the 2011 baseline. Warwickshire and West Mercia recorded a reoffending rate 3% worse than the baseline rate, and South Yorkshire’s rate was 2.8% worse. With most CRCs, however, outperforming the reoffending rate form 2011, the figures are a promising set of results.

 

Transforming Rehabilitation – Comparing CRC performance

Now that the baseline rates have been published, we can better understand how well each area was performing in 2011 and whether a CRC is now being asked to better good or bad performance achieved in that year. The chart below describes the difference between the actual baseline rate and the 2011 baseline’s OGRS score (in other words their expected rate of reoffending). A negative result in the chart means the area performed better in 2011 than the OGRS score expected.

Chart showing the difference between a CRC's actual baseline rate and the 2011 baseline’s OGRS score

Source: Ministry of Justice Final Proven Reoffending Rates TR (Oct to Dec 2015 cohort).

The charts highlights that six of the CRCs are being asked to beat better than expected performance in 2011 (in other words to be better than good). Whereas other CRCs, notably London and Wales, are being asked to outperform potentially poor performance in 2011. It it interesting that South Yorkshire and, Warwickshire & West Mercia – the two areas that recorded poor performance for TR – are being asked to beat good performance from 2011. Merseyside and Cheshire & Greater Manchester, however, are equally being asked to beat good performance from 2011 and were able to do so for the October to December 2015 cohort. The OGRS score does not allow for area effects, which will exist and could explain the differences between the OGRS score and the baseline rate. It not possible now to conclude whether payment by results will be easier in some areas than others, but, going forward, I will monitor the impact of whether a CRC is being asked to perform better than good or poor performance from 2011 on their ability to achieve payment by results bonuses.

 

Notes on analysis

The latest Ministry of Justice bulletin released more data than was previously available and I was able to complete a statistical analysis of the impact of TR. This could only be completed with making conservative assumptions that would make finding a statistically significant result less likely. The following actions were taken:

  • I assumed the spread of offenders across CRCs in 2011 was exactly the same as it was in the October to December 2015 cohort. This would not be the case but any analysis would want to weight the two samples so they represented each other so the impact of this assumption is minimal.
  • The 2011 sample size was assumed to be the same as that of the October to December 2015 cohort. The 2011 sample will be considerably bigger, so this assumption meant the standard error used for the analysis was larger than it should be.
  • A t-test with unequal variances assumed was used to test the difference between the cohort’s and the baseline’s reoffending rate. The t statistic result was 4.6.

Blog originally guest posted on http://www.russellwebster.com 31st October 2017 with additional commentary from Russell Webster.