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Background - SOAs
- From October 2004, Super Output Areas (middle layer) replaced
wards as the standard lower-level geography for the June Agricultural
survey data.
- Super Output Areas (SOAs) are a new geography designed to improve
the reporting of small area statistics.
- They were introduced initially for use on the Neighbourhood
Statistics (NeSS) website, but are intended to eventually
become the standard across National Statistics.
- Until now (2004) the standard unit for presenting local statistical
information was the electoral ward/division. But because these
are subject to regular boundary changes this created problems
when trying to compare datasets from different time periods. Therefore
it was decided to develop a range of areas whose boundaries would
not change. These were built from groups of 2001 Survey Output
Areas (OAs) and are known as Super Output Areas (SOAs).
- There are 3 layers of SOA. These are based on population numbers
with the Middle Layer SOAs having a minimum population 5000 and
a mean of 7200. There are 6781 Middle Layer SOAs in England (compared
with approximately 8000 wards).
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New Hierarchy
- Note: Each layer nests within the layer above, i.e. SOAs
nest within NUTS 4, which nest within NUTS 3, etc.
- Level 1 - England
- Level 2 - NUTS 1 (or GOR - Government Office Regions)
- Level 3 - NUTS 3 (or Cty/UA - County/Unitary Authority)
- Level 4 - NUTS 4 (or LA - Local Authority)
- Level 5 - SOA middle layer (Super Output Area, middle layer)
- previously ward.
- [NUTS - the Nomenclature of Units for Territorial Statistics]
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Compare Wards to Super Output Areas
- Click Here to find which wards are
in which SOA, (note: These are the 1998 boundary wards).
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Data Searches - From England to Super Output Areas
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Background - Repopulation
- From 2004 a change in the methodology used to publish June Agricultural
Survey Data was adopted. This was to 'repopulate' data that would
otherwise be suppressed due to disclosure and data-protection
reasons.
- The repopulated data would be a random number based on the original
data, so would be a good approximation of the actual value, without
compromising confidentiality.
- For more information: Click
Here ...
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