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English Housing Survey, 2023-2024: Household Data
No full textAbstract copyright UK Data Service and data collection copyright owner.The English Housing Survey (EHS) is a continuous national survey commissioned by the Ministry of Housing, Community and Local Government (MHCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures. The information obtained through the survey provides an accurate picture of people living in the dwelling, and their views on housing and their neighbourhoods. The survey is also used to inform the development and monitoring of the Ministry's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public.
The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 12,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC).
The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire.
Safeguarded and Special Licence Versions:
From 2014 data onwards, the Safeguarded versions (previously known as End User Licence (EUL)) of the EHS will only include derived variables. In addition the number of variables on the new EUL datasets has been reduced and disclosure control increased on certain remaining variables. New Special Licence versions of the EHS will be deposited later in the year, which will be of a similar nature to previous EHS EUL datasets and will include derived and raw datasets.
Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages.
SN 9442 - English Housing Survey, 2023-2024: Household Data contains data from the interview survey only. The data from the physical survey are available under SN 9441 - English Housing Survey, 2023: Housing Stock Data.Main Topics:The EHS Housing survey consists of two components.Interview survey on the participating household - An interview is first conducted with the householder. The interview topics include: household characteristics, satisfaction with the home and the area, disability and adaptations to the home, ownership and rental details and income details. All interviewees are guaranteed confidentiality and all data is anonymised.Physical survey on the housing stock - A visual inspection of both the interior and exterior of the dwelling is carried out by a qualified surveyor to assess the condition and energy efficiency of the dwelling. Topics covered include whether the dwelling meets the Decent Homes Standard; cost to make the dwelling decent; existence of damp and Category 1 Hazards as measured by the Housing Health and Safety Rating System (HHSRS); Energy Efficiency Rating. The physical survey is carried out on the dwelling of a sub-sample of the participants of the interview survey. The sub-sample consists of the dwelling of participants living in private or social rented properties and a sub-sample of those in owner occupied properties. A proportion of the dwellings found to be vacant during the interview survey are also included in the physical survey.</p
Quarterly Labour Force Survey, Household Dataset, April - June, 2025
No full textAbstract copyright UK Data Service and data collection copyright owner.BackgroundThe 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.Household datasetsUp to 2015, the LFS household datasets were produced twice a year (April-June and October-December) from the corresponding quarter's individual-level data. From January 2015 onwards, they are now produced each quarter alongside the main QLFS. The household datasets include all the usual variables found in the individual-level datasets, with the exception of those relating to income, and are intended to facilitate the analysis of the economic activity patterns of whole households. It is recommended that the existing individual-level LFS datasets continue to be used for any analysis at individual level, and that the LFS household datasets be used for analysis involving household or family-level data. From January 2011, a pseudonymised household identifier variable (HSERIALP) is also included in the main quarterly LFS dataset instead.Change to coding of missing values for household seriesFrom 1996-2013, all missing values in the household datasets were set to one '-10' category instead of the separate '-8' and '-9' categories. For that period, the ONS introduced a new imputation process for the LFS household datasets and it was necessary to code the missing values into one new combined category ('-10'), to avoid over-complication. This was also in line with the Annual Population Survey household series of the time. The change was applied to the back series during 2010 to ensure continuity for analytical purposes. From 2013 onwards, the -8 and -9 categories have been reinstated.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each volume alongside the appropriate questionnaire for the year concerned. However, LFS volumes are updated periodically by ONS, so users are advised to check the ONS LFS User Guidance page before commencing analysis.Additional data derived from the QLFSThe Archive also holds further QLFS series: End User Licence (EUL) quarterly datasets; Secure Access datasets (see below); two-quarter and five-quarter longitudinal datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.End User Licence and Secure Access QLFS Household datasetsUsers should note that there are two discrete versions of the QLFS household datasets. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. Secure Access household datasets for the QLFS are available from 2009 onwards, and include additional, detailed variables not included in the standard EUL versions. Extra variables that typically can be found in the Secure Access versions but not in the EUL versions relate to: geography; date of birth, including day; education and training; household and family characteristics; employment; unemployment and job hunting; accidents at work and work-related health problems; nationality, national identity and country of birth; occurrence of learning difficulty or disability; and benefits. For full details of variables included, see data dictionary documentation. The Secure Access version (see SN 7674) has 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.Changes to variables in QLFS Household EUL datasetsIn order to further protect respondent confidentiality, ONS have made some changes to variables available in the EUL datasets. From July-September 2015 onwards, 4-digit industry class is available for main job only, meaning that 3-digit industry group is the most detailed level available for second and last job.Review of imputation methods for LFS Household data - changes to missing valuesA review of the imputation methods used in LFS Household and Family analysis resulted in a change from the January-March 2015 quarter onwards. It was no longer considered appropriate to impute any personal characteristic variables (e.g. religion, ethnicity, country of birth, nationality, national identity, etc.) using the LFS donor imputation method. This method is primarily focused to ensure the 'economic status' of all individuals within a household is known, allowing analysis of the combined economic status of households. This means that from 2015 larger amounts of missing values ('-8'/-9') will be present in the data for these personal characteristic variables than before. Therefore if users need to carry out any time series analysis of households/families which also includes personal characteristic variables covering this time period, then it is advised to filter off 'ioutcome=3' cases from all periods to remove this inconsistent treatment of non-responders.
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.Main Topics:The LFS household datasets cover:characteristics of the household: number of people of working age; number of people over working age; number of children aged 0 to 4; number of children aged 5 to 15; number of dependent children (i.e. those in full-time education) aged 16 to 18economic activity in the household: number of people in employment; number of people in full-time employment; number of people in part-time employment; unemployed; economically inactive; students; sick or disabled; economically inactive but would like to work and are not seeking work because they do not believe there is work available ('discouraged workers'); care of dependants</ul
Growing Up in Scotland: Cohort 1: Sweep 11, 2021-2023, Attainment Data: Secure Access
No full textAbstract copyright UK Data Service and data collection copyright owner.The Growing Up in Scotland (GUS) study is a large-scale longitudinal social survey which follows the lives of several groups of Scottish children from infancy through childhood and adolescence, and aims to provide important new information on children and their families in Scotland. The study forms a central part of the Scottish Government's strategy for the long-term monitoring and evaluation of its policies for children, with a specific focus on the early years. Unlike other similar cohort studies, this survey has a specifically Scottish focus. A key objective of GUS is to address a significant gap in the evidence base for early years policy monitoring and evaluation. The study seeks both to describe the characteristics, circumstances and experiences of children in their early years (and their parents) in Scotland and, through its longitudinal design, to generate a better understanding of how children's start in life can shape their longer term prospects and development.Since 2005, study design and data collection have been undertaken by ScotCen Social Research with collaborations with the Centre for Research on Families and Relationships, based at the University of Edinburgh and the MRC/CSO Social and Public Health Sciences Unit over certain periods of the project. The survey design consisted of recruiting an initial total of 8,000 parents in 2005, comprising two cohorts of children (5,000 from birth, 3,000 from age two years and ten months), and then interviewing parents annually until their child reached age five years ten months. Further fieldwork was undertaken with the birth cohort when the children were around eight, ten, twelve and fourteen years old. A boost sample of 500 children from predominantly high deprivation areas was added to the cohort as part of the age 12 fieldwork.For sweeps 1 to 9 data were collected via an in-home, face-to-face interview with self-complete sections. Fieldwork for sweeps 10 and 11 were disrupted due to the COVID pandemic. As a result, portions of the data were collected via web and telephone questionnaires whilst others involved face-to-face interviews where they were permitted. The study user guides provide further details.Special Licence data:The main survey data are available under Special Licence:SNs 9373-9383 and 9386-9387 - Growing Up in Scotland: Cohort 1SN 7432 - Growing Up in Scotland: Cohort 2SN 8366 - Growing Up in Scotland: Cohort 1, Primary 6 Teacher SurveySecure Access Geographic Data:Geographic data are available under Secure Access and are separated by cohort, sweep and type of geographic variable. Information is available on the GUS Access Data web page. Users must also include the main Growing Up in Scotland Special Licence data in the Accredited Researcher Proposal form and add it to their projects (please note there is no need for Secure Access users to complete a separate Special Licence application).Secure Access Early Learning and Childcare Administrative Data:Care Inspectorate quality information on the settings which provided children in Birth Cohort 1 and Birth Cohort 2 with their state-funded early learning and childcare (pre-school) entitlement when they were aged between 3 and 5 years old is available under SN 8543 (Birth Cohort 1) and SN 8544 (Birth Cohort 2).Secure Access Linked Administrative Data:A data matching exercise was was undertaken using the Scottish Government Pupil Census at Birth Cohort 1 Sweep 11 and participants were linked with their Scottish Candidate Number (SCN). The SCNs were then supplied to the Scottish Qualifications Authority (SQA), who were able to provide the attainment records for participants (available under SN 9447). The SCNs were then supplied to Skills Development Scotland (SDS), who were able to provide the school leaver destinations record for participants (available under SN 9448).SN 9447 - Growing Up in Scotland: Cohort 1: Sweep 11, 2021-2023, Attainment Data: Secure AccessUsing GUS participants date of birth, postcode and school SEED code, a data matching exercise was undertaken using the Scottish Government Pupil Census. Using these identifiers, participants were linked with their Scottish Candidate Number (SCN). SCNs are allocated to pupils at school and in further-education colleges who undertake Scottish Qualifications Authority (SQA) courses. Once the matching exercise was complete, over 90% of Sweep 11 GUS participants were matched with their SCN. The pupil census only includes pupils at Local Authority funded schools in Scotland. Therefore, of those that could not be matched, the majority are most likely pupils at independent or private schools. The SCNs were then supplied to the SQA, who were able to provide the attainment record for participants. SCNs have since been removed from the dataset, and replaced with GUSID. Researchers can use this GUSID to link attainment data with GUS survey responses.When researchers are approved/accredited to access this study, the GUS Cohort 1, Sweep 11 study (SN 9383) will be automatically provided alongside.Main Topics:The data file includes an ID variable for matching to the main GUS sweep survey data and seven SQA attainment variables detailing information about the qualifications obtained. </div
Annual Population Survey Household Dataset, January - December, 2024
No full textAbstract copyright UK Data Service and data collection copyright owner.The Annual Population Survey (APS) household datasets are produced annually and are available from 2004 (Special Licence) and 2006 (End User Licence). They allow production of family and household labour market statistics at local areas and for small sub-groups of the population across the UK. The household data comprise key variables from the Labour Force Survey (LFS) and the APS 'person' datasets. The APS household datasets include all the variables on the LFS and APS person datasets, except for the income variables. They also include key family and household-level derived variables. These variables allow for an analysis of the combined economic activity status of the family or household. In addition, they also include more detailed geographical, industry, occupation, health and age variables.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. 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
End User Licence and Secure Access APS data
Users 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 childfamily 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 familynationality and country of origingeography: 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 districthealth: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressThe 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
Third Sector and Civil Society Organisations in the UK, 1869-2025
No full textThis dataset brings together information on all organisations registered with at least one charitable or non-profit regulator in the United Kingdom. It was developed by combining and deduplicating records from ten separate registers, covering organisations across all four nations of the UK. The Third Sector and Civil Society (TSCS) in the UK are overseen by a range of regulatory bodies, including three national charity regulators and several additional registers for non-profit entities. Companies House, the UK’s official register of companies, also includes non-profit types such as companies limited by guarantee and community interest companies.
Because these registers operate independently and often overlap—many organisations appear in more than one—the available data is fragmented. This fragmentation makes it difficult to form a clear picture of civil society and its role within the UK. By integrating these diverse sources and linking records where evidence suggests they refer to the same organisation, we produce a unified “spine” of TSCS organisations. This consolidated list enables consistent mapping, analysis, and monitoring of the sector as a whole. The spine can also be linked to other datasets—such as government procurement records—to examine patterns in public spending, or to demographic data to explore the geographic and social distribution of civil society activity across the UK.The voluntary sector is widely acknowledged as containing very large numbers of organisations that make an enormous contribution to well-being and social cohesion in the UK. It encompasses charities, social enterprises, mutuals, cooperatives, and many less formal voluntary and community organisations. We know a great deal from survey data about patterns of individual giving to charities, and about patterns of volunteering. But there is a substantial gap in the availability of high-quality data about voluntary organisations. And it is argued that better-quality information and evidence would lead to the contribution of those organisations being properly recognised, leading in turn to higher levels of public and voluntary support for them.
This project responds to this need by creating the first national database on the population of organisations forming the third sector through bringing together information about charities with information about different kinds of noncharitable civil society organisations (including Community Interest Companies, Co-operatives and Mutuals, and non-profit Companies Limited by Guarantee). A variety of relevant registers are maintained by different regulators and public bodies across the four nations of the UK. Each register holds partial and sometimes overlapping information about civil society organisations. This project combines them into a single, deduplicated dataset, linking records that refer to the same organisation.
The project will open up new avenues for research on, for example, the survival and growth of third sector organisations; the contribution of the third sector to public service delivery; the level of voluntary sector activity in different parts of the country. In this way, we will make the contribution of the sector much more visible to stakeholders.
In strategic terms this work provides an important demonstration of the uses of administrative data for research on organisations - a field in which most work to date has focussed on administrative data on individuals. The dataset can be linked to publicly available information on government and NHS spending, allowing users to identify which organisations receive public funding. It can be used to support further analysis of the size, scope, and distribution of third sector organisations across the UK This will be of value to funders (such as charitable foundations), central and local government, local and regional councils for voluntary service, which sustain these organisations locally, and commissioners of public services such as the NHS, which rely substantially on the voluntary sector to deliver services.</p
Engagement of Cities With Faith Leaders Regarding Climate Change Action: Metadata and Documentation, 2021-2022
No full textThe three documents archived comprise the project information sheet, the consent form, and the list of questions to be asked to faith leaders who act on climate change in the UK.
We conducted semi-structured interviews between October 2021 and February 2022 with individuals based throughout the UK (listed in the Appendix). We do not claim that this sample is representative of all of the views and experiences of Muslims involved in climate action. Interviewees included Muslims who were: local councillors; faith representatives and spokespeople; a civil servant; an employee in the not-for-profit climate sector; and environmental campaigners. We also interviewed two non-Muslims involved in interfaith activities with Muslim communities. We interviewed a wide range of individuals to analyse the experiences of different types of potential Muslim climate intermediaries, and the strategies, interactions, and impacts they demonstrate. We included anyone who self-identified as
Muslim and played a role in representing a community or acting on climate change with others. Meaning, they were not required to have passed any threshold for said involvement in climate action, because such criteria may have led to the exclusion of valuable perspectives regarding stymied involvement in climate action.
We identified interviewees by purposive sampling and searching online for climate activities within the UK that referred to Muslim participants or Islam. From there, the snowball method was used to expand our range of contacts. Interviews were conducted online, and interviewees were assured anonymity. Interviews ranged from 30 to 90 min in length, with the majority being around an hour, and were recorded on Zoom and then transcribed by professional transcription companies or by one of the co-authors.
The data could not be archived due to ethical constraints.The science behind climate change has been established, and now the mitigation of climate change has become a political puzzle. We need to act quickly to mitigate the worst impacts of climate change, and so this project is designed to find and then share effective policy solutions that can be used across society.
Until very recently, attempted solutions for climate change were 'top down': for example, the United Nations organised annual conferences, and those countries responsible for producing the most greenhouse gases dominated these negotiations. However, this approach for dealing with climate change has failed to generate effective change quickly enough, and academics are looking for new governance solutions for this most pressing and significant of issues.
Increasingly, scholars argue that we need to be improving policy-making the local level, and empowering a wide range of people take a lead in responding to climate change. In particular, they argue we need 'polycentric governance'. Polycentric governance involves businesses, NGOs and government agencies working independently of each other, while also overlapping and coordinating with one another, as part of complex, multi-level networks. The outcome should be that no individual group or organisation is solely responsible for mitigating climate change, and so every 'node' in the network is encouraged to fulfil its part without fearing being exploited by others.</p
Interviews With IFCN-Member Fact-Checkers, 2025
No full textWe conduct 18 semi-structured interviews with International Fact-Checking Network member fact-checkers from around the world. Our findings underline the diverse range of epistemic work undertaken by fact-checkers. We argue that this diverse range of work is consistent with three distinct epistemic approaches to fact-checking, which we term the verification model, the argumentative model, and the interpretative model. Our findings suggest that the verification model is a dominant but not universal ideal that is rarely fully or consistently implemented in practice. Our findings also offer insights regarding the appeal of the verification model as well as the reasons why and circumstances in which fact-checkers move beyond it. Our findings contribute towards a fuller, richer understanding and characterisation of the epistemologies of fact-checking; and have significant implications for critiques and defences of the epistemology of fact-checking and concepts and measures proposed in the literature to enhance the epistemic approach of fact-checkers.Fact-checking, as a distinct journalistic form, has risen to prominence in the 21st century as a response to concerns about a lack of respect for the truth in political debate and the rapid spread of misinformation across
social media platforms. This project will leverage expertise and insights from the social sciences and philosophy to examine fact-checking epistemologies – that is, simply put, how fact-checkers produce, justify
and articulate their knowledge claims. In the context of political polarisation, challenges to the authority of expertise, concerns about dishonesty in political debate, and the spread of misinformation online, the
epistemologies of fact-checkers and how they are perceived by public audiences are topics of great importance. This research will generate novel and impactful knowledge about how fact-checkers produce and
justify fact-checks, how automation could change this, and how UK and US public audiences and stakeholders view different epistemic approaches to fact-checking.</p
Growing Up in Scotland: Cohort 1: Sweep 3, 2007-2008: Special Licence Access
No full textAbstract copyright UK Data Service and data collection copyright owner.The Growing Up in Scotland (GUS) study is a large-scale longitudinal social survey which follows the lives of several groups of Scottish children from infancy through childhood and adolescence. It aims to provide important information on children, young people and their families in Scotland. The study forms a central part of the Scottish Government's strategy for the long-term monitoring and evaluation of its policies for children and young people, with a specific focus on the early years. The study seeks both to describe the characteristics, circumstances and experiences of children in their early years in Scotland and, through its longitudinal design, to generate a better understanding of how children's start in life can shape their longer term prospects and developmentSince 2005 fieldwork has been undertaken by the Scottish Centre for Social Research. The survey design for Birth Cohort 1 consisted of recruiting the parents of an initial total of 5,217 children aged 10 months old in 2005 and interviewing them annually until their child reached age six. Further fieldwork was then undertaken at ages 8, 10, 12, 14 and 17-18 with a sample boost added at age 12.Data for sweeps 1-9 were collected via an in-home, face-to-face interview with self-complete sections. Fieldwork for sweep 10 was disrupted due to the COVID pandemic. As a result, the final portion of the data was collected via web and telephone questionnaires. Sweep 11 data were gathered via web, telephone and face-to-face surveys of cohort members and their parent/carer.Further information about the survey may be found on the Growing Up in Scotland website.In May 20205, data and documentation for Cohort 1, Sweeps 1-11 were released as individual studies (SNs 9373-9383 and 9386-9387). Previously they were held under one study (SN 5760) which has been withdrawn from the data catalogue.Main Topics:The main carer questionnaire covered the following topics:household informationnon-resident parentsfood and nutritionparentingtransition to pre-schoolchildcarechild health and developmentactivities with otherschild, parent and family social networksneighbourhood and communitywork, employment and incomeaccommodation and transportA topic overview covering all sweeps, is available on the GUS website.</div
Growing Up in Scotland: Cohort 1: Sweep 8, 2014-2015: Special Licence Access
No full textAbstract copyright UK Data Service and data collection copyright owner.The Growing Up in Scotland (GUS) study is a large-scale longitudinal social survey which follows the lives of several groups of Scottish children from infancy through childhood and adolescence. It aims to provide important information on children, young people and their families in Scotland. The study forms a central part of the Scottish Government's strategy for the long-term monitoring and evaluation of its policies for children and young people, with a specific focus on the early years. The study seeks both to describe the characteristics, circumstances and experiences of children in their early years in Scotland and, through its longitudinal design, to generate a better understanding of how children's start in life can shape their longer term prospects and developmentSince 2005 fieldwork has been undertaken by the Scottish Centre for Social Research. The survey design for Birth Cohort 1 consisted of recruiting the parents of an initial total of 5,217 children aged 10 months old in 2005 and interviewing them annually until their child reached age six. Further fieldwork was then undertaken at ages 8, 10, 12, 14 and 17-18 with a sample boost added at age 12.Data for sweeps 1-9 were collected via an in-home, face-to-face interview with self-complete sections. Fieldwork for sweep 10 was disrupted due to the COVID pandemic. As a result, the final portion of the data was collected via web and telephone questionnaires. Sweep 11 data were gathered via web, telephone and face-to-face surveys of cohort members and their parent/carer.Further information about the survey may be found on the Growing Up in Scotland website.In May 20205, data and documentation for Cohort 1, Sweeps 1-11 were released as individual studies (SNs 9373-9383 and 9386-9387). Previously they were held under one study (SN 5760) which has been withdrawn from the data catalogue.Main Topics:The main carer questionnaire covered the following topics:household informationparentingnon-resident parents (NRP)primary school out of school carechild health and developmentactivitiesfood and eatingemployment and educationincome, expenditure and financial stresshousing and accommodationhousehold informationThe child self-completion interview consisted of an audio-CASI section with questions on the following topics: schoolfriendsrelationship with parents/carerslife satisfactionA topic overview covering all sweeps, is available on the GUS website.</p
Crime Survey for England and Wales, 2023-2024
No full textAbstract copyright UK Data Service and data collection copyright owner.The Crime Survey for England and Wales (CSEW) asks a sole adult in a random sample of households about their, or their household's, experience of crime victimisation in the previous 12 months. These are recorded in the victim form data file (VF). A wide range of questions are then asked, covering demographics and crime-related subjects such as attitudes to the police and the criminal justice system (CJS). These variables are contained within the non-victim form (NVF) data file. In 2009, the survey was extended to children aged 10-15 years old; one resident of that age range was also selected from the household and asked about their experience of crime and other related topics. The first set of children's data covered January-December 2009 and is held separately under SN 6601. From 2009-2010, the children's data cover the same period as the adult data and are included with the main study.The Telephone-operated Crime Survey for England and Wales (TCSEW) became operational on 20 May 2020. It was a replacement for the face-to-face CSEW, which was suspended on 17 March 2020 because of the coronavirus (COVID-19) pandemic. It was set up with the intention of measuring the level of crime during the pandemic. As the pandemic continued throughout the 2020/21 survey year, questions have been raised as to whether the year ending March 2021 TCSEW is comparable with estimates produced in earlier years by the face-to-face CSEW. The ONS Comparability between the Telephone-operated Crime Survey for England and Wales and the face-to-face Crime Survey for England and Wales report explores those factors that may have a bearing on the comparability of estimates between the TCSEW and the former CSEW. These include survey design, sample design, questionnaire changes and modal changes.More general information about the CSEW may be found on the ONS Crime Survey for England and Wales web page and for the previous BCS, from the GOV.UK BCS Methodology web page.History - the British Crime SurveyThe CSEW was formerly known as the British Crime Survey (BCS), and has been in existence since 1981. The 1982 and 1988 BCS waves were also conducted in Scotland (data held separately under SNs 4368 and 4599). Since 1993, separate Scottish Crime and Justice Surveys have been conducted. Up to 2001, the BCS was conducted biennially. From April 2001, the Office for National Statistics took over the survey and it became the CSEW. Interviewing was then carried out continually and reported on in financial year cycles. The crime reference period was altered to accommodate this.
Secure Access CSEW dataIn addition to the main survey, a series of questions covering drinking behaviour, drug use, self-offending, gangs and personal security, and intimate personal violence (IPV) (including stalking and sexual victimisation) are asked of adults via a laptop-based self-completion module (questions may vary over the years). Children aged 10-15 years also complete a separate self-completion questionnaire. The questionnaires are included in the main documentation, but the data are only available under Secure Access conditions (see SN 7280), not with the main study. In addition, from 2011 onwards, lower-level geographic variables are also available under Secure Access conditions (see SN 7311).New methodology for capping the number of incidents from 2017-18The CSEW datasets available from 2017-18 onwards are based on a new methodology of capping the number of incidents at the 98th percentile. Incidence variables names have remained consistent with previously supplied data but due to the fact they are based on the new 98th percentile cap, and old datasets are not, comparability has been lost with years prior to 2012-2013. More information can be found in the 2017-18 User Guide (see SN 8464) and the article ‘Improving victimisation estimates derived from the Crime Survey for England and Wales’. No data available for 10-15 year-olds for 2023/24Data for 10-15-year-old respondents is not currently included in the 2023/24 study. The Office for National Statistics is currently assessing these data and deciding whether to include it for this year. The questionnaire for 10-15-year-olds has been included in the documentation and is also available on the ONS Crime and Justice Methodology webpage. At the time of release, the technical report and user guide were not yet available, but will be published in due course on the same webpage.Main Topics:
The adult non-victim form questionnaire covers: perceptions of crime and local area; performance of the CJS; mobile phone crime; experiences of the police (Module A); attitudes to the CJS (Module B); crime prevention and security (Module C); financial loss and fraud; anti-social behaviour; demographics and media. The adult victim form contains offence-level data. Up to six different incidents were asked about for each respondent. Each of these constituted a separate victim form and can be matched back to the respondent-level data. Topics covered included: the nature and circumstances of the incident; details of offenders; costs; emotional reactions; and contact with the Police. Fraud victims are now asked an entirely separate set of questions.Self-completion modules for adult respondents covered: drug use and drinking; sources of support and perceptions of safety; interpersonal violence (IPV) (domestic abuse, sexual victimisation and stalking); and experience of abuse during childhood. These data are subject to Secure Access conditions and are available as part of SN 7280.</ul