Send provision leaving deprived areas of England ‘trailing behind’, report finds

The Guardian - World NewsEN 3 min read 100% complete by Sally Weale Education correspondentFebruary 11, 2026 at 11:00 PM

Read Original Article

AI Summary

medium article 3 min

A report by the Policy Exchange thinktank reveals an unequal distribution of increased special educational needs and disabilities (SEND) funding in England. The research, covering 2018-19 to 2024-25, found that SEND spending rose more rapidly in wealthier council areas (65%) compared to more deprived areas (51%), despite evidence linking SEND needs to deprivation. Two former education secretaries are urging the government to restore "sanity and certainty" to the SEND system. The report highlights the unsustainable financial burden on local authorities, with council leaders warning that SEND debts could lead to widespread bankruptcy by 2028. The government is expected to unveil proposals to overhaul the SEND system in an upcoming schools white paper.

Key Entities & Roles

Key Player Opposition Context

Zachary Marsh 50% Estelle Morris 60% Ruth Kelly ×270% Local Authority ×570% Policy Exchange ×380% United Kingdom ×290%

Keywords

special educational needs 100% send 90% local authority spending 80% deprived areas 80% affluent councils 70% inequitable spending 60% policy exchange 50% school funding 50% council debt 40%

Sentiment Analysis

Very Negative

Score: -0.60

Source Transparency

Source

The Guardian - World News

Classification Confidence

90%

This article was automatically classified using rule-based analysis.

Topic Connections

Explore how the topics in this article connect to other news stories

No topic relationship data available yet. This graph will appear once topic relationships have been computed.

special educational needs send local authority spending deprived areas affluent councils inequitable spending policy exchange school funding council debt

Explore Full Topic Graph

Find Similar Articles

AI-Powered

Discover articles with similar content using semantic similarity analysis.