According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.

In a survey conducted in July 2021 about the whether respondents think that diversity and inclusion in companies and institutions in the United Kingdom had improved or worsened in the last six months, **** percent of the respondents said that it had improved a little, whereas **** percent of respondents said that it had got a little worse.

In a survey conducted in July 2021 regarding the ways in which respondents personally supported diversity and inclusion in the workplace in the United Kingdom, just over half of respondents said that they had talked with friends or family about these matters, while **** percent said that they posted about it publicly on a social media platform.

According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.

The reporting rate for staff declaring their ethnicity, gender etc. Updated: monthly.

The Area Level Index of Age Diversity (ALIAD) is based on the Simpson's Index of Diversity. It is commonly used in ecological studies to quantify the biodiversity of a habitat as it takes into account both the richness, i.e. the number of species present, and the evenness, i.e. the abundance of each species, within an environment. As species richness and evenness increase, so diversity increases. The index represents the probability that two randomly selected individuals will belong to different groups. It ranges from 0 and 100, with higher values representing greater diversity. ALIAD was computed for each Lower Super Output Area (LSOA) in England and Wales (E&W), each Data Zone (DZ) in Scotland and each Super Output Area (SOA) in Northern Ireland from 2002 to 2019. It is based on the mid-year population estimates (MYPE) for each area for each year. This is information is freely available in accordance with version 3.0 of the Open Government Licence. However, the different national statistical agencies compute MYPE for different age groups. In England and Wales estimates are provided for single-year age groups, i.e. the number of people aged 0, 1, 2, 3, etc. In Scotland estimates are provided for quinary age groups, i.e. the number of people aged 0-4, 5-9, 10-14, etc. In Northern Ireland (NI) estimates are provided for four larger age groups, i.e. 0-15, 16-39, 40-64 and 65+. It was decided to match the age groups to the NI classification as i) this would provide the greatest geographical coverage, ii) the estimates ought to be more robust and iii) in discussions with policy and practice stakeholders these age groups were seen as more meaningful than single-year or quinary age groups. An exact match was possible between the E&W and NI age groups. However, because of the use of quinary age groups it is not possible to get an exact match for all age groups in Scotland. Hence, the age groups used on Scotland are 0-14, 15-39, 40-64 and 65+. The final dataset contains the computed ALIAD values for each of the 34,753 LSOAs, the 6,976 DZs and the 890 SOAs from 2002-2019. ALIAD has a range of 0-100. On this scale 0 would represent total age concentration, i.e. every member of the area is in the same age group, and 100 would represent complete age diversity within the area.There is evidence that Britain is becoming more and more generationally divided. A major part of this is that the places where we live have become increasingly 'age segregated'. This means younger people tend to live in places where there are more younger people and older people tend to live in places where there are more older people. Deep generational divisions can have implications for social cohesion and effective societal functioning. Policy makers are concerned that this could have negative health, economic, social and political costs. Indeed, a recent report by the Resolution Foundation estimated that age-segregation could cost the UK economy £6 billion per year. However, there is currently no research in Britain that has been able to directly test whether living in areas with a greater mix of ages has an impact on people. By linking information on the number of people in different age groups at the local level with information from a long running survey, our project will be the first to do this. We will create a new measure, called the 'area level index of age diversity', for all the residential areas in Great Britain (these are called Lower Super Output Areas in England and Wales and Data Zones in Scotland). Unlike existing measures which tend to focus just on younger versus older adults, this new measure will use information from people of all ages to get a better idea of the mix of age groups in an area. The first thing we intend to do with this information is to produce a series of maps of Britain to show which local areas are more or less age diverse. This information will be very useful for local government, councils, city planners and the like. Once we have done this, we will then link our new measure of age diversity to information on around 50,000 people living in Britain who have been part of a long running study (called the UK Household Longitudinal Survey). This will enable us to see whether living in areas that have people from a wide (or narrow) range of age groups impacts on people's health (e.g. whether the person has an illness or chronic condition), well-being (e.g. loneliness), civic participation (e.g. whether someone volunteers or not), and neighbourhood quality (e.g. whether people trust their neighbours). Our findings will provide a much needed evidence base on the extent of local area level age diversity in Britain and what effect (if any) this has on people's lives. ALIAD was computed for each Lower Super Output Area (LSOA) in England and Wales (E&W), each Data Zone (DZ) in Scotland and each Super Output Area (SOA) in Northern Ireland from 2002 to 2019. It is based on the mid-year population estimates (MYPE) for each area for each year.

On average, approximately 35.5 percent of the leadership positions at Standard Chartered were held by women in 2023. On the board, 38 percent of the directors were women, and a similar gender distribution could be seen in the management team. At the senior leadership level, the share of women was slightly lower, at 32.5 percent. Between 2016 and 2023, the share of women on the board as well as in senior leadership increased, while in the management team it decreased notably.

On 31 March 2024, 91.6% of police officers were White, and 8.4% were from Asian, Black, Mixed, and Other ethnic backgrounds.

Participation and success rates of apprentices & adult learners by ethnicity, gender, disabilities and age.

This project is the first census of all local councillors in all four constitutive nations of the UK, conducted in 2018 and 2019. The local level, so important to our democracy, is too often ignored, and political representation is predominantly studied at the national level. The particular importance of local level to ethnic representation cannot be overstated as it is often the first step in politics and political careers for many minority politicians, and a first line of contact for minority individuals and communities in need of help. This project seeks to fill this research gap and to put local representation at the heart of studying how ethnic minorities are politically represented in Britain. Our research design was developed to study the experiences of ethnic minority local councillors from visibly racialised backgrounds of both genders, to further our understandings of the mechanisms that underpin representational inequalities. We collected the ethnicity, gender and political party of every local councillor in the UK by referring to council websites. We sought to sample our interviewees to reflect a range of non-white backgrounds and political experience as well as gender balance. Interviewees were asked about how they became involved in local politics, their views on the extent of demand for greater diversity in local government and their experiences of running for selection and election for local government as well as serving as a local councillor. The collection consists of interview transcripts with 95 ethnic minority local councillors, candidates and activists, or white British councillors in local government leadership positions.

As of 30 September 2024, Black people made up 15.2% of social workers for children and families, and 4.6% of the working age population.

This project is the first census of all local councillors in all four constitutive nations of the UK, conducted in 2018 and 2019. The local level, so important to our democracy, is too often ignored, and political representation is predominantly studied at the national level. The particular importance of local level to ethnic representation cannot be overstated as it is often the first step in politics and political careers for many minority politicians, and a first line of contact for minority individuals and communities in need of help. This project seeks to fill this research gap and to put local representation at the heart of studying how ethnic minorities are politically represented in Britain. Our research design was developed to study the experiences of ethnic minority local councillors from visibly racialised backgrounds of both genders, to further our understandings of the mechanisms that underpin representational inequalities. We collected the ethnicity, gender and political party of every local councillor in the UK by referring to council websites. We sought to sample our interviewees to reflect a range of non-white backgrounds and political experience as well as gender balance. Interviewees were asked about how they became involved in local politics, their views on the extent of demand for greater diversity in local government and their experiences of running for selection and election for local government as well as serving as a local councillor. The collection consists of interview transcripts with 95 ethnic minority local councillors, candidates and activists, or white British councillors in local government leadership positions.Understandings of ethnic inequalities in the UK have developed substantially as a result of the work of The Centre on Dynamics of Ethnicity (CoDE). CoDE has successfully carried out an innovative programme of research, pursued challenging scientific objectives, and worked closely with a range of non-academic partners to impact on policy debates and development. In a rapidly evolving political and policy context, we propose a further, ambitious programme of work that takes us in new directions with a distinct focus. We will move beyond nuanced description to understanding processes and causes of ethnic inequalities, and build directly on our established experience in interdisciplinary and mixed methods working. In addition, we will use a co-production approach, working with a range of partners, including key public institutions such as the BBC, universities, political parties, ethnic minority NGOs, activists, and individuals, in order to frame and carry out our research in ways that will maximise our societal impact and lead to meaningful change. Our overarching objectives are to: -Understand how ethnic inequalities develop in a range of interconnected domains -Examine how these processes relate to and are shaped by other social categories, such as gender, class, religion and generation -Understand how ethnic inequalities take shape, and are embedded, in institutional spaces and practices -Work closely with policy and practice partners to meaningfully address enduring ethnic inequalities -Pursue methodological developments with interdisciplinary mixed methods and co-production at their core -Achieve ongoing high quality international academic impact Through a research plan divided into four work packages, we will examine ethnic inequalities in (1) higher education, (2) cultural production and consumption, (3) politics, representation and political parties and (4) pursue policy and institutional impact with our work in these areas. Alongside this, we are also conducting a programme of work on severe mental illness. These work packages will be organised around our ambition to understand, explain and impact on ethnic inequalities through a focus on institutional production of and responses to ethnic inequalities. At the core of our methodological approach is interdisciplinary and mixed methods working. Our quantitative work will be predominantly secondary data analysis, making the best use of the wide range of resources in the UK (e.g. Understanding Society, Destination of Leavers of Higher Education Survey, British Election Study, ONS Longitudinal Studies). Our qualitative work will be based around ethnographic approaches that are attentive to the ways in which social processes play out differently in different sites and institutions. We are informed especially by the approach of institutional ethnography which prioritises an attention to the lived, everyday experience of inequality, but aims to clarify the wider social relations in which such experiences are embedded and by which they are shaped. Thus institutional ethnographies will be developed which begin with exploring the experience of those directly involved in institutional settings as a route to understanding how structures and practices of institutions shape individuals' experiences and practices. Throughout our work we will integrate and mobilise research evidence to engage with a full range of partners in order to influence policy and practice development, public understanding and institutional practice. As well as having academic impact (journal articles, conferences, seminars, newsletters), our findings will be communicated directly to policy and advocacy organisations through a combination of well developed (blogs, Twitter, policy briefings) and emerging (podcasts and live streaming, museum and art exhibitions, online portal for individual narratives) forms of dissemination, and we will work directly with these organisations to achieve change. We hand coded all councillors’ ethnicity based on pictures included on the relevant council website, in cases where we lacked pictures or pictures were not definitive, we performed an online search of local media and councillors’ own professional websites. Finally, we used OriginsInfo software to auto-code the names of all councillors who we hand coded as ethnic minority, or unknown. OriginsInfo operates a proprietary algorithm to compare personal and family names with the ethnic, religious and cultural origin of 5,000,000 names from around the world. OriginsInfo matches forenames and surnames against a stored database of names and classifies them according to their most likely cultural origins by linguistic and religious affiliations. We used semi-structured interviews in order to gain insight into the ways in which ethnic minority councillors make sense of their social locations in their political environments, routes to office including selection and election processes, their experiences of serving on local councils and engaging with the constituents they represent. We sought to sample our interviewees to reflect a range of ethnic non-white backgrounds and political experience as well as gender balance. We conducted 94 semi-structured interviews, the majority of which were with British ethnic minority local councillors in England. Five of our female interviewees were of ethnic minority background who had been candidates for local council or parliament, rather than councillors. We also interviewed two local women activists of minority background working on political representation of women of colour.

This dataset tracks annual diversity score from 2014 to 2023 for Uk Early Childhood Lab vs. Kentucky and Fayette County School District

Board gender diversity varied among the UK's largest banks in 2025. Women comprised an average of **** percent of board directors at the ten largest banks. Three banks - HSBC, Virgin Money, and NatWest Group - had female-majority boards. Metro Bank had the lowest female representation, with women holding **** percent of board seats.

The project generated several key findings, in line with the original project themes: 1) The project demonstrates that ethnic diversity alone does not appear to be a key driver of Brexit support, despite much of the public/political narrative in the area. Instead, we demonstrate that it is patterns of segregation which determine when diversity drove Brexit support. Thus, how increasing ethnic diversity of society appears to trigger tensions is in more segregated forms. Where diverse communities are integrated relations actually appear to improve. 2) The project uniquely demonstrates that residential segregation is a significant negative driver of mental health among ethnic minority groups in the UK. Mental health policy in the UK acknowledges that ethnic minorities often suffer worse mental health than their majority group counterparts. This work demonstrates that community characteristics need to be considered in mental health policy; in particular, how patterns of residential segregation are a key determinant of minority group mental health. 3) We demonstrate that, as expected, the ethnic mix of a community is a strong predictor of patterns of interethnic harassment. However, we also demonstrate that, even controlling for this, how residentially segregated an area is a stronger and consistent predictor of greater harassment. This will help societies better identify potential drivers of harassment and areas where focus should be on minimising hate crime. 4) The project demonstrates the key role sites of youth engagement can play in building positive intergroup relations among young people. In particular, their efficacy for overcoming key obstacles to integration such as residential segregation. The project has generated several other impacts related to the project themes of social capital/social cohesion and mental health, as relates to the Covid-19 pandemic: 1) The paper explores the potential impact of the Covid-19 pandemic on people’s perceptions of cohesion in their local communities; particularly for vulnerable groups/communities, such as ethnic minorities or those living in highly deprived neighbourhoods. To this end, we examine both trends over time in overall levels of cohesion as well as patterns of positive and negative changes experienced by individuals using nationally representative data from Understanding Society Study. We test whether rates of positive-/negative-change in cohesion over the pandemic-period differed across socio-demographic groups and neighbourhood characteristics. These trends are then compared to patterns of positive-/negative-change over time experienced in earlier periods to test whether the pandemic was uniquely harmful. We show that the overall levels of social cohesion are lower in June 2020 compared to all of the examined pre-pandemic periods. The decline of perceived-cohesion is particularly high in the most deprived communities, among certain ethnic minority groups and among the lower-skilled. Our findings suggest that the pandemic put higher strain on social-resources among vulnerable groups and communities, who also experienced more negative changes in other areas of life. 2) The study examines the impact of coronavirus-related restrictions on mental health among American adults, and how this relationship varies as a function of time and two measures of vulnerability (preexisting physical symptoms and job insecurity). We draw on data from two waves of Corona Impact Survey, which were fielded in late April and early of May 2020. Multilevel models were used to analyze the hierarchically nested data. Experiencing coronavirus disease-2019 restrictions significantly raise mental distress. This association is stronger for individuals with preexisting health conditions and those who worry about job prospects. These findings hold with the inclusion of region-wave covariates (number of deaths, wave dummy and aggregate measure of restrictions). Finally, there is a cross-level interaction: the restriction-distress connection is more pronounced in the second wave of data. Our research indicates that people who are more physically and/or financially vulnerable suffer more from the imposed restrictions, i.e. ‘social isolation’. The mental health impact of coronavirus pandemic is not constant but conditional on the level of vulnerability.