creating multiple dimension indices for local areas

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“Answering the Ultimate Question of Life, the Universe, and Everything” Developing local multiple dimension indices to compare areas in Birmingham Richard Browne Equalities, Social Cohesion and Community Safety [email protected] @richardbrowne80

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Presentation for the recent internal research day at Birmingham City Council. Presentation covering the development of several data indices used by City Council

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Page 1: Creating Multiple Dimension Indices for local areas

“Answering the Ultimate Question of Life, the Universe, and Everything”

Developing local multiple dimension indices to compare areas in Birmingham

Richard BrowneEqualities, Social Cohesion and Community [email protected]@richardbrowne80

Page 2: Creating Multiple Dimension Indices for local areas
Page 3: Creating Multiple Dimension Indices for local areas

The world is full of indices…..

Page 4: Creating Multiple Dimension Indices for local areas

FTSE 100

Page 5: Creating Multiple Dimension Indices for local areas
Page 6: Creating Multiple Dimension Indices for local areas
Page 7: Creating Multiple Dimension Indices for local areas
Page 8: Creating Multiple Dimension Indices for local areas

Index of Multiple

Deprivation

Page 9: Creating Multiple Dimension Indices for local areas

• Sustainability Index• Neighbourhood

Deprivation Index• Community Cohesion

Index• Big Lottery Index• Mental Health Index• Child Poverty Index• Social Impact of the

Recession Index

We love a good index…

Page 10: Creating Multiple Dimension Indices for local areas

But what is an index?

• Effectively there are composite measurements• Way of bringing multiple datasets together• Way of monitoring complex issues/problems in

an simple way• Way of measuring something where there is no

existing single way of measuring it

Page 11: Creating Multiple Dimension Indices for local areas

Why use an index?.....

The Douglas Adams Syndrome

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Page 13: Creating Multiple Dimension Indices for local areas

Community Cohesion Index

• Sought to provide a measurement of community cohesion at ward level in the form of a single numerical score which can then be tracked over time

• Used by the Community Cohesion Forum to direct resources in perceived vulnerable areas

• Not a replacement for tension monitoring – not likely to “predict a riot or disturbance”

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Fully understand the subject that you are measuring

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Page 16: Creating Multiple Dimension Indices for local areas

Community Cohesion

The index must be based on a robust understanding of the issue.The CCI was based on firm academic research and the content of the Community Cohesion Strategic Framework

Destructive Behaviour Element•prevalence of criminal and anti-social acts against other citizens•strong indicator of a lack of cohesion within a local community as trust is destroyed and individuals become isolated

Deprivation Element •structural inequality between communities is a powerful inhibitor of cohesion in more deprived wards

Perception Element•Resident perceptions of community harmony, decision making and personal safety vital indicators of cohesion

Page 17: Creating Multiple Dimension Indices for local areas

Choose Appropriate indicators

•Available at a consistent geographical level•From a consistent timeframe

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Criteria

• Relevant to, and capable of measuring a recognised aspect of cohesion

• Able to produce sufficiently robust data at ward level

• Updated at least annually• Available with a time lag of no more than 6-9

months after the period they relate to.

Page 19: Creating Multiple Dimension Indices for local areas
Page 20: Creating Multiple Dimension Indices for local areas

Find the Standard Score (Z-score) for each data point

Page 21: Creating Multiple Dimension Indices for local areas

Z-Scores

• To allow the combination of indicators of different types and units, its is necessary to find the standard score for each indicator data point.

• The Z-score just is indication of the relationship between a particular score and the mean – showing how many standard deviations a particular observation is from the mean

• To this just calculate the mean and standard deviation of all observations and apply “standardize function in Execl

• It will leave you with a + or – score for each ward.• These can be then averaged up across the indicators to give

on overall score.

Page 22: Creating Multiple Dimension Indices for local areas

Average Scores up,Decide and apply weightings

Page 23: Creating Multiple Dimension Indices for local areas

Weightings

• Now should have a list of 40 ward scores for each indicator in your index

• Weightings are important – are some indicators more important than others?

• This can be a very subjective• Once weightings are applied you can calculate

final scores for each index.

Page 24: Creating Multiple Dimension Indices for local areas

Sutton Four Oaks 27 Sutton Four Oaks 51 Sutton Four Oaks 43 Sutton Vesey 18Sutton Vesey 26 Sutton New Hall 47 Sutton New Hall 41 Moseley And Kings Heath 13Sutton New Hall 26 Sutton Trinity 39 Sutton Vesey 37 Sutton Four Oaks 10Sutton Trinity 17 Sutton Vesey 33 Sutton Trinity 32 Longbridge 10Perry Barr 15 Oscott 31 Hall Green 26 Sutton New Hall 9Hall Green 15 Perry Barr 30 Harborne 25 Northfield 9Oscott 14 Harborne 28 Perry Barr 23 Oscott 9Moseley And Kings Heath 11 Hall Green 26 Selly Oak 23 South Yardley 8Bournvil le 11 Bournvil le 23 Bournvil le 22 Billesley 8Harborne 10 Billesley 17 Northfield 17 Brandwood 7Selly Oak 10 Springfield 16 Edgbaston 14 Selly Oak 6Northfield 10 Longbridge 16 Oscott 12 Perry Barr 6Longbridge 8 Sheldon 14 Quinton 10 Hall Green 4Billesley 6 Moseley And Kings Heath 10 Moseley And Kings Heath 8 Weoley 3Brandwood 5 Weoley 9 Handsworth Wood 7 Acocks Green 2Edgbaston 4 Edgbaston 9 Sheldon 6 Sparkbrook 2Weoley 4 Quinton 7 Brandwood 5 Sutton Trinity 1Sheldon 4 Erdington 6 Erdington 4 Kings Norton 1Springfield 3 Acocks Green 6 Weoley 4 Birmingham Score 0Quinton 3 Kings Norton 3 Springfield 3 Sheldon 0South Yardley 2 Brandwood 3 Longbridge 1 Bournvil le 0Acocks Green 0 South Yardley 2 Birmingham Score 0 Handsworth Wood -1Birmingham Score 0 Birmingham Score 0 Bartley Green -4 Springfield -2Kings Norton 0 Bartley Green 0 Kings Norton -4 Edgbaston -2Handsworth Wood -1 Northfield -1 Bil lesley -5 Aston -2Erdington -1 Selly Oak -1 Hodge Hil l -5 Quinton -3Hodge Hil l -6 Tyburn -8 Acocks Green -8 Bordesley Green -3Bartley Green -7 Hodge Hil l -8 South Yardley -9 Ladywood -3Stockland Green -8 Handsworth Wood -13 Tyburn -10 Harborne -3Tyburn -8 Stockland Green -15 Stockland Green -10 Washwood Heath -5Stechford and Yardley North -10 Bordesley Green -19 Stechford and Yardley North -10 Stockland Green -5Bordesley Green -11 Stechford and Yardley North -23 Bordesley Green -21 Soho -5Sparkbrook -13 Sparkbrook -23 Kingstanding -22 Hodge Hil l -6Aston -15 Lozells And East Handsworth -24 Shard End -28 Stechford and Yardley North -6Shard End -18 Shard End -27 Aston -30 Erdington -7Soho -20 Aston -30 Ladywood -30 Tyburn -8Washwood Heath -20 Kingstanding -37 Soho -30 Nechells -9Ladywood -22 Nechells -44 Washwood Heath -32 Shard End -9Lozells And East Handsworth -23 Washwood Heath -45 Sparkbrook -34 Bartley Green -12Nechells -23 Soho -46 Lozells And East Handsworth -34 Lozells And East Handsworth -16Kingstanding -24 Ladywood -62 Nechells -34 Kingstanding -20

NB. A higher score i s better NB. A higher score i s better

Destructive Behaviour Element Deprivation Element Perception ElementCohesion Index : 2008/09 Baseline by Element Scores

Overall IndexCohesion Index 2008/09 Baseline

Page 25: Creating Multiple Dimension Indices for local areas

Make all your pretty maps and graphs!!!

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Drawbacks and future work

• They are only snapshots in time.• Geographical ones are easier than community

based ones.• Ward based indicators are not that helpful in

many respects.• Significant drawbacks in relation to data

availability • What do they really tell us? Tell us where not

why…..

Page 29: Creating Multiple Dimension Indices for local areas

Photos Recognition

• NASA Goddard Space Flight - “Hurricane Carlotta Stands Out in Earth View” June 15 2012

• Leo Reynolds “Number 1” Flickr May 10 2010• Jon Jordan “Number 2” Flickr December 5 2013• Yuma Hori “Tiny Micro adventure 3rd Floor” Flickr

December 17 2006• Yaniv Golan “White 5 on Orange Dumster” Flickr

November 12 2005

Page 30: Creating Multiple Dimension Indices for local areas

“Answering the Ultimate Question of Life, the Universe, and Everything”

Developing local multiple dimension indices to compare areas in Birmingham

Richard BrowneEqualities, Social Cohesion and Community [email protected]@richardbrowne80