Segregation in education

Map 1: Proportions of White British pupils at state schools by Westminster parliamentary constituency (2016)
Sources: Department for Education; SchoolDash analysis.

Map 2: Proportions of White British pupils at state schools by Westminster parliamentary constituency (2016)
Sources: Department for Education; SchoolDash analysis.

Figure 1: Proportion of White British children in English mainstream state schools (2011-16)
Sources: Department for Education; SchoolDash analysis.
Map 3: Change in proportion of White British pupils by Westminster parliamentary constituency (2011-16)
Sources: Department for Education; SchoolDash analysis.

Figure 2: Change in proportion of White British children against starting proportion (2011-16)
Note: Two Local authority areas – the City of London and the Isles of Scilly – have been omitted because they show extreme percentage changes across very small numbers of pupils.
Sources: Department for Education; SchoolDash analysis.
  1. A school is deemed 'segregated' if the proportion of White British pupils is more than 15 percentage points higher or lower than that in other nearby schools. For example, in an area where 50% of pupils are White British, any school with less that 35% would be deemed to have a 'Low' proportion and any schools with more than 65% would be deemed to have a 'High' proportion.
  2. The above criterion clearly does not identify segregated schools in any areas where the overall proportion of White British pupils is less than or equal to 15%, or greater than or equal to 85% (since White British pupils cannot comprise less than 0% or more than 100% of the school population). To allow for this, we also define as 'segregated' any school that has less than half or more than twice the proportion of either ethnic group compared to other nearby schools. For example, a school in which less than 10% of pupils are White British in an area where 20% have this ethnicity is deemed to have a 'Low' proportion. Conversely, a school in which less than 10% of pupils are non-white-British in an area where 20% have this ethnicity is deemed to have a 'High' proportion of White British pupils.
  3. In some cases (eg, small schools or ethnically homogenous local areas), these proportions may correspond to very small numbers of pupils, potentially creating to misleading statistical effects. For this reason, we do not classify any school as 'High' or 'Low' if the number of pupils by which it is out of balance with its local area is less than eight.
Figure 3: Proportion of White British children in each school against proportion in its locality (2016)
Note: Only mainstream state schools are included. Independent schools and special schools have been omitted.
Sources: Department for Education; SchoolDash analysis.
Map 4: Proportions of ethnically segregated schools by local authority area (2016)
Sources: Department for Education; SchoolDash analysis.

Map 5: Proportions of ethnically segregated secondary schools by local authority area (2016)
Sources: Department for Education; SchoolDash analysis.

Figure 4: Ethnic balance of schools by Ofsted rating (2016)
Sample sizes: Primary schools – Outstanding: 3,064. Good: 11,706. Requires improvement: 1,338. Inadequate: 165.
Secondary schools – Outstanding: 710. Good: 1,739. Requires improvement: 495. Inadequate: 140.
Sources: Department for Education; SchoolDash analysis.
Figure 5: Ethnic balance of schools by religious denomination (2016)
Sample sizes: Primary schools – No faith: 10,773. Any faith: 6,250. C of E: 4,425. Catholic: 1,661. Other Christian: 106. Other faith: 58.
Secondary schools – No faith: 2,738. Any faith: 637. C of E: 212. Catholic: 319. Other Christian: 75. Other faith: 31.
Sources: Department for Education; SchoolDash analysis.
Figure 6: Ethnic balance of secondary schools by sex and academic selection (2016)
Sample sizes: Mixed sex: 3,006. Single sex: 369. Boys only: 158. Girls only: 211. Non-selective: 3,212. Grammar: 163.
Sources: Department for Education; SchoolDash analysis.
Figure 7: Ethnic balance of schools by academy classification (2016)
Sample sizes: Primary schools – Converter academies: 2,699. Free schools: 128. LA-maintained schools: 13,006. Sponsor-led academies: 1,190.
Secondary schools – Converter academies: 1,483. Free schools: 195. LA-maintained schools: 1,036. Sponsor-led academies: 661.
Sources: Department for Education; SchoolDash analysis.
Figure 8: Summary of ethnic segregation by primary school type (2016)
Notes: School deprivation figures based on pupils' eligibility for free school meals, with bands defined by the DfE. Local deprivation figures based on the mean IDACI of postcodes within a 2km radius of each school, with schools then divided into three roughly equally sized groups. Small schools have fewer than 200 pupils, large ones have more than 320. A small proportion of low attainers means less than 12% and a high proportion means more than 18%. Urban, suburban and rural groups use ONS rural-urban categories applied to school postcodes.
Sources: Department for Education; Department for Communities and Local Government; Office for National Statistics; SchoolDash analysis.
Figure 9: Summary of ethnic segregation by secondary school type (2016)
Notes: Local deprivation figures based on the mean IDACI of postcodes within a 4km radius of each school, with schools then divided into three roughly equally sized groups. Small schools have fewer than 700 pupils, large ones have more than 1,200. For other notes, see Figure 8, above.
Sources: Department for Education; Department for Communities and Local Government; Office for National Statistics; SchoolDash analysis.
Map 6: Proportions of socio-economically segregated primary schools by local authority area (2016)
Sources: Department for Education; SchoolDash analysis.

Map 7: Proportions of socio-economically segregated secondary schools by local authority area (2016)
Sources: Department for Education; SchoolDash analysis.

Figure 10: Summary of socio-economic segregation by primary school type (2016)
Notes: See notes accompanying Figure 8.
Sources: Department for Education; Department for Communities and Local Government; Office for National Statistics; SchoolDash analysis.
Figure 11: Summary of socio-economic segregation by secondary school type (2016)
Notes: See notes accompanying Figure 9.
Sources: Department for Education; Department for Communities and Local Government; Office for National Statistics; SchoolDash analysis.
Figure 12: Levels of ethnic and socio-economic segregation in primary schools by local authority (2016)
Note: Two Local authority areas – the City of London and the Isles of Scilly – have been omitted because they contain only one state school apiece.
Sources: Department for Education; SchoolDash analysis.
Figure 13: Levels of ethnic and socio-economic segregation in secondary schools by local authority (2016)
Note: Two Local authority areas – the City of London and the Isles of Scilly – have been omitted because they contain only one state school apiece.
Sources: Department for Education; SchoolDash analysis.
Figure 14: Summary of ethnic and socio-economic segregation by primary school type (2016)
Notes: See notes accompanying Figure 8.
Sources: Department for Education; Department for Communities and Local Government; Office for National Statistics; SchoolDash analysis.
Figure 15: Summary of socio-economic segregation by secondary school type (2016)
Notes: See notes accompanying Figure 9.
Sources: Department for Education; Department for Communities and Local Government; Office for National Statistics; SchoolDash analysis.
  1. The data presented here cover only pupils of compulsory school age (4-16 years) attending mainstream state schools. We have omitted special schools and independent schools. Data for the latter group is in any case mostly unavailable because independent schools are not subject to the same reporting requirements as state schools. Note also that ethnicity data is not available for all pupils even at state schools and some (typically about 1%) are recorded as having an unclassified ethnicity. Our data report only on children with classified ethnicities. Finally, the Department for Education routinely suppresses small values in its data – usually those corresponding to 1 or 2 pupils – in order to protect personal confidentiality. In those cases we have have made estimates of the numbers involved. This is necessarily an uncertain process, but any errors introduced are likely to be very small.
  2. Bangladeshi, Black African, Black Caribbean, Chinese, Gypsy/Roma, Indian, Irish, Irish traveller, Pakistani, White British, Other Asian, Other Black, White and Asian, White and Black African, White and Black Caribbean, Other Mixed, Other White, and Other.
  3. The small discrepancies in these figures (eg, 4.74 / 6.84 is 69%, not 70%) is caused by the fact that ethnicity data are missing for some pupils. 70% of pupils for whom we have ethnicity data are White British. All ethnic proportions quoted here use as the denominator the number of pupils for whom we have ethnicity data. This is typically about 1% lower than the total number of pupils.
  4. Schools were only matched with those of the same phase – either primary or secondary. Where data was unavailable for a nearby school (eg, newly established schools that had yet to submit pupil details), the next closest school was chosen so that each school was always compared with 10 nearby establishments.
  5. This is presumably in part because the radius encompassing the 10 closest schools tends to be larger, making it more likely that the analysis will incorporate more distant areas with different ethnic profiles. But this is not unreasonable: secondary schools usually have much bigger catchment areas than primary schools so should be compared with larger local areas.
  6. For numerical data by local authority area, see Appendix 2 of our accompanying paper. Note that these are not always identical to the data presented on the maps shown here. This is for two reasons: (i) SchoolDash Maps are continually updated with new information from the DfE and other sources, while the analysis in our paper used a snapshot taken on 3rd March 2017; and (ii) SchoolDash Maps use slightly different algorithms when processing data for all-through and middle schools (ie, those that have both a primary and a secondary phase). Where differences exist, the numbers given in our paper should be considered definitive.
  7. Note that within each region the percentage of schools with 'Low' proportions of White British pupils is not necessarily the same as the percentage of those with 'High' proportions of White British pupils. This may seem counterintuitive until we recall that schools are being classified by a threshold metric that does not distinguish between those that are very close to the cutoff point and those that are much further away. Where one group is much larger than another within the same geographical region it is an indication that the the average level of segregation among schools in the larger group is lower than that in the smaller group. For example, in London many more schools are classified as having 'Low' proportions of White British pupils than having 'High' proportions. This suggest that many 'Low' schools are close to the threshold while 'High' schools tend to be further away from it. This makes sense as London has a much smaller proportion of White British pupils than other regions, so the range of values that constitute a 'Low' classification is more limited than that for a 'High' classification.

The inbetweeners: Partially selective state schools

Figure 1: Private school enrolment rate by distance from state school (2016)
 
Note: Distances at the threshold between two groups are allocated to the higher group.
For example, schools that are exactly 2km away are included in the 2-5km category.
Sample sizes: Grammar schools: 163. Non-selective schools: 3,013. Partially selective schools: 38.
Sources: Department for Education; SchoolDash analysis.

  1. Nearby schools were only included if they overlapped in gender with the school in question. For example, when analysing a boys-only school, any nearby girls-only schools were excluded from the analysis because they do not compete for pupils.
  2. There is arguably a very small decline with distance. This may be a statistical artefact or it may indicate that private schools are slightly more common in urban areas, where schools are located closer together. Note that poverty rates (IDACI scores) also tend to decline with distance, presumably reflecting the fact that levels of deprivation are, on average, higher in urban areas.

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