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Participation Survey, 2024-2025
No full textAbstract copyright UK Data Service and data collection copyright owner.The Participation Survey is a continuous push-to-web survey of adults aged 16 and over in England. It serves as a successor to the Taking Part survey, which ran for 16 years as a continuous face to face survey. Paper surveys are available for those not digitally engaged. Fieldwork started in October 2021 and it is envisaged that the survey will be a key evidence source for Department for Digital, Culture, Media and Sport (DCMS) and its sectors by providing statistically representative national estimates of adult engagement with the DCMS sectors. The survey’s main objectives are to:
Provide a central, reliable evidence source that can be used to analyse cultural, digital, and sporting engagement, providing a clear picture of why people do or do not engage.
Provide data at a county level to meet user needs, including providing evidence for the levelling up agenda.
Underpin further research on driving engagement and the value and benefits of engagement.Further information on the survey can be found on the gov.uk Participation Survey webpage.For 2024-2025 annual data the fieldwork period was from 10th April 2024 - 2nd April 2025. Participants in the survey are randomly selected from addresses from the Post Office’s list of addresses in England. This ensures results reflect the experiences and views of the whole population.Main Topics:The Participation Survey collects data on engagement in:
the arts
libraries
heritage
museums and galleries
tourism
major cultural events
major sporting events
sport
gambling
digital sectors
The survey includes information on frequency of participation, reasons for participating, barriers to participation and attitudes to the sectors.
Information is also gathered on demographics (e.g. age, education), and related areas including wellbeing, loneliness, and use of digital technology.</p
Egyptian Parliamentary Speeches, 1866-1882
No full textThe dataset forms part of a research program by Mohamed Saleh titled "Intra-Elite Conflict and the Reluctant Democratization of the Middle East and North Africa," funded by the British Academy Mid-Career Fellowship in 2024/25. This research program aims at developing a new historical political economy of the Middle East that explains the economic roots of authoritarianism in the region. It theoretically and empirically investigates how demands for democratization could emerge from intra-elite conflicts in an agrarian economy, despite the lack of an industrial bourgeoisie, and how elite politics shift with colonialism and postcolonial regimes. While elite conflicts can lead to democratization, they can alternatively result in autocracy. Furthermore, colonialism and postcolonial military coups could curtail these developments leading to episodes of democratic opening and authoritarian backsliding. The research program tests this by examining elite politics in Egypt, using a novel database on parliament members from 1824 to 2020, and parliamentary speeches in 1866-1882 and 1924-1952.
This dataset covers the universe of speeches made in the Egyptian parliament from 1866 to 1882. The dataset was constructed by the authors from the original Arabic-language parliamentary minutes that were published in four volumes by the National Archives of Egypt
Trade Union Use of Digital Communications Technology: Interview data, 2023-2024
No full textThis research was designed to investigate the ways in which trade unions use digital communications technology to communicate with and amongst their members, and at how digitally-enabled communications fit in with wider campaigning and organising practices, including industrial action such as strikes. The use of digital communications technologies in established and mainstream trade union settings has been (and, to date, continues to be) significantly under-researched. The data in this collection comprises transcripts of a series of interviews from a case study of the National Education Union (NEU). There are two groups of interview transcripts. One comes from individual interviews with five full-time officers (FTOs) and staff at NEU head office (HQ), who work in and/or have responsibility for national digital communications and associated data-analysis and data-management functions. The second group comes from group interviews (GIs) carried out with seven groups of local union reps and branch officers from different parts of England. We focussed on England because the management of schools is now different in each of the four devolved nations of the UK, and England has the most fragmented system, which provides the greatest challenges to the NEU's traditional organising model. Sites for GIs were selected for geographical spread (three in London, one in the North of England and one in the South), plus we selected for different school governance models; specifically, we wanted to interview reps from Multi-Academy Trusts, a relatively new type of school that presents novel challenges for teaching unions. The selection of sites for rep interviews was also significantly influenced by access considerations, being wholly dependent on arrangements made by NEU FTOs and branch officers, as well as the willingness of reps to give up their time during a period of intense union activity – notably, a national pay campaign, including strikes, which followed a period of significant stress and workplace conflict over school closures and related issues during the COVID-19 pandemic – in addition to the usual heavy workloads associated with classroom teaching. As a result, the GIs carried out were varied in terms of the number and composition of reps present (varying between two and 13 participants), and were always pressed for time (which significantly restricted the gathering of demographic data). The data is therefore somewhat patchy and unrepresentative, but nevertheless generated rich insights and achieved a reasonable degree of saturation on important issues. Key findings include overlapping but sometimes different approaches between NEU HQ and local reps, as well as sophisticated understandings by reps of the use of different digital communications technologies for different purposes, the relationship between technological and in-person communications, and the place of each in wider union campaigning and activism.The Digital Futures at Work Research Centre (Dig.IT) will establish itself as an essential resource for those wanting to understand how new digital technologies are profoundly reshaping the world of work. Digitalisation is a topical feature of contemporary debate. For evangelists, technology offers new opportunities for those seeking work and increased flexibility and autonomy for those in work. More pessimistic visions, in contrast, see a future where jobs are either destroyed by robots or degraded through increasingly precarious contracts and computerised monitoring. Take Uber as an example: the company claims it is creating opportunities for self-employed entrepreneurs; while workers' groups increasingly challenge such claims through legal means to improve their rights at work.
While such positive and pessimistic scenarios abound of an increasingly fragmented, digitalised and flexible transformation of work across the globe, theoretical understanding of contemporary developments remains underdeveloped and systematic empirical analyses are lacking. We know, for example, that employers and governments are struggling to cope with and understand the pace and consequences of digital change, while individuals face new uncertainties over how to become and stay 'connected' in turbulent labour markets. Yet, we have no real understanding of what it means to be a 'connected worker' in an increasing 'connected' economy. Drawing resources from different academic fields of study, Dig.IT will provide an empirically innovative and international broad body of knowledge that will offer authoritative insights into the impact of digitalisation on the future of work.
The Dig.IT centre will be jointly led by the Universities of Sussex and Leeds, supported by leading experts from Aberdeen, Cambridge, Manchester and Monash Universities. Its core research programme will cover four broad-ranging research themes. Theme one will set the conceptual and quantitative base for the centre's activities. Theme two involves a large-scale survey of Employers' Digital Practices at Work. Theme three involves qualitative research on employers' and employees' experiences of digitalisation at work across 4 sectors (Creative industries, Business Services, Consumer Services, Public Services). Theme 4 examines how the disconnected attempt to reconnect, through Public Employment Services, the growth of new types of self-employment, platform work and workers' responses to building new forms of voice and representation in an international context. Specific projects include:
1. The Impact of Digitalisation on Work and Employment
-Conceptualising digital futures, historically, regionally and internationally
-Comparative regulation of digital employment
- Mapping regional and international trends of digital technology and work
2. Employers' Digital Practices at Work Survey
3. Employers' and employees' experiences of digital work across sectors
-Changing management processes and practices
-Workers' experiences of digital transformation
4. Reconnecting the disconnected: new channels of voice and representation
- displaced workers, job search and the public employment service
- self-employment, interest representation and voice
Dig.IT will establish a Data Observatory on digital futures at work to promote our findings through an interactive website, report on a series of methodological seminars and new experimental methods and deliver extensive outreach activities. It will act as a one-platform library of resources at the forefront of research on digital work and will establish itself as a focal point for decision-makers across the policy spectrum, connecting with industrial strategy, employment and welfare policy. It will also manage an Innovation Fund designed to fund novel research ideas, from across the academic community as they emerge over the life course of the centre.</p
Annual Population Survey, July 2024 - June 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.Occupation data for 2021 and 2022The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022APS Well-Being DatasetsFrom 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.APS disability variablesOver time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage. End User Licence and Secure Access APS dataUsers should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to:
age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
nationality and country of origin
geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
health: including main health problem, and current and past health problems
education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
system variables: including week number when interview took place and number of households at address
The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.Main Topics:Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS.<br
Community Acceptance of Nature-based Solutions for Coastal Flood Risk Management - Survey and Focus Group Data, 2022-2023
No full textThis study aimed to understand what factors influence community acceptance of nature-based solutions (NbS) for coastal flood risk management. Coastal communities are already experiencing the impacts of sea level rise and more frequent storm events on property, infrastructure and livelihoods and accelerated coastal erosion. Various adaptation approaches exist, varying from hard engineering solutions to NbS, but whether these strategies are implemented often depends on social acceptance by local communities. This study is part of a large interdisciplinary NERC-ESRC funded project Resilient Coasts: Optimising Co-Benefit Solutions (Co-Opt) 2021-2025.
To pinpoint what influences community acceptance of NbS for flood risk management in the UK, we employed an explanatory sequential mixed methods research design. We also used a case study approach focusing on four sites in the UK - St Andrews (Scotland), Airth (Scotland), Hesketh Bank (England), and Pensarn (Wales). The sites were selected to demonstrate a range of socio-demographic characteristics and baseline conditions, with a selection of coastal management solutions varying from “grey” to “green” that are already in place or could be implemented in the future.
Firstly, we operationalised a questionnaire survey to identify values, norms and perceived trust that influence social acceptability in each case study site. The survey respondents were randomly selected from AddressBase Core product by the Ordnance Survey for each case study site and conducted from May 2022 to October 2023. A postcard introducing the survey with a QR code and a link to a Qualtrics online survey was sent first, followed by a printed copy with a pre-paid envelope two weeks later. A final reminder postcard was with a QR code and link to a Qualtrics online survey was sent 2-4 weeks later. In total 328 complete and valid responses were received (13.40% response rate).
Secondly, focus group discussions were conducted to elaborate on the initial quantitative findings. In total, seven focus groups were hosted in the case study sites one in St Andrews and two in the rest of the three sites Airth, Hesketh Bank and Pensarn. Participants included interested and/or affected groups such as landowners, farmers, business owners, local councillors and representatives from local risk management authorities and environmental organisations.
The mixed methods approach worked via quantitative data suggesting the strength and patterns of relationships, and qualitative data suggesting the nature and mechanisms of causal relationships.
The results show that community acceptance is place-based and is influenced by the context, with certain factors being site specific. The study highlights the complexity of community acceptance of NbS for coastal flood risk management, indicating that local perceptions are influenced by a combination individual factors such as trust; the characteristics of schemes; and they ways in which governance systems interact with local communities.Sea and society interact most strongly at the coast where communities both benefit from and are threatened by the marine environment. Coastal flooding was the second highest risk after pandemic flu on the UK government's risk register in 2017. Over 1.8 million homes are at risk of coastal flooding and erosion in England alone. Extreme events already have very significant impacts at the coast, with the damage due to coastal flooding during the winter 2013/14 in excess of £500 million, and direct economic impacts exceeding £260 million per year on average. Coastal hazards will be increasing over the next century primarily driven by unavoidable sea level rise. At the same time, the UK is committed to reach net zero carbon emissions by 2050. It is therefore essential to ensure that UK coasts are managed so that coastal protection is resilient to future climate and the net zero ambition is achieved. Protecting the coast by maintaining hard 'grey' defences in all locations currently planned is unlikely to be cost-effective. Sustainable coastal management and adaptation will therefore require a broader range of actions, and greater use of softer 'green' solutions that work with nature, are multifunctional, and can deliver additional benefits.
Examples already exist and include managed realignment, restoration of coastal habitats, and sand mega-nourishments. However, the uptake of green solutions remains patchy. According to the Committee on Climate Change, the uptake of managed realignment is five times too slow to meet the stated 2030 target. Reasons are complex and span the whole human-environment system. Nature-based solutions often lack support from public opinion and meet social resistance. Despite removing long-term commitment to hard defences, the economic justification for green approaches remains uncertain due to high upfront costs, difficulty in valuing the multiple co-benefits offered, and uncertainties inherent to future environmental and socio-economic projections. The frameworks used to support present day coastal management and policy making (e.g. Shoreline Management Plans) do not provide comprehensive and consistent approaches to resolve these issues. Consequences are that the effectiveness of these policy approaches is reduced. Delivering sustainable management of UK coasts will therefore require new frameworks that embrace the whole complex human-environment system and provide thorough scientific underpinning to determine how different value systems interact with decision making, how climate change will impact coastal ecosystem services, and how decision support tools can combine multiple uncertainties.
Co-Opt will deliver a new integrated and interdisciplinary system-based framework that will effectively support the required transition from hard 'grey' defences to softer 'green' solutions in coastal and shoreline management. This framework will combine for the first time a conceptual representation of the complex coastal socio-ecological system, quantitative valuation of coastal ecosystem services under a changing climate, and the characterisation of how social perceptions and values influence both previous elements. Our new framework will be demonstrated for four case studies in the UK in collaboration with national, regional, and local stakeholders. This will provide a scalable and adaptive solution to support coastal management and policy development. Co-Opt has been co-designed with project partners essential to the implementation and delivery of coastal and shoreline management (e.g. Environment Agency, Natural Resources Wales, NatureScot, coastal groups) and will address their specific needs including development of thorough cost-benefit analyses and recommendations for action plans when preferred policy changes. Co-Opt will further benefit the broad coastal science base by supporting more integrated and interdisciplinary characterisation of the complex coastal human-environment system.</p
Glasgow Mobility App Survey, 2022: Secure Access
No full textAbstract copyright UK Data Service and data collection copyright owner.The Glasgow Mobility App Survey (GlaMAS) is a cross-sectional survey based on a sample of the general adult population living in private residences across the Glasgow city region. The data collection aimed to capture information about individuals' travel behaviour through three methods. First, the researchers conducted a household survey to get information on socio-demographic characteristics and travel-related attitudes and behaviours. Second, each participant was asked to install TravelAI's 'MyWays' app on their mobile phone. The app automatically tracks the locations of individuals, detects stops, and estimates the mode of travel. Third, participants were asked to complete a one-day travel diary administered through the 'MyWays' app so that this could be compared to the automatically-detected travel records.Main Topics:The household survey collected data relating to:family type, household income, etc., to allow understanding of the socio-economic background of the householdindividual's patterns of activity and mobilityvalues, attitudes, and perceptions towards different modes of travel relating to behaviours and daily activityinformal competencies, like numeracy, IT skills, etc.work patterns, including work from home informationimpact of COVID-19 on attitudes and perceptions towards different modes of travelThe manual travel diary and automatic trip data from the 'MyWays' app aimed to investigate the following:the potential of smartphones for automatically producing a travel diarythe correspondence between the manual travel diary and the automatic travel diary</ul
COVID-19 Intimacies: Resilience and Viral Safety among LGBT and Heterosexual People Using Dating Apps in the COVID-19 Era, 2023
No full textThis data collection explores how lesbian, gay, bisexual, trans (LGBT) and heterosexual individuals used dating apps to navigate intimacy and social connection during and after COVID-19 lockdowns. It investigates how digital platforms facilitated or hindered emotional and physical closeness, and how these interactions shaped personal resilience and perceptions of viral risk. Drawing on a national survey (n=824) and qualitative interviews (n=53), the study examines differing cultures of intimacy across sexual and gender identities, and their implications for online dating practices and support needs. Findings aim to inform how internet-based services can better support diverse emotional and social needs during times of crisis.
The deposited collection contains anonymised survey responses of of 824 heterosexual and LGBTQ+ (self-identified lesbian, gay, bisexual, Trans and Queer) people and anonymised transcripts of 53 semi-structured online interviews which addressed the flux and flow of dating app use, the meanings and practices attached to virtual intimacies and connections, and of COVID-19 and the negotiation of viral risk.This project examines lesbian, gay, bisexual, trans (LGBT) and heterosexual people's use of online dating apps to negotiate intimacy (i.e. emotional and/or physical closeness) during and after COVID-19 social distance and lockdowns. It focuses on how diverse sexual and gendered cultures of intimacy are facilitated or constrained by dating apps during and after COVID-19, the implications of the existing and new intimate practices associated with dating apps for supporting personal resilience (i.e. people's ability to cope with difficult situations, such as those associated with COVID-19 lockdowns and social distance) , and how they encourage or discourage intimacy that is safe from COVID-19 and similar viral infections. It will generate knowledge about how internet-based services can be harnessed to support people's social and emotional needs, as well as safer intimacies, during and after the implementation of social distance measures.
The researchers will collaborate with service providers and community representatives throughout the project to identify virtual interventions as appropriate to diverse intimate cultures and to promote personal resilience and 'safer' intimacy in the context of social distance and heightened viral risk. The study will include an initial round of online workshops with an expert partner group to explore how they: view the intimate possibilities and risks associated with virtual dating during COVID-19; have developed support activities online; and responded to any increase to the level of service demand. The group will advise on the design, undertaking and analysis of the research, and will be composed by representatives from dating app businesses, service providers, community representatives and international research experts and scholars.
The project will combine a nationwide online survey (n= 600 approx.) with in-depth online qualitative interviews (n=60). Closed survey questions will enable the gathering of demographic data and the deployment of the Adult Resilience Measure (ARM-R), as developed by Resilience Research Centre, Dalhousie University, to provide data on resilience. Open survey questions will generate data on self-perceptions of the implications of dating app use for countering or enhancing a sense of social isolation and intimate disconnectedness during the COVID-19 era, as well as the implications for negotiating viral risk. Virtual semi-structured interviews will generate data about diverse cultures and practices of intimacy pre- and post COVID-19; the possibilities and challenges presented by social distance for maintaining existing and developing new practices and cultures of intimacy; the virtual interactions involved in the negotiation of viral risk; and the ebb and flow of personal resilience as it links to dating app use over time. The interviews will generate data on LGBT and heterosexual experiences of using dating apps before, during and in transitioning out of social distance and lockdowns. The rationale for this focus is that the existing research suggests that lesbians, gay men, bisexuals, trans and heterosexuals have different cultures of intimacy, dating norms, online/offline practices of intimacy, and can have distinctive perceptions of viral risks (e.g. gay men are likely to be more informed about HIV) that influence their intimate practices online and are linked in multi-dimensional ways to their negotiation of risks offline.
From the outset, the project will work with its expert partners group to determine what support services for intimate relations can be developed and/or transitioned to online service delivery during times of social distancing, with an emphasis of catering for diverse intimate cultures as they are shaped by gendered sexualities in interaction with socio-cultural positioning linked to geography, generation, racial and economic location.</p
Contextualised Accent Bias in Professional Hierarchies: Accent Effect on Evaluations of Graduate and Legal Job Candidates, 2021-2022
No full textThis data collection contains two experimental studies examining contextualised accent bias in UK professional settings. The motivation for the research is that accent continues to function as a salient social cue in the UK, signalling classed and regional identities, and may influence how speakers are evaluated in education, employment, and professional advancement. Although previous work has documented general attitudes toward English accents, less is known about how these evaluations change in relation to specific roles, sectors, and expectations within professional hierarchies. The aim of the studies was to test whether accent bias emerges selectively in contexts where role demands and linguistic norms align with particular social meanings associated with different accents.
Study 1 investigates evaluations of a recent university graduate speaking either Received Pronunciation (RP) or Multicultural London English (MLE). Participants listened to two short interview recordings and then rated the candidate on general impression and on their perceived suitability for a range of UK job roles differing in sector and seniority, including hospitality, public administration, and banking. Study 1 explores whether listeners apply accent-linked stereotypes differently when judging roles with varying status, client-facing demands, or symbolic prestige.
Study 2 focuses on the legal profession and examines how UK law students evaluate a candidate speaking either RP or MLE across legal career pathways in corporate and criminal law. Participants rated the likelihood that the candidate would receive appointments to positions ranging from trainee solicitor and pupillage roles to solicitor, barrister, and senior barrister roles. Study 2 tests whether accent-based evaluations are shaped by the linguistic expectations and prestige norms associated with different branches of the legal profession.
Across both studies, general evaluations showed no overall differences by accent, but role-specific evaluations revealed systematic patterns. Non-standard accents were judged more positively in some customer-facing or lower-status contexts, whereas RP was favoured in higher-status professional roles, particularly in legal pathways where linguistic standards are more tightly enforced. These findings support the view that accent bias is context dependent and can contribute to structural barriers to progression in UK professional hierarchies.
The dataset includes audio-based evaluation measures, role and sector judgments, accent perception items, attention checks, and demographic variables.This project investigates how English accents influence evaluations of job candidates across professional contexts in the UK.
Study 1 examines how listeners judge a recent university graduate speaking either Received Pronunciation or Multicultural London English across sectors and job seniority levels. Study 2 focuses on the legal profession, with law students evaluating a candidate for roles across corporate and criminal law, from trainee positions to senior barrister roles.
The findings show that accent bias is highly context dependent, emerging in specific professional settings and increasing where linguistic standards are more tightly enforced. The dataset supports research on workplace inequality, recruitment practices, and social mobility.</p
Labour Force Survey Five-Quarter Longitudinal Dataset, April 2023 - June, 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.
Longitudinal data
The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary.
LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2022 WeightingThe population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust.Main Topics:The five-quarter longitudinal datasets include a subset of the most commonly used variables from the Quarterly Labour Force Survey (QLFS), covering the main areas of the survey
Labour Force Survey Five-Quarter Longitudinal Dataset, October 2023 - December, 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.
Longitudinal data
The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary.
LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2022 WeightingThe population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust.Main Topics:The five-quarter longitudinal datasets include a subset of the most commonly used variables from the Quarterly Labour Force Survey (QLFS), covering the main areas of the survey