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Academics brand categorisation of ethnic pupils 'almost useless'

1 min read Education
The system used by the Department for Education (DfE) to categorise the ethnicity of pupils and monitor their attainment has been branded unfit for purpose by academics.

A study by the Institute for Policy Studies in Education at London Metropolitan University, found that the categories of white, mixed, Asian, black and Chinese mask ethnic, linguistic, religious and social diversity and “do little to enhance understanding” of the disadvantages affecting minority communities.

The research, which was commissioned by creative-writing charity Arvon, suggests that government should “rethink” the ethnic categories it uses to record data and assess educational disadvantage.

It proposes that recording children’s first language could be a more useful way of monitoring progress and attainment.

The report cites Peterborough as an area where there are growing numbers of Eastern European children. “We have no way of knowing how they are attaining,” the study says. “In terms of ethnicity they are hidden in the ‘white’ category.”

Sumi Hollingworth, one of the authors of the study, explained: “With the growing number of new arrivals from both western and eastern Europe, for example Polish, Czech, Portuguese, Spanish, all of whom speak a first language other than English, this category is almost useless as it masks language barriers and social class differences, but also potential discrimination faced by some of these groups.”

The research also argues that the conflation of data on children of African and Caribbean descent into the category ‘black’ masks important variations in attainment.

For example, French and Somali-speaking children's attainment is generally lower than that of children with Caribbean heritage, while English-speaking children of African descent achieve similar results at school to children in the white British group.

A Department for Education spokeswoman said: “We’re working on a revised ethnicity standard which allows for varying levels of detail on ethnicity data to be collected locally. We’ll be looking at how to collect more detailed national ethnicity data in the future.”

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