Against socioeconomic marginality as a risk factor – 2

risk (flickr birdmanphotos)

In the previous blog post I discussed several arguments put forward by legal scholar Sonja Starr against including socioeconomic factors such as unemployment, low or lack of education, and homelessness in risk assessment instruments used for informing sentencing decisions.

Here is another argument, put forward by legal scholar Michael Tonry in an article titled ‘Legal and Ethical Issues in the Prediction of Recidivism’:

Tonry reiterates widely supported normative and ethical rules such as ‘don’t treat people differently based on the basis of social class’, that are ‘largely incompatible’ with sorting people into risk categories. Tonry describes how, in the US, in the 1970s federal parole guidelines initially allowed variables such as employment, education, residential status and family characteristics, but that these factors were gradually abandoned because ‘they are heavily correlated with race’. The 1991 parole guidelines do not include education, employment or family characteristics.

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Against socioeconomic marginality as a risk factor

risk bus juliefaith flickr

I have written several times about risk assessment of individual defendants and offenders and the role of socioeconomic factors such as employment, educational level, income, financial situation and housing. Risk assessment is used by criminal justice agencies – in the US, UK, Canada and the Netherlands, as well as other countries – to inform decisions about bail, pre-trial detention, sentencing, probation, parole, treatment, and/or supervision.

For example, a widely used tool called LSI-R and a tool that is used in New York State called COMPAS take into account the following individual factors (mentioned in Starr 2014, see below):

  • Performance at work
  • Housing stability
  • Neighbourhood crime rates
  • Dependence on social assistance
  • High school grades
  • Chances of finding work above minimum wage


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Are algorithms class-blind?

Toledo 65 algorithm (jmjesus Flickr)

In an earlier post I wrote about a supposedly new solution to the injustice of the American bail system: risk assessment. To briefly summarize: many people in the US are in jail because they can’t afford to post bail, and risk assessment would avoid class bias because such assessment would be based on factors that are known to predict re-offending and not appearing in court. I criticized this idea, because risk assessment introduces a new class bias when factors include employment, housing, community support, and owning a car and a cell phone. Replacing judges’ biased discretion with a biased risk assessment tool does not solve the problem.

A recent article in the New York Times pointed out this problem, discussing how bail decisions use ‘little science’ and that ‘hidden biases against the poor and minorities can easily creep into the decision-making.’ For this and other reasons ‘many law enforcement groups and defense lawyers have supported the use of scientifically validated’ risk assessment tools. The news: ‘Now comes help in a distinctly modern form: an algorithm.’


There is new risk assessment tool based on an algorithm. Interestingly, this new tool, already tested and rolled out in 21 jurisdictions, challenges the widespread belief that class and criminal behaviour are tightly related:

The Arnold assessment has been met with some skepticism because it does not take into account characteristics that judges and prosecutors normally consider relevant: the defendant’s employment status, community ties or history of drug and alcohol abuse.

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Helaas, weer geen antwoord op kritiek Rotterdamwet

Rotterdam_kunstwerk_alles_is_waardeloos (wiki commons)

Mijn belangrijkste punt van kritiek op de Rotterdamwet betreft de inkomenseis: die is discriminerend en stigmatiserend. De inkomenseis houdt in dat woningzoekenden die leven van een bijstandsuitkering geen toegang hebben tot huurwoningen in de sociale en particuliere sector in aangewezen ‘probleemwijken’. De overheid hoopt hiermee de leefbaarheid in die wijken te verbeteren (sinds de invoering van de wet in 2006 maakt alleen Rotterdam er gebruik van; de inkomenseis geldt in vijf wijken op Rotterdam Zuid).

Naast de twijfel die ik heb over de effectiviteit (op basis van mijn eigen onderzoek, maar ook de laatste evaluatie van de wet overtuigt niet), is mijn bezwaar tegen deze maatregel dat woningzoekenden met lage inkomens niet alleen worden gediscrimineerd maar ook gestigmatiseerd, omdat er een link wordt gelegd tussen het leven van een laag inkomen en probleemgedrag (zie ook mijn stuk voor Vers Beton).

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