This just in.

A call center in New Zealand dedicated to child welfare matters is collating data on families in order to see if patterns can be spotted, and child abuse prevented as a result. 

Whilst New Zealand is at the cutting edge of child welfare policy, the use of data to effectively predict the likelihood of future harm is something we should all be concerned about.

A uniform system which starts and ends with stats, raises several problems. The first is that we have no definitive data which confirms that factors like poverty, lack of education and family histories of violence are always predictors for child abuse. It also reinforces unhelpful and unkind stereotypes which will filter into the welfare system and become entrenched in its day-to-day ethos, bolstering stigmas and allowing the view that these families are somehow inferior, to endure.

Those families that do not ‘fit the profile’, also risk going unspotted by child welfare professionals. If poverty and a lack of education increase the risk of abuse in a home, then an abundance of resources and access to high quality education could also increase that risk by further enabling abusers through access to such resources. That is because highly manipulative behaviours, present in abusers, exist at every level of society, with stress perhaps rather than background, being the underpinning commonality which joins demographics together. Any future research would need to focus on stress and its impact on individuals, rather than the more obvious demarcations of class and opportunity.

Research tells us that social workers already have a natural bias towards families who are known to them as a result of parenting difficulties they’ve faced in the past. Bias is part of the human condition, persistent in all of us, and even affects those who we think are immune to it by virtue of their education or intellect, like judges for example,  but high quality training is required, even for judges, in order to ensure that it does not taint reasoning and lead to miscarriages of justice.

That this new initiative seeks to target areas of support rather than apportion blame and remove children from parents in the first instance, is at least a positive step. The initiative – that of using the collected data to try to preempt abuse – hopes to offer families at risk support, such as parenting programmes. The reality though, is that if stress is in fact the underlying cause of abuse in many homes, parenting classes are not likely to have any meaningful impact on preventing abuse.

The article also offers some interesting further reading on the topic:

• Predictive Modeling – Potential Application in Prevention Services and;
• Vulnerable Children – CAN ADMINISTRATIVE DATA BE USED TO IDENTIFY CHILDREN AT RISK OF ADVERSE OUTCOMES?

Whilst it must be right to use data and analyse it in order to build the best child welfare system possible, caution must be a necessary ally in ensuring that any findings are not set in stone and left to operate on their own, but are combined with professional expertise and the discretion of highly experienced and properly trained child welfare teams.