The government could better support disadvantaged pupils if its intervention criteria included how heavily populated an area is, instead of the 鈥渃rude鈥� current measure of regions, researchers have said. Timo Hannay, the managing director of , said the current measure to target support to schools 鈥� based on the number of pupil premium children 鈥� was a 鈥渂inary threshold鈥�. Categorising pupils based on income alone also meant social deprivation was not 鈥渇ully captured鈥�, as health, crime and the environment also had effects on poverty. Other support has been based on where schools are located 鈥� for instance, the 55 education investment areas. But Hannay said this did not group together similar schools as it normally applied across a whole council area, missing the 鈥渢ype鈥� of place a school was located. applied a clustering algorithm to Index of Multiple Deprivation (IMD) data 鈥� which is relative poverty in small areas 鈥� and higher education participation rates. IMD data is also based on crime, employment, environment and health outcomes. Timo Hannay The analysis, funded by the Gatsby Foundation, found six clusters of schools with similar characteristics. 鈥淭he analysis indicates the importance of place, as well as poverty, but not in the sense of the regions that we tend to talk about,鈥� Hannay said. 鈥淚nstead, it highlights the differences between towns and cities on one hand, versus suburbs and rural areas on the other, and the relationships these have with poverty.鈥� For instance, the analysis found some urban areas performing exceptionally well 鈥� despite high income deprivation. 鈥淎ffluent urban鈥� areas 鈥� richer city areas in London 鈥� had large levels of income deprivation, but good outcomes, while 鈥減oor urban鈥� areas 鈥� particularly in the north and Midlands, but also east London 鈥� had adverse socioeconomic indicators and weak education outcomes, but not as bad as would be expected. But 鈥減oor suburban鈥� schools 鈥� mostly in the north and Midlands 鈥� had mixed IMD indicators, but high deprivation and poor outcomes and had 鈥渇allen the furthest behind鈥�. ‘More sophisticated view of disadvantage’ 鈥淔rom this analysis alone we cannot say exactly why, but perhaps we should be considering the educational impact of the cultural and social capital often associated with more densely populated places, not just the single dimension of affluence and poverty that currently gets all the attention,鈥� Hannay said. 鈥淲e hope the approach can form the basis of a more sophisticated view of disadvantage that recognises that not all poor communities are the same, and that deprivation has many faces. Understanding this is the first step towards better targeted interventions and policies to address these challenges.鈥� A Schools Week investigation last month, based on SchoolDash data, revealed the uphill battle faced by leaders of disadvantaged schools. Schools in the poorest areas struggled more to recruit teachers, had higher supply costs and paid more for basic supplies for pupils. And many gaps had worsened as schools with the poorest pupils were hit hardest by fall-out from the Covid pandemic. A new model to group 鈥榮imilar鈥� schools? 鈥�&苍产蝉辫; Suburban This represents 鈥渕iddle England鈥� outside the major cities. Socioeconomic and educational indicators are mostly unexceptional. 鈥�&苍产蝉辫; Affluent suburban Richer suburban and rural neighbourhoods. The incidence of income deprivation is very low, but educational outcomes are not as good as you might expect 鈥�&苍产蝉辫;Affluent urban Richer city areas, especially in London. Much greater levels of income deprivation, but also higher levels of educational engagement and better outcomes. 鈥�&苍产蝉辫; Poor urban Especially in the north and the Midlands, but also the east of London and elsewhere. Lots of adverse socioeconomic indicators, coupled with relatively weak educational outcomes 鈥� although not as bad as you might think given the levels of poverty. 鈥�&苍产蝉辫; Poor suburban Again, mainly in the north and Midlands. IMD indicators are mixed, but income deprivation is high and educational outcomes are poor. These are the areas that have fallen furthest behind. 鈥�&苍产蝉辫; Urban Middling city areas in London, Birmingham and Manchester, among other places. Moderately high levels of income deprivation, but relatively good educational outcomes.