The June Agricultural Survey SOAs

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Super Output Areas - and the June Agricultural Survey


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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).

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]

Compare Wards to Super Output Areas

  • Click Here to find which wards are in which SOA, (note: These are the 1998 boundary wards).

Data Searches - From England to Super Output Areas


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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