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E-Frame conference, Amsterdam, 09.02.14 Measuring social progress in communities

Measuring social progress in communities

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Measuring social progress in communities. Today. About Social Life Measuring wellbeing at the local level WP9 Pan-European stocktake Case studies Key findings What next ?. About Social Life. The Young Foundation. Social Life. Measuring wellbeing at a local level. - PowerPoint PPT Presentation

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Page 1: Measuring social progress  in communities

E-Frame conference, Amsterdam, 09.02.14

Measuring social progress in communities

Page 2: Measuring social progress  in communities

Today

1. About Social Life2. Measuring wellbeing at the local level3. WP94. Pan-European stocktake5. Case studies6. Key findings7. What next?

Page 3: Measuring social progress  in communities

About Social Life

The Young Foundation Social Life

Page 4: Measuring social progress  in communities

Measuring wellbeing at a local level

Page 5: Measuring social progress  in communities

Five stages of WARM (first version)

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Slide 6

WARM in Ardwick, Manchester

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WP9: Work package stages

Stage oneYoung Foundation

Inventory of pan-European indicators

Stage twoYoung Foundation

Case Studies in Barcelona & Malmö

Stage threeUNISI & UNIPI

Convene expert workshop

Stage fourYoung Foundation

Report & recommendations

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Pan-European stocktake

National levelPan-European country level data

Regional level (NUTS 1-5)European sub-country level units

Data for: England, Ireland, France, Spain, Sweden

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Stocktaking

Measure Key terms & concepts Indicator SP SE FR EN IELife satisfaction

Self-assessed life satisfaction; happiness

All things considered, how satisfied are you with your life as a whole nowadays?

1 3 1 3 1

Education Participating in further or higher education

Participation of 17 year olds in education or training

3 3 3 3 3

Education Young people who are unemployed and not in education

16 to 18 year olds who are not in education, training or employment

3 3 3 3 3

Education Per cent of population completed higher education

% of the population whose highest qualification is a first degree (or equivalent)

3 3 3 3 3

Education Per cent of population with no or low qualifications

Adults (25-54) With No or Low Qualification Rate (Persons, %)

3 2 3 3 3

Health People with long-term poor health e.g. cancer; depression - of working age (16 to 65)

People of working age with a limiting long-term illness (Persons, Percentage)

2 3 2 3 3

Health Good health General health: Good (Persons, %)

3 3 1 3 1

Health Subjective or self-assessed levels of health

Self-reported measure of people's overall health and wellbeing

3 3 1 3 3

Material wellbeing

Per cent of people unemployed

Unemployment rate (Persons, %)

3 3 3 3 3

Material wellbeing

Per cent of people receiving benefits for unemployment

Claimants for Less than 12 Months - Rate (Persons, %)

1 2 2 3 1

RAG rating: 3 = Data exists. 2 = proxy indicator exists, 1 = Indicator does not exist.

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Methodological challenges:

• NUTS are problematic at local level• Multiple geographical units• Timeliness• Cultural differences• Robustness & sample size• Data availability and co-ordination between agencies places limitations on what can be done.

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Case studies

What does resilience and wellbeing mean in other neighbourhoods in Europe?

Local Level dataInventory of pan-European indicators

Les Roquetes (Barcelona) & Lindängen (Malmö)

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Lindängen, Malmö, Sweden

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Les Roquetes, Barcelona, Spain

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Key findings from case studies

The data wasn’t capturing the strengths and needs in both these areas. For example:

• Sense of belonging to the local area• Volunteering• Ability to influence local decisions• Social capital• Financial security

This makes it difficult for local agencies to act accordingly

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Overall findings

• Country level data maps to WARM framework

• The larger the spatial unit, the more data there is available

• More data at individual level (eg. education, health, employment) rather than collective level (eg. neighbourliness, sense of belonging to local area)

• Local level wellbeing and resilience is often invisible in data

Therefore…

• Need to bridge top-down and bottom-up data collection

• Local agencies need to collectively find ways to capture this data

• Need to think of a role for crowd-sourced locally generated data

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Resilience Wellbeing

WARM version 2, using predictive data from national surveys

What next?

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A framework for social sustainability

Social Life Social Sustainability Framework, 2011