The ABPE (5,440,486 people) was 0.7% higher than the MYE (5,404,700 people). At single year of age level, ABPE was generally higher than MYE for people aged: 6–14 and 28–64 and generally lower for people aged: 1–5, 15–27 and 65+. The ABPE ranged from 3.8% higher to 4.8% lower at council area level, with half of the council areas being within 1.2 per cent of MYE. The results of this statistical research are encouraging. Future work will now focus on improving the quality of estimates across all age groups and at sub-national geographic aggregations.

Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex, and the survey research organisations Verian Group and NatCen. It builds on and incorporates the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society: Linked Education Administrative Datasets (Scottish Education Data), Scotland, 2007-2018: Secure Access study contains six files extracted from Sottish Education Data held by the Scottish Government. These can be linked (within the Secure Access service) to Understanding Society participants using the cross-wave personal identifier (variable pidp). The Scottish Education Data files include information on pupil background, attainment, destination of leavers, student support, school attendance, absences and exclusions for all individuals with a valid consent to education linkage collected in Waves 1 and 4 of Understanding Society. This includes consents collected from parents of children aged 4-15 and of the young adults aged 16-43 and born in 1981 or later. The files include School Pupil Census data collected in September from pupils in state schools. Attainment data relates to senior phase attainment covering SQA qualifications. See documentation for further details.

Related UK Data Archive studies
The equivalent study to this one that covers England is available in SN 7642. This study is frequently linked through the pidp variable to one of the main Understanding Society datasets: SN 6614 (End User Licence), SN 6931 (Special Licence) or SN 6676 (Secure Access). A Special Licence dataset containing School Codes for the main Understanding Society study (SN 7182) is also available. Further details can be found on the "http://discover.ukdataservice.ac.uk/series/?sn=2000053" target="_blank" style="background-color: rgb(255, 255, 255);"> Understanding Society series webpage.

DataLoch works with data in several ways, including: collaborating with clinicians to improve the data quality; linking datasets to enable broad insights; translating data into common standard definitions; and maintaining a high-quality metadata dictionary. Critical to this work is the involvement of clinical experts from NHS Scotland who have a detailed understanding of routine data in health care and help the DataLoch team make sure the data are research-ready.

Our initial focus was on building a COVID-19 dataset to support clinicians and NHS partners in their ongoing COVID-19 response. These data have proven to be an invaluable resource enabling researchers and clinicians to generate new knowledge and insights. Feedback from our early contributors has helped inform improvements to the process and development of the data to support research beyond COVID-19.

About this dataset

Context

The dataset tabulates the population of New Scotland town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for New Scotland town. The dataset can be utilized to understand the population distribution of New Scotland town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in New Scotland town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for New Scotland town.

Key observations

Largest age group (population): Male # 50-54 years (486) | Female # 55-59 years (457). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the New Scotland town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the New Scotland town is shown in the following column.
• Population (Female): The female population in the New Scotland town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in New Scotland town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Scotland town Population by Gender. You can refer the same here

Objectives: We sought to work collaboratively with public health stakeholders who use evidence in their work to identify practical ways that cross-sectoral data sharing and linkage could be used to best effect to improve health and reduce health inequalities.

Methods: We undertook three sequential stakeholder workshops with participants from local and central government, public health teams, Health and Social Care Partnerships, the third sector, organisations which support data-intensive research, and public representatives from across Scotland. The workshops were informed by a scoping review on use of evidence in public health policy and practice, searching Medline, Scopus, SSCI, and key institutional websites, and by three case studies of existing cross-sectoral linkage projects.

Details of data collection: The data collection comprises de-identified transcripts of stakeholder workshops and a copy of the visual map produced as part of the workshops. Stakeholders comprised people We held workshops to bring together people working in public health practice; in policy sectors potentially relevant to health; and in information governance, infrastructure and/or support for data and research; as well as a number of public representatives. Potential attendees were identified through a stakeholder mapping exercise with the project advisory group, followed by review of relevant organisational websites and advice from gatekeeper organisations such as Administrative Data Scotland.

Background Secondary data from different sectors can provide unique insights into the social, environmental, economic, and political determinants of health. This is especially pertinent in the context of whole-systems approaches to public health, which typically combine cross-sectoral collaboration with the application of theoretical insights from systems science. However, sharing and linkage of data between different sectors to inform healthy public policy is still relatively rare. Previous research has documented the perspectives of researchers and members of the public on data sharing, especially healthcare data, but has not engaged with decision-makers working in public health practice and public policy. Objective(s) We sought to work collaboratively with public health stakeholders who use evidence in their work to identify practical ways that cross-sectoral data sharing and linkage could be used to best effect to improve health and reduce health inequalities. Methods We undertook three sequential stakeholder workshops with participants from local and central government, public health teams, Health & Social Care Partnerships, the third sector, organisations which support data-intensive research, and public representatives from across Scotland. The workshops were informed by a scoping review on use of evidence in public health policy and practice, searching Medline, Scopus, SSCI, and key institutional websites, and by three case studies of existing cross-sectoral linkage projects. Findings were synthesised using thematic analysis. Setting and scope Scotland; public and third sector data.

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old. End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).


How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Health Administrative Datasets (SAIL) for Wales held under SN 9310
  
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application.

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

The Millennium Cohort Study: Linked Health Administrative Data (Scottish Medical Records), Child Health Reviews, 2000-2015: Secure Access includes data files from the NHS Digital Hospital Episode Statistics database for those cohort members who provided consent to health data linkage in the Age 50 sweep, and had ever lived in Scotland. The Scottish Medical Records database contains information about all hospital admissions in Scotland. This study concerns the Child Health Reviews (CHR) from first visit to school reviews.

Other datasets are available from the Scottish Medical Records database, these include:

• Prescribing Information System (PIS) held under SN 8710
• Scottish Immunisation and Recall System (SIRS) held under SN 8711
• Scottish Birth Records (SMR11) held under SN 8712
• Inpatient and Day Care Attendance (SMR01) held under SN 8713
• Outpatient Attendance (SMR00) held under SN 8714

Users

Gross expenditure on Research and Development in Scotland broken down by expenditure type (by Business, Government and/or Higher Education) - with UK and International comparisons.

Source agency: Scottish Government

Designation: National Statistics

Language: English

Alternative title: Gross Expenditure on Research and Development Scotland

The ABPE for Scotland are higher than the published MYE for 2016 and 2018, and very similar to the MYE for 2017. For all three years, the ABPE has more males than the MYE. In 2016 and 2018 the differences between the ABPE and MYE are larger for males than for females. Different age ranges show different patterns, although these patterns are roughly consistent over the three years: For young adults (aged around 18–25) the ABPE are generally higher than the MYE for females, and lower for males For those aged 30–65 there is little difference between the ABPE and MYE for females, but for males the ABPE is notably higher For those aged 67+ the ABPE for females and males are both lower than the MYE For young adults (aged around 18–25) the ABPE are generally higher than the MYE for females, and lower for males For those aged 30–65 there is little difference between the ABPE and MYE for females, but for males the ABPE is notably higher For those aged 67+ the ABPE for females and males are both lower than the MYE The ABPE is generally higher than the MYE in the most-deprived areas, and lower in the least-deprived areas. There is a higher difference between ABPE and MYE for males in the most-deprived areas. This is consistent throughout council areas, and in each of the three years. Males in the age range of 30–59 show the largest percentage differences. The ABPE is generally higher than the MYE in urban areas, and lower in rural areas.

Integrated statistical indicators that were retrieved from the official Scottish data portal in order to facilitate the exploitation of Machine Learning methods in Open Government Data. Data include 60 statistical indicators from seven categories such as health and social care, housing, and crime and justice. The indicators refer to the 6,976 “2011 data zones” of Scotland, while the year of reference is 2015. Data are ready to be used by the research community, students, policy makers, and journalists and give rise to plenty of social, business, and research scenarios that can be solved using Machine Learning technologies and methods.

This dataset is about books, has 3 rows and is filtered where the book publisher is Communities Scotland, Research Dept.. It features 7 columns including book, author, publication date, language, and book publisher. The preview is ordered by publication date (descending).

Abstract copyright UK Data Service and data collection copyright owner.

Scotland 2 - fieldwork completed during week of August 23-31, 1974. A quota sample of 976 individuals were interviewed in 36 constituencies.
Main Topics:

Demographics; party preferences; party affiliation and voting intention; the Scottish National Party; attitudes to the governance of Scotland; Scottish independence; Scottish Assembly/Parliament.

The Scottish Social Attitudes (SSA) survey was launched by ScotCen Social Research (formerly the Scottish Centre for Social Research) in 1999, following the advent of devolution. Based on annual rounds of interviews of between 1,200 to 1,500 people drawn using probability sampling (based on a stratified, clustered sample), it aims to facilitate the study of public opinion and inform the development of public policy in Scotland, similar to the British Social Attitudes (BSA) series (held at the Archive under GN 33168). The SSA survey has been conducted annually each year since 1999, with the exception of 2008. The survey has a modular structure. In any one year it typically contains three to five modules, each containing 40 questions. Funding for its first two years came from the Economic and Social Research Council, while from 2001 onwards different bodies have funded individual modules each year. These bodies have included the Economic and Social Research Council, the Scottish Government and various charitable and grant awarding bodies, such as the Nuffield Foundation and Leverhulme Trust.

Further information on the SSA and links to publications may be found on the ScotCen Social Research Scottish Social Attitudes webpages.

The 2012 survey was the 13th wave in the series. The sample included a boost of addresses in remote and rural parts of Scotland.

For the second edition (September 2013), data from the main Scottish Social Attitudes 2012 survey were added to the study, which previously contained only the data from questions covering constitutional change. The documentation has been updated accordingly.

This dataset was created in October-December 2022 for the National Library of Scotland's Data Foundry by Gustavo Candela, National Librarian’s Research Fellowship in Digital Scholarship 2022-23.

This output is based on the The National Bibliography of Scotland (version 2) dataset and is the result of the transformation to RDF described in a research article published in the Journal of Information Science.

For more information about the project, visit the Data Foundry Fellowship page.

References

Candela, G. (2023). Towards a semantic approach in GLAM Labs: The case of the Data Foundry at the National Library of Scotland. Journal of Information Science. https://doi.org/10.1177/01655515231174386

The dataset comprises 109 hydrographic data profiles, collected by a conductivity-temperature-depth (CTD) sensor package, from across the Inner Seas off the west coast of Scotland area including specifically the Minches area between the mainland and the Outer Hebrides, and the Scottish continental shelf. The data were collected during September of 1998. A complete list of all data parameters are described by the SeaDataNet Parameter Discovery Vocabulary (PDV) keywords assigned in this metadata record. The data were collected by the Fisheries Research Services Aberdeen Marine Laboratory.

Demonstration and Research Marine Protected Areas (MPAs) can be designated by Scottish Ministers under the Marine (Scotland) Act 2010. The boundaries of the Possible Demonstration and Research MPAs provided in this dataset represent the recommendation within the 12 nautical mile Territorial Sea limit. The following URL provides a link to further information on the Possible Demonstration and Research MPAs: www.scotland.gov.uk/Topics/marine/marine-environment/mpanetwork/DandRMPAsFor information regarding the wider MPA network in Scotland’s seas and protected areas management see: www.scotland.gov.uk/Topics/marine/marine-environment/mpanetwork,www.snh.gov.uk/mpasand www.jncc.defra.gov.uk/scottishmpas

About this dataset

Context

The dataset tabulates the Scotland population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Scotland.

Content

The dataset constitues the following two datasets across these two themes

• Scotland, SD Population Breakdown by Gender
• Scotland, SD Population Breakdown by Gender and Age

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

BBCE data for entrepreneurs by sectors for Burghs in Scotland 1851-1901. Detailed definitions and method given in WP 6. The downloads include the total number of the economically active population from the BBCE broken down by sector, sex, for employers, own-account proprietors, and workers. All data are weighted for census non-response bias in 1891-1901.

The data mart links data from (NHS 24, Scottish Ambulance Service, Out of Hours Primary Care, Emergency Department, Acute, Mental Health and Deaths) to show a Continuous Unscheduled Care Pathway (CUP) for records with a valid CHI number.

This dataset contains COVID-19 Vaccination events in Scotland since December 2020. This includes information such as eligibility cohort, date of vaccination, and vaccination product.

The dataset comprises 64 hydrographic data profiles, collected by a conductivity-temperature-depth (CTD) sensor package, taken at each trawling station from the Inner Seas off the west coast of Scotland, Irish Sea and St. George's Channel, and the North East Atlantic Ocean (limit 40W) areas including the specific locations: north and west coasts of Scotland; Irish Sea West Orkney; Butt of Lewis; Outer Hebrides; Inner Hebrides; South Minch; Clyde; North & West Ireland, Irish Sea. CTD casts taken during the month of March 2004. A complete list of all data parameters are described by the SeaDataNet Parameter Discovery Vocabulary (PDV) keywords assigned in this metadata record. The data were collected by the Fisheries Research Services Aberdeen Marine Laboratory.