Dataset - Social problems in the UK : an introduction in the news

Sources distribution - Social problems in the UK : an introduction in the news

According to sports fans in the United Kingdom, the European Union was the biggest societal issue in the country in 2022. Specifically, ** percent of survey participants believed social challenges connected to the European Union to be the most important, whereas just ** percent were of the opinion that the monarchy or capital punishment were the most important issues in the UK that year.

Sections distribution - Social problems in the UK : an introduction in the news

During a survey held in early 2023, ** percent of responding marketing leaders in the United Kingdom (UK) said it was not appropriate for brands to take a stance on politically-charged issues. Meanwhile, ** percent of the respondents found that appropriate.

This statistic presents the results of a survey of adults in the United Kingdom which asked them how they thought about social media's impact on social and political issues. According to data published by Ipsos, ** percent of people in the United Kingdom thought that social media gave a voice to people who would not normally take part in debates.

Evolution, trends - Social problems in the UK : an introduction in the news

The economy was seen by 49 percent of people in the UK as one of the top three issues facing the country in June 2025. The ongoing cost of living crisis afflicting the UK, driven by high inflation, is still one of the main concerns of Britons. Immigration has generally been the second most important issue since the middle of 2024, just ahead of health, which was seen as the third-biggest issue in the most recent month. Labour's popularity continues to sink in 2025 Despite winning the 2024 general election with a strong majority, the new Labour government has had its share of struggles since coming to power. Shortly after taking office, the approval rating for Labour stood at -2 percent, but this fell throughout the second half of 2024, and by January 2025 had sunk to a new low of -47 percent. Although this was still higher than the previous government's last approval rating of -56 percent, it is nevertheless a severe review from the electorate. Among several decisions from the government, arguably the least popular was the government withdrawing winter fuel payments. This state benefit, previously paid to all pensioners, is now only paid to those on low incomes, with millions of pensioners not receiving this payment in winter 2024. Sunak's pledges fail to prevent defeat in 2024 With an election on the horizon, and the Labour Party consistently ahead in the polls, addressing voter concerns directly was one of the best chances the Conservatives had of staying in power in 2023. At the start of that year, Rishi Sunak attempted to do this by setting out his five pledges for the next twelve months; halve inflation, grow the economy, reduce national debt, cut NHS waiting times, and stop small boats. A year later, Sunak had at best only partial success in these aims. Although the inflation rate fell, economic growth was weak and even declined in the last two quarters of 2023, although it did return to growth in early 2024. National debt was only expected to fall in the mid to late 2020s, while the trend of increasing NHS waiting times did not reverse. Small boat crossings were down from 2022, but still higher than in 2021 or 2020. .

The English and Welsh Civil and Social Justice Panel Survey (CSJPS) collects data relating to people’s experiences of civil justice (or ‘justiciable’) problems and the strategies they used to resolve them.

The survey is a substantial development of the English and Welsh Civil and Social Justice Survey (CSJS), which was first conducted in 2001, then again in 2004, and on a continuous basis between 2006 and 2009. Respondents to the first wave of the CSJPS, conducted between June and October 2010, were asked about the experience of problems in each of 15 distinct civil justice problem categories: consumer; employment; neighbours; owned housing; rented housing; money; debt; welfare benefits; divorce; problems ancillary to relationship breakdown; domestic violence; education; care proceedings; personal injury, and clinical negligence.

For up to three problems (selected at random, if more than three problems had been experienced), respondents were asked about disputants, problem resolution strategies, advisers consulted, formal dispute resolution processes, how and when problems concluded, the causes and consequences of problems, understanding of rights, and regrets. For one (random) problem, respondents were also asked for detailed information about the steps they had taken to resolve it.

Extensive Demographic and household details were also collected. The fieldwork for the second wave of the CSJPS was carried from winter 2011 (18 months after the Wave 1). The survey was broadly similar to Wave 1. Ongoing problems at the time of the wave 1 interview were also revisited at wave 2, with further details set out in the technical report and questionnaire.

This dataset is about books. It has 2 rows and is filtered where the book subjects is Social problems-England-Fiction. It features 9 columns including author, publication date, language, and book publisher.

Sentiment polarity - Social problems in the UK : an introduction in the news

Anonymised transcripts from ESRC Postdoctoral Fellowship examining recordings of telephone calls to a UK housing charity helpline.
Contextual metadata about each interview is included in the relevant file.

This survey, the first in an annual series, is designed to monitor trends in a wide range of social attitudes in Great Britain. The British Social Attitudes Survey (BSA) is similar in purpose to the General Social Survey carried out by the National Opinion Research Center (NORC) in the United States. The BSA questionnaire had two parts, one administered by an interviewer and the other completed by the respondent. This survey contained questions on political orientation, including attitudes toward the parties, likely voting behavior in the next British General Election, political tolerance, and relations with other nations. Other topics include beliefs and expectations concerning both national and personal economic conditions, attitudes toward government spending and programs, social problems such as crime and racial prejudice, and attitudes toward marriage and sexual mores. Additional demographic data gathered included age, gender, education, occupation, household income, marital status, social class, and religious and political affiliations.

This dataset of historical poor law cases was created as part of a project aiming to assess the implications of the introduction of Artificial Intelligence (AI) into legal systems in Japan and the United Kingdom. The project was jointly funded by the UK’s Economic and Social Research Council, part of UKRI, and the Japanese Society and Technology Agency (JST), and involved collaboration between Cambridge University (the Centre for Business Research, Department of Computer Science and Faculty of Law) and Hitotsubashi University, Tokyo (the Graduate Schools of Law and Business Administration). As part of the project, a dataset of historic poor law cases was created to facilitate the analysis of legal texts using natural language processing methods. The dataset contains judgments of cases which have been annotated to facilitate computational analysis. Specifically, they make it possible to see how legal terms have evolved over time in the area of disputes over the law governing settlement by hiring.

A World Economic Forum meeting at Davos 2019 heralded the dawn of 'Society 5.0' in Japan. Its goal: creating a 'human-centred society that balances economic advancement with the resolution of social problems by a system that highly integrates cyberspace and physical space.' Using Artificial Intelligence (AI), robotics and data, 'Society 5.0' proposes to '...enable the provision of only those products and services that are needed to the people that need them at the time they are needed, thereby optimizing the entire social and organizational system.' The Japanese government accepts that realising this vision 'will not be without its difficulties,' but intends 'to face them head-on with the aim of being the first in the world as a country facing challenging issues to present a model future society.' The UK government is similarly committed to investing in AI and likewise views the AI as central to engineering a more profitable economy and prosperous society.

This vision is, however, starting to crystallise in the rhetoric of LegalTech developers who have the data-intensive-and thus target-rich-environment of law in their sights. Buoyed by investment and claims of superior decision-making capabilities over human lawyers and judges, LegalTech is now being deputised to usher in a new era of 'smart' law built on AI and Big Data. While there are a number of bold claims made about the capabilities of these technologies, comparatively little attention has been directed to more fundamental questions about how we might assess the feasibility of using them to replicate core aspects of legal process, and ensuring the public has a meaningful say in the development and implementation.

This innovative and timely research project intends to approach these questions from a number of vectors. At a theoretical level, we consider the likely consequences of this step using a Horizon Scanning methodology developed in collaboration with our Japanese partners and an innovative systemic-evolutionary model of law. Many aspects of legal reasoning have algorithmic features which could lend themselves to automation. However, an evolutionary perspective also points to features of legal reasoning which are inconsistent with ML: including the reflexivity of legal knowledge and the incompleteness of legal rules at the point where they encounter the 'chaotic' and unstructured data generated by other social sub-systems. We will test our theory by developing a hierarchical model (or ontology), derived from our legal expertise and public available datasets, for classifying employment relationships under UK law. This will let us probe the extent to which legal reasoning can be modelled using less computational-intensive methods such as Markov Models and Monte Carlo Trees.

Building upon these theoretical innovations, we will then turn our attention from modelling a legal domain using historical data to exploring whether the outcome of legal cases can be reliably predicted using various technique for optimising datasets. For this we will use a data set comprised of 24,179 cases from the High Court of England and Wales. This will allow us to harness Natural Language Processing (NLP) techniques such as named entity recognition (to identify relevant parties) and sentiment analysis (to analyse opinions and determine the disposition of a party) in addition to identifying the main legal and factual points of the dispute, remedies, costs, and trial durations. By trailing various predictive heuristics and ML techniques against this dataset we hope to develop a more granular understanding as to the feasibility of predicting dispute outcomes and insight to what factors are relevant for legal decision-making. This will allow us to then undertake a comparative analysis with the results of existing studies and shed light on the legal contexts and questions where AI can and cannot be used to produce accurate and repeatable results.

This report presents findings from the third (wave 3) in a series of follow up reports to the 2017 Mental Health of Children and Young People (MHCYP) survey, conducted in 2022. The sample includes 2,866 of the children and young people who took part in the MHCYP 2017 survey. The mental health of children and young people aged 7 to 24 years living in England in 2022 is examined, as well as their household circumstances, and their experiences of education, employment and services and of life in their families and communities. Comparisons are made with 2017, 2020 (wave 1) and 2021 (wave 2), where possible, to monitor changes over time.

Social tech ventures, which combine technological innovation and commercial trade to address social challenges, hold immense promise for creating scalable, cost-effective solutions to pressing global social problems. Despite their potential, research on social tech ventures remains nascent, particularly concerning how these ventures develop, scale, pivot, and manage mission drift. Existing studies primarily focus on non-tech social ventures or commercial ventures, leaving critical gaps in understanding the unique dynamics and developmental processes of social tech ventures.

This project explored how social tech venturing unfolds. It focused on how social tech firms develop their mission, as well as how they develop their commercial and social elements as they evolve. It aimed to uncover how they adapt over time and when the market environment changes.

Due to ethical concerns the data cannot be shared, but the interview protocols are made available.

This data was generated as part of an 18 month ESRC funded project,as part of UKRI’s rapid response to COVID-19. The project examines how UK period poverty initiatives mitigated Covid-19 challenges in light of lockdown measures and closure of services, and how they continued to meet the needs of those experiencing period poverty across the UK. Applied social science research methodologies were utilised to collect and analyse data as this project, about the Covid-19 pandemic, was undertaken during an ongoing ‘real world’ pandemic. Data collection was divided into two phases. Phase 1 (October 2020 – February 2021) collected data from period poverty organisations in the UK using semi-structured interviews and an online survey to develop an in-depth understanding of how period poverty organisations were responding to and navigating the Covid-19 Pandemic. Having collected and analysed this data, phase 2 (June – September 2021) used an online survey to collect data from people experiencing period poverty in order to better understand their lived experiences during the pandemic. Our dataset comprises of phase 1 interview transcripts and online survey responses, and phase 2 online survey responses.

Period poverty refers not only to economic hardship with accessing period products, but also to a poverty of education, resources, rights and freedom from stigma for girls and menstruators (1). Since March 2020, and the introduction of lockdown/social distancing measures as a result of the Covid-19 pandemic, more than 1 of every 10 girls (aged 14-21) cannot afford period products and instead must use makeshift products (toilet roll, socks/other fabric, newspaper/paper). Nearly a quarter (22%) of those who can afford products struggle to access them, mostly because they cannot find them in the shops, or because their usual source/s is low on products/closed (2).

Community /non-profit initiatives face new challenges related to Covid-19 lockdown measures as they strive to continue to support those experiencing period poverty. Challenges include accessing stocks of period products, distribution of products given lockdown restrictions, availability of staff/volunteer assistance and the emergence of 'new' vulnerable groups. There is an urgent need to capture how initiatives are adapting to challenges, to continue to support the needs of those experiencing period poverty during the pandemic. This data is crucial to informing current practice, shaping policy, developing strategies within the ongoing crisis and any future crises, and ensuring women and girls' voices are centralised.

The project builds upon existing limited knowledge by providing insight into how UK based initiatives and projects are mitigating challenges linked to Covid-19, by examining how they are continuing to meet the needs of those experiencing period poverty and identifying any gaps in provision.

1. Montgomery P., et al., 2016. Menstruation and the Cycle of Poverty. PLoS ONE 11(12): e0166122.
2. Plan International UK, 2020. The State of Girls' Rights in the UK: Early insights into the impact of the coronavirus pandemic on girls. London: Plan International UK

The Health Survey for England series was designed to monitor trends in the nation's health, to estimate the proportion of people in England who have specified health conditions, and to estimate the prevalence of risk factors associated with these conditions. The surveys provide regular information that cannot be obtained from other sources on a range of aspects concerning the public's health. The surveys have been carried out since 1994 by the Joint Health Surveys Unit of NatCen Social Research and the Research Department of Epidemiology and Public Health at UCL. Each survey in the series includes core questions and measurements (such as blood pressure, height and weight, and analysis of blood and saliva samples), as well as modules of questions on topics that vary from year to year. New topics this year include hearing and mental health. The achieved sample for the 2014 survey was 8,077 adults (aged 16 and over) and 2,003 children (aged 0-15). This year tables are in excel spreadsheets and the way the findings are presented in the report and summary has changed. We would very much like to hear readers' views about these changes. Please tell us via the short reader survey at the bottom of this page in Related links. Please note this release was updated on 15 January 2016 to add chapter 2 - Mental Health Problems and chapter 3 - Attitudes towards Mental Illness and their associated excel tables and to update the Summary of Key Findings.

The Legal Problem and Resolution Survey, 2014-2015 (LPRS), builds on the English and Welsh Civil and Social Justice Survey (CSJS) and Civil and Social Justice Panel Survey (CSJPS), a series of surveys conducted between 2001 and 2012. As a number of significant reforms have been made to the civil, family and administrative justice systems recently, there was a need to adapt and develop previous versions of the questionnaire to ensure it more closely met current policy objectives.

LPRS collected information about the prevalence of civil, administrative and family legal problems, the characteristics of these problems and the people experiencing them, and the problem outcomes. The survey also covered the help and advice people obtained to resolve problems and the resolution strategies that they used.

Further information about this survey can be found on gov.uk Publications webpage.