The social mobility index of England sets out the differences between where children grow up and the chances they have of doing well in adult life.

More details available at: https://www.gov.uk/government/publications/social-mobility-index

The Social Mobility Index compares the chances that a child from a disadvantaged background will do well at school and get a good job across each of the 324 local authority district areas of England. It examines a range of measures of the educational outcomes achieved by young people from disadvantaged backgrounds and the local job and housing markets to shed light on which are the best and worst places in England in terms of the opportunities young people from poorer backgrounds have to succeed.

Please take a look at our interactive atlas spine chart, where you can discover how all the English districts, unitaries and boroughs ranked, as well as the data scores behind the ranks. http://atlas.cambridgeshire.gov.uk/SocialMobilityIndex/atlas.html

Social mobility and life opportunities across different generations in Great Britain; indicators from the Opinions and Lifestyle Survey (OPN).

🇬🇧 영국 English The social mobility index of England sets out the differences between where children grow up and the chances they have of doing well in adult life. More details available at: https://www.gov.uk/government/publications/social-mobility-index The Social Mobility Index compares the chances that a child from a disadvantaged background will do well at school and get a good job across each of the 324 local authority district areas of England. It examines a range of measures of the educational outcomes achieved by young people from disadvantaged backgrounds and the local job and housing markets to shed light on which are the best and worst places in England in terms of the opportunities young people from poorer backgrounds have to succeed. Please take a look at our interactive atlas spine chart, where you can discover how all the English districts, unitaries and boroughs ranked, as well as the data scores behind the ranks. http://atlas.cambridgeshire.gov.uk/SocialMobilityIndex/atlas.html

This dataset is about books. It has 44 rows and is filtered where the book subjects is Social mobility-Great Britain. It features 9 columns including author, publication date, language, and book publisher.

Abstract copyright UK Data Service and data collection copyright owner.

The purpose of this survey was to enquire into patterns of social mobility in England and Wales.
Main Topics:

Variables
Detailed information was collected on (i) the occupations held by respondents at various stages in their working lives and their associated employment status and industry; (ii) their education and all forms of occupationally relevant training; (iii) their formal qualifications; and (iv) to a more limited extent, the occupations, training, and qualifications of various of their kin. Questions were also included on respondents' areas of residence, current income, friendship patterns, political affiliations, etc.
In order to construct a data set which would permit the investigation of trends in social mobility between 1972 and 1983, an extensive recoding excercise was undertaken. This involved the recoding of data for approximately one in six (N=1522) of respondents to the 1972 survey for whom information on both their present and their fathers' occupation was available. This information, which was originally coded to the 1970 OPCS system of occupational classification was recoded to the 1980 OPCS system. These data have now been merged with the main survey (although they can be supplied as a separate file).
Occupational data from the British Election Study, 1983 (SN:2005) were recoded so as to become comparable with these data. It was hoped that the 'splicing' of the two studies would enable researchers to gain a clear idea of how mobility rates and patterns have changed in Britain over recent decades.

This project looks at the patterns and trends of social mobility and social capital in China and Britain. With regard to mobility, it examines how family class influences children's education, employment and occupational attainment in the two countries, what similarities and what differences there may be in the regulations. Particular attention is given to the role of household registration system (hukou) in China in inhibiting the mobility chances for people originating from rural origins. As for social capital, it examines the sources, manifestations and impacts of social networks and civic engagement in the two countries. While formal civic engagement is less developed in China, social networks (guanxi) may be more developed in that country. Close attention will be paid to the role of the political institutions in the first regard and the instrumental roles of networks in promoting or inhibiting social advancement in the second regard. A range of publicly available datasets in the two countries will be used such as Understanding Society and China General Social Survey. It will use a range of descriptive and modelling techniques. Various dissemination activities will take place such as presentations at the international sociology conferences and in China.

Abstract copyright UK Data Service and data collection copyright owner.

The COVID Social Mobility and Opportunities Study (COSMO) is a longitudinal cohort study, a collaboration between the UCL Centre for Education Policy and Equalising Opportunities (CEPEO), the UCL Centre for Longitudinal Studies (CLS), and the Sutton Trust. The overarching aim of COSMO is to provide a representative data resource to support research into how the COVID-19 pandemic affected the life chances of pupils with different characteristics, in terms of short-term effects on educational attainment, and long-term educational and career outcomes.

The topics covered by COSMO include, but are not limited to, young people's education experiences during the pandemic, cancelled assessments and education and career aspirations. They have also been asked for consent for linking their survey data to their administrative data held by organisations such as the UK Department for Education (DfE). Linked data is planned to be made available to researchers through the ONS Secure Research Service.

Young people who were in Year 11 in the 2020-2021 academic year were drawn as a clustered and stratified random sample from the National Pupil Database held by the DfE, as well as from a separate sample of independent schools from DfE's Get Information about Schools database. The parents/guardians of the sampled young people were also invited to take part in COSMO. Data from parents/guardians complement the data collected from young people.

Further information about the study may be found on the COVID Social Mobility and Opportunities Study (COSMO) webpage.

COSMO Wave 2, 2022-2023
All young people who took part in Wave 1 (see SN 9000) were invited to the second Wave of the study, along with their parents (whether or not they took part in Wave 1).

Data collection in Wave 2 was carried out between October 2022 and April 2023 where young people and parents/guardians were first invited to a web survey. In addition to online reminders, some non-respondents were followed up via face-to-face visits or telephone calls over the winter and throughout spring. Online ‘mop-up’ fieldwork was also carried out to invite all non-respondents into the survey one last time before the end of fieldwork.

Latest edition information:
For the second edition (April 2024), a standalone dataset from the Keeping in Touch (KIT) exercise carried out after the completion of Wave 2, late 2023 have been deposited. This entailed a very short questionnaire for updating contact details and brief updates on young people's lives. A longitudinal parents dataset has also been deposited, to help data users find core background information from parents who took part in either Wave 1 or Wave 2 in one place. Finally, the young people's dataset has been updated (version 1.1) with additional codes added from some open-ended questions. The COSMO Wave 1 Data User Guide Version 1.1 explains these updates in detail. A technical report and accompanying appendices has also been deposited.

Further information about the study may be found on the COSMO website.

Main Topics:

For young people, Wave 2 included:

• a household grid
• changes to current status since Wave 1
• qualifications studied towards
• early labour market experience
• residual disruption due to the pandemic
• university applications
• attitudes to education and future careers
• spare time/leisure activities
• homelessness
• health and wellbeing
• friends, peers and family support
• health-related behaviours.

For parents, Wave 2 included:

• demographics
• attitudes to education/education and career aspirations
• parenting, home learning, tuition and catch-up
• working status across the pandemic (since the last interview for parents also interviewed in Wave 1)
• parental tenure, HRP and occupation details
• parental education
• parental income
• grandparents
• COVID-19 history and vaccination
• parent health and wellbeing
• disadvantage.

This qualitative data-set is of young people's spatial imaginaries within the UK context. It contains interviews carried out with young people aged 16/17 years across different geographic contexts. In particular, interviews focussed around the importance and significance of place, including: i) the role place has on the choices of young people who are socially and educationally similar but located in geographically diverse areas; ii) ways in which economically, socially, culturally or politically distinct places act as pull or push factors for different social groups; iii) what social, cultural, or economic importance particular localities hold for different groups.

The creation of a fairer society through social mobility is high on the political agenda in the UK. It is often assumed that widening participation in higher education (HE), through various policies and initiatives, will equate to a fairer and more socially mobile society. Yet, while more disadvantaged groups are now progressing to HE, social mobility remains weak, suggesting that this is an over-simplified picture of the ways in which social inequalities are (re)produced in countries like the UK. The geographical (im)mobility of young people at this key transition point is rarely alluded to here, in terms of its significance in shaping social (im)mobility. In spatially diverse countries like the UK, access to universities, key labour markets, social networks, and other valuable resources often necessitate some degree of geographical mobility. In addressing social inequalities in wider society, it is therefore crucial to understand the nature of student flows across diverse parts of the UK, including the rationales different young people have for their (im)mobility to and from different places. There is already some evidence to suggest that the costs of HE study can deter the most disadvantaged young people from moving away for their studies, but what other place-based factors, including the cultural, social, and economic characteristics of localities might be important in shaping student (im)mobility? This interdisciplinary project will undertake an innovative and far-reaching programme of policy relevant research addressing the mobility patterns of UK HE students. The value of this research has been endorsed by all four UK HE Funding Councils, the UK Government's Social Mobility and Child Poverty Commission (Chaired by Rt. Hon. Alan Milburn), The Sutton Trust, and Universities UK. These organisations are members of the project stakeholder group and will be closely involved in the research and dissemination programme, ensuring that the research addresses areas of policy relevance and reaches a wide audience. This novel research will uncover, for the first time, the nature of student flows within and across the four countries of the UK, together with rich and in-depth understandings about how they are shaped. Taking into account the socially, economically, politically and culturally diverse nature of UK society, the project will seek to understand the placed nature of educational decision making in particular. This unique work is interdisciplinary in nature, drawing on, and contributing to, the academic disciplines of geography, education, and sociology. The research is mixed methods and organised around two distinct but sequential phases, which include large scale quantitative analysis of UK-wide student records data (phase 1) that will frame the collection of new qualitative data (phase 2). Phase 1 will involve advanced spatial analysis to examine student flows at country, region, and locality levels, producing innovative graphics displaying these spatial movements in visual form. This analysis will explore patterns and relationships between student movements and social as well as spatial characteristics. In the second phase, qualitative research will take place in 10 purposefully selected case study schools across the UK, selected on the basis of criteria developed from the quantitative analysis. To explore the sorts of factors shaping young people's mobility patterns, data collection will involve interviews with young people, two members of their social network, as well as observation of their school contexts. These rich qualitative data will dig beneath the surface of the quantitative patterns, capturing how young people's subjective experiences of space and their own geographical imaginaries impact on their geographic (im)mobility. It will explore how these relationships to place and mobility intentions are constructed and influenced by their individual biographies, social network and school.

Data on young people’s attitudes about their futures by household income, deprivation, and parental education levels. Estimates using Wave 1 of the COVID Social Mobility and Opportunities (COSMO) study dataset.

The CLOSER Contextual Database provides time series data on some key indicators of social change to facilitate and promote cross-cohort research. In addition to the quantitative indicators, the Database provides information on the institutional context through key dates related to the implementation of policies.

The CLOSER Contextual Database is one of the data resources of CLOSER (Cohort & Longitudinal Studies Enhancement Resources, www.closer.ac.uk). This initiative promotes the use and access of the UK's longitudinal studies.

This study supplies experimental statistics on the association between degree attainment (i.e. the proportion of first degree qualifiers awarded a first or upper second class) and our area-based measure of deprivation across the UK. Social mobility is often viewed as relating to the extent to which an individual’s outcomes (e.g. on the basis of earnings or employment) differ to that of their parents. Improving social mobility continues to be a key policy objective across all nations of the UK, with education seen as one of the potential ways in which this can be achieved. Consequently, this has led to regular statistics being distributed on attainment gaps in primary and secondary education by various measures of deprivation. The evidence consistently illustrates those experiencing greater levels of deprivation display lower levels of attainment, which can inhibit progress in raising social mobility.

The Air Traffic Data International Mobility Indicators for the UK results from the investigation on air passenger data from the Sabre Corporation [1], accessed through a collaboration with the JRC Ispra. Starting from air passenger traffic volumes from each country of origin and to the final country of destination, two mobility indicators based on log flow ratios were provided: the Flow Log Ratio (FLR) and the Cumulative Flow Log Ratio (CFLR). These indicators, computed with monthly and yearly resolution, allow to eliminate short term trips observing the general pattern of longer-term mobility. The Flow Log Ratio (FLR) is defined as the logarithm of the ratio between the number of incoming individuals in a given country (e.g., entering the UK) and the number of outgoing individuals in the same observed country (e.g., leaving the UK). Specifically, for each country or set of countries of origin and destination (C1, C2), and over a specified period of time, t, we consider the incoming flow FI(t) (from C2 to C1) and the outgoing flow FO(t) (from C1 to C2). The Flow Log Ratio FLR(t) is then defined as log2(FI(t)/FO(t)). If the FLR is below 0, it means that more individuals moved out of C1 compared to those who moved in, while an index above 0 shows that C1 is an attractive country with more people coming in. An FLR of 1 means the incoming flows are twice as large as outgoing flows, while an FLR of -1 means the outgoing flows are twice less. The FLR is an indicator that allows to study the trends point by point in time and observe point-wise changes in trends. The Cumulative Flow Log Ratio (CFLR) is defined as the logarithm of the ratio between the cumulative incoming flows and cumulative outgoing flows up to the current time window t. Compared to the FLR, the CFLR allows to evaluate cumulative pattens over much longer periods, rather than performing a point-wise analysis. The indicators are provided for the UK versus the rest of the European Union. Further, we provide regional indicators using the division of EU member states into regions proposed by the EuroVoc vocabulary [2]: Northern (Finland, Denmark, Sweden, Estonia, Latvia, Lithuania), Southern (Greece, Italy, Malta, Portugal, Cyprus, Spain), Western (France, Germany, Ireland, Luxembourg, Netherlands, Austria, Belgium), Central and Eastern (Hungary, Poland, Romania, Bulgaria, Croatia, Slovakia, Czechia, Slovenia). Europe-level indicators are also included. The entire Air Traffic Data International Mobility Indicators for the UK includes monthly and yearly Flow Log Ratio and Cumulative Flow Log Ratio indicators calculated at different spatial and time resolutions. Further, the monthly set also provides the components obtained by applying Seasonal-Trend decomposition (TSD) [3] to FLR regional values. These allow for separating seasonal from overall patterns. The Air Traffic Data International Mobility Indicators for the UK include FLRs and CFLRs values calculated for the United Kingdom versus a) the 27 countries in the European Union, b) the four regions of the European Union, and c) the entire European Union. Monthly data are provided from February 2011 to October 2021, while yearly data covers 2011-2021. Moreover, the monthly dataset includes components, i.e., trend, seasonal, and residual signals, obtained by decomposing the regional EU FLRs with Statsmodels [4] Python library (using an additive model with 12 components). In publishing the dataset, we followed the DEU guidelines for publishing high-quality data. To ensure interoperability and facilitate automatic processing by machines, we used the CSV format with US-ASCII encoding. All country names follow the ISO2 standard. The European subregions follow the EuroVoc vocabulary, dates are standardised, time series are complete. The CSV files are accompanied by a README that defines all variables included in the data and cross-references publications. References: [1] Sabre. Market intelligence, global demand data. https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202302101437200109948&URLID=11&ESV=10.0.19.7431&IV=259BC11764855306985B70AF21AF9795&TT=1676039840964&ESN=Vs8xERNXlu7bOs3Tyb9f%2Fa8tNspLAa%2FGwagIu4vHdcQ%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cHM6Ly93d3cuc2FicmUuY29tL3Byb2R1Y3RzL21hcmtldC1pbnRlbGxpZ2VuY2UvLA&HK=D2BCC95C29FB56BEC2A395CC3D9C17C53D482CA86C9C38AA591FB4CEC3FD597F 2021. Accessed: 2021-11-15. [2] https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202302101437200109948&URLID=10&ESV=10.0.19.7431&IV=2934525D891132A3AEF7FAE3284ABBF5&TT=1676039840964&ESN=1y%2BYp5gdrdyZM9uJx0B%2FPBEP1rDDsKvDHe7LgSX0cS8%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cHM6Ly9ldXItbGV4LmV1cm9wYS5ldS9icm93c2UvZXVyb3ZvYy5odG1sP3BhcmFtcz03Miw3MjA2&HK=8C84248906662B84FF5949BF9C969AA3FE97AB3970282A47E9BDFA1EB8E0B1F6 [3] Cleveland, R.B., Cleveland, W.S., McRae, J.E. and Terpenning, I., 1990. STL: A seasonal-trend decomposition. J. Off. Stat, 6(1), pp.3-73. [4] McKinney, W., Perktold, J., & Seabold, S. (2011)....

Addressing the under-researched issue of weapon tolerance, the paper examines factors behind male knife and gun tolerance across four different cultures, seeking to rank them in terms of predictive power and shed light on relations between them. To this end, four regression and structural equation modelling analyses were conducted using samples from the US (n = 189), India (n = 196), England (n = 107) and Poland (n = 375). Each sample of male participants indicated their standing on several dimensions (i.e., predictors) derived from theory and related research (i.e., Psychoticism, Need for Respect, Aggressive Masculinity, Belief in Social Mobility and Doubt in Authority). All four regression models were statistically significant. The knife tolerance predictors were: Aggressive Masculinity (positive) in the US, Poland and England, Belief in Social Mobility (negative) in the US and England, Need for Respect (positive) in India and Psychoticism (positive) in Poland. The gun tolerance predictors were: Psychoticism (positive) in the US, India and Poland, Aggressive Masculinity (positive) in the US, England and Poland, and Belief in in Social Mobility (negative) in the US, Belief in Social Mobility (positive) and Doubt in Authority (negative) in Poland. The Structural Equation Weapon Tolerance Model (WTM) suggested an indirect effect for the latent factor Perceived Social Ecological Constraints via its positive relation with the latent factor Saving Face, both knife and gun tolerance were predicted by Psychoticism.

ObjectiveSince the outbreak of COVID-19, public health and social measures to contain its transmission (e.g., social distancing and lockdowns) have dramatically changed people's lives in rural and urban areas globally. To facilitate future management of the pandemic, it is important to understand how different socio-demographic groups adhere to such demands. This study aims to evaluate the influences of restriction policies on human mobility variations associated with socio-demographic groups in England, UK.MethodsUsing mobile phone global positioning system (GPS) trajectory data, we measured variations in human mobility across socio-demographic groups during different restriction periods from Oct 14, 2020 to Sep 15, 2021. The six restriction periods which varied in degree of mobility restriction policies, denoted as “Three-tier Restriction,” “Second National Lockdown,” “Four-tier Restriction,” “Third National Lockdown,” “Steps out of Lockdown,” and “Post-restriction,” respectively. Individual human mobility was measured with respect to the time period people stayed at home, visited places outside the home, and traveled long distances. We compared these indicators across the six restriction periods and across socio-demographic groups.ResultsAll human mobility indicators significantly differed across the six restriction periods, and the influences of restriction policies on individual mobility behaviors are correlated with socio-demographic groups. In particular, influences relating to mobility behaviors are stronger in younger and low-income groups in the second and third national lockdowns.ConclusionsThis study enhances our understanding of the influences of COVID-19 pandemic restriction policies on human mobility behaviors within different social groups in England. The findings can be usefully extended to support policy-making by investigating human mobility and differences in policy effects across not only age and income groups, but also across geographical regions.

The State of Calderdale assembly is held annually. It is hosted by Calderdale Council to bring together key representatives from the public, private, and voluntary and community sectors. Each organisation has its own priorities, many of which are similar to other organisations in the borough. The event enables a discussion between all partners as to how to meet these priorities, identify where there may be gaps and provide opportunities for working together. By targeting our resources together, we can work together to make the most improvements for Calderdale.

The theme for the 2018 assembly was Calderdale Vision 2024 - Calderdale Council will be 50 in 2024 and the vision is our ambition for where we want to be by our anniversary.

You can also watch the keynote speech from the 2018 assembly, given by Lord Victor Adebowale, Chief Executive of Turning Point: State of Calderdale 2018: Keynote speech.

The information in this dataset provides signposts to the key issues that inform the Council's three priorities - Grow the economy, Reduce inequalities, and Build a sustainable future.

This dataset also includes a report that looks at the State of Nation 2017: Social mobility in Great Britain by the Social mobility commission.

Abstract copyright UK Data Service and data collection copyright owner.

The aims and objectives of this project were :
to examine the relationship between, one the one hand, social mobility and on the other, political preferences, attitudes and behaviour within the context of Northern Ireland, a society which is deeply divided on politico-religious backgrounds. In particular, the aim was to determine the degree to which those who are socially mobile display patterns of political preferences, attitudes or behaviour (in specific areas) which are distinctively different from those characteristic of their class of origin or class of destination;
to advance our understanding of whether social mobility might lead to change in political attitudes and constitutional aspirations in Northern Ireland, as is widely believed;
to advance the methodological analysis within the 'mobility effects' literature by (i) addressing, within the Sobel (1981) framework, the issue of measurement error; (ii) extending the model to take into account intra-generational, as well as extra-generational, mobility;
to construct a social mobility dataset for Northern Ireland which will permit further research on social mobility in at least three areas, (i) an examination of the changes in the Northern Ireland male mobility regime over the period 1973 to 1995. This will be based on a comparison with 1973 mobility data; (ii) a cross-national study of changes in the male mobility regime over the same period in comparison with the Republic of Ireland; (iii) the first examination of female mobility patterns In Northern Ireland.
Main Topics:

This dataset provides information on the following areas, in respect of the sampled respondents : demographics of the household; growing up (parents' occupation, schools attended, country of birth); education; current employment and employment history; partner's education and employment; religious activities; social attitudes and voting behaviour; cultural consumption; social networks.
Standard Measures
SEG, Registrar General's Social Class, Goldthorpe Classes, Hope-Goldthorpe Scale, and the International Socio-economic Index of Occupational Status were computed for all jobs held by the respondent during his/her career, partner's current job and respondent's parents' job when the respondent was aged 14 years. The Socialist/Laissez-faire Scale (Heath, Evans and Martin, 1993) was also computed for respondents.

Image: Snapshot from the Map of Community Views To understand different communities’ experiences during the COVID-19 pandemic, Deputy Mayor for Social Integration, Social Mobility and Community Engagement, Dr Debbie Weekes-Bernard and the GLA Community Engagement Team convened a series of virtual roundtable conversations and community meetings with groups and community leaders between April and September 2020. These conversations covered a range of complex issues. We heard about the overexposure of Black and Asian Minority Ethnic communities to the pandemic because they often work in frontline roles; the upsurge in hate crime against East and South East Asian Londoners; heightened need for domestic abuse support and better community language translations including specific dialects; the deep impact the virus has had on specific groups such as Somali, Bengali and Pakistani Londoners, particularly because of challenges with housing arrangements; the challenges for families around education for many groups including Gypsy, Roma, Traveller communities; concerns for LGBT+, Younger and Older Londoners; the impact of the Black Lives Matter movement; faith communities having to adapt their services and facing loss of income as a result, and much more. It was clear throughout that grassroots Faith and Community groups have played a crucial role meeting essential needs. The map of community views does not name specific groups but captures themes that can be addressed at policy level in close partnership with those affected, by recognising the strength of London’s community sector. 21 Roundtables and Community Meetings 250 Civil society and community groups reached

Data on the experiences of GCSE students in England during the coronavirus pandemic, by income-related deprivation. Estimates on experiences of remote learning, education recovery and catch-up activities and aspirations for the future, using the COVID Social Mobility and Opportunities (COSMO) study dataset.

This data was collected when participants joined the Co-Motion project. Participants were recruited to the project if they lived in one of the three case study areas, were aged 55 years of over and answered yes to experiencing at least one of nine pre-defined key life transitions in the preceding 12 months. The participants also took part in Phase 2: Postal Questionnaire Data and Phase 3: Telephone Interviews (where consent was given) and data can be linked using the unique ID number, "UK Data Code" found in the datasets.

Mobility, wellbeing and the built environment: Wellbeing in later life is linked to the maintenance of independence, physical mobility itself and the sense of being able to get about. Mobility is vital for accessing services, resources and facilities, for social participation, and for avoiding loneliness. Thus mobility has been described more broadly as 'engagement with the world'.

The design of the built environment has a key role to play in enabling - or frustrating - mobility. Thus appropriate design or redesign of the built environment can expand horizons and support wellbeing. However, this project focuses on complements or alternatives to physical design or redesign of the built environment. Design and adaptation are time and resource intensive. Many well-understood mobility barriers remain in place because of budget constraints. Design of the built environment is just one the determinants of mobility and wellbeing. Any one environment cannot meet all needs at once, and needs can vary even for an individual, as people pass through key physical and social transitions which may alter mobility and wellbeing.

Based on participatory research, this project aims to create a suite of options and tools which may be able to meet contrasting needs, support mobility and wellbeing, and do so more quickly and affordably than adapting the built environment.

The research aims to: 1) Explore mobility and wellbeing for older people going through critical but common life transitions; 2) Investigate and address variation and contradictions in needs of different groups of older people (and even for single individuals over time), and between different built environment agendas; and 3) To co-create practical tools which can act as complements or alternatives to redesign of the built environment.

After a foundation stage the work will commence with interviews with national experts and stakeholders. We will select three contrasting local areas in which to base the rest of the research, and interview c15 local stakeholders in each area. We will then start a pioneering quarterly tracking study of mobility and wellbeing, working with c120 older people in the three sites who are experiencing critical but common life transitions such as losing a driving license, losing a partner, or becoming a carer. These transitions are often seen as key points for deterioration in mobility and wellbeing, and as key points for support and intervention.

We will then work with a series of small groups of older people in workshops and co-design sessions, to explore the potential for interventions as alternatives and complements to promoting mobility and wellbeing via redesign. Each will involve a series of day-long meetings between researchers and older people, over about a year. One set of workshops will explore how well 'crowdsourcing' and Participatory Geographical Information Systems can add to and collate information about mobility wants and needs and barriers. Another will involve older people with varying interests in relation to the built environment, to explore conflicts and the potential for consensus on some issues. There will be co-design workshops with older people to explore mobile technologies based on SmartPhones, to help people avoid key blockages to mobility in particular areas. Other workshops will work with mobility scooter users, and manufacturers and those whose mobility may be threatened by scooters, to explore the feasibility of adapting scooters to reduce problems. The impact of participation itself will be tracked.

Project outputs will include: a project website, accessible annual interim and summative reports to project stakeholders and others, a summative report, articles for academic journals across team member disciplines, trade press articles for relevant professionals, potentially video or new media, a local stakeholder and older person conference and national 'Roadshow', as well as other dissemination events.