Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_893df0c34cf86a6df6f6be6768faf680/view

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

These statistics relate to students enrolled in tertiary education providers by a range of demographic and other characteristics.

The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for Leicester and compare this with national statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsEthnicityThis dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.Definition: The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.Respondents could choose one out of 19 tick-box response categories, including write-in response options.This dataset includes data relating to Leicester City and England overall.

Why does ethnic violence occur in some places but not others? This paper argues that the local ethnic configuration below the national level is an important determinant of how likely conflict is in any particular place. Existing studies of ethnicity and conflict focus on national-level fractionalization or dominance, but much of the politics surrounding ethnic groups’ grievances and disputes takes place at a more local level. We argue that the existence of multiple ethnic groups competing for resources and power at the level of sub-national administrative regions creates a significant constraint on the ability of states to mitigate ethnic groups’ grievances. This in turn increases the likelihood of conflict between ethnic groups and the state. In particular, we argue that diverse administrative regions dominated by one group should be most prone for conflict. Using new data on conflict and ethnic group composition at the region level, we test the theory and find that units with one demographically dominant ethnic group among multiple groups are most prone to conflict.

From 1995, the General Household Survey (GHS) is conducted in between 2 Population Censuses as a mid-decade mini-Census.

The General Household Survey (GHS) 2015 is the third in the series of mid-decade national survey. It covers a wide range of topics and provides comprehensive data on Singapore’s population and households in between the population censuses that are conducted once in ten years.

Dataset from Housing & Development Board. For more information, visit https://data.gov.sg/datasets/d_b553c9286f58ba96ef0ee1088743da52/view

Community Specific Profiles are grouped by race and ethnicity. We measure by race, ethnicity, and other demographics to understand the specific needs of different communities and evaluate effective service delivery and accountability. This dataset is the groupings used to combine projects with multiple levels and types of data standards. These include the minimum and comprehensive race and ethnicity categories from the City of Portland Rescue Plan Data Standards. They also include race and ethnicity categories in the HUD HMIS data standards.-- Additional Information: Category: ARPA Update Frequency: As Necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=60968

Accepted for publication in Cooperation and Conflict. Includes do-file and data-file (stata) as well as online appendix.

This statistic shows the share of ethnic groups in Australia in the total population. 33 percent of the total population of Australia are english.

Australia’s population

Australia’s ethnic diversity can be attributed to their history and location. The country’s colonization from Europeans is a significant reason for the majority of its population being Caucasian. Additionally, being that Australia is one of the most developed countries closest to Eastern Asia; its Asian population comes as no surprise.

Australia is one of the world’s most developed countries, often earning recognition as one of the world’s economical leaders. With a more recent economic boom, Australia has become an attractive country for students and workers alike, who seek an opportunity to improve their lifestyle. Over the past decade, Australia’s population has slowly increased and is expected to continue to do so over the next several years. A beautiful landscape, many work opportunities and a high quality of life helped play a role in the country’s development. In 2011, Australia was considered to have one of the highest life expectancies in the world, with the average Australian living to approximately 82 years of age.

From an employment standpoint, Australia has maintained a rather low employment rate compared to many other developed countries. After experiencing a significant jump in unemployment in 2009, primarily due to the world economic crisis, Australia has been able to remain stable and slightly increase employment year-over-year.

The most common blood type among the population in the United States is O-positive. Around 53 percent of the Latino-American population in the U.S. has blood type O-positive, while only around 37 percent of the Caucasian population has this blood type. The second most common blood type in the United States is A-positive. Around 33 percent of the Caucasian population in the United States has A-positive blood type. Blood type O-negative Those with blood type O-negative are universal donors as this type of blood can be used in transfusions for any blood type. O-negative blood type is most common in the U.S. among Caucasian adults. Around eight percent of the Caucasian population has type O-negative blood, while only around one percent of the Asian population has this blood type. Only around seven percent of all adults in the United States have O-negative blood type. Blood Donations The American Red Cross estimates that someone in the United States needs blood every two seconds. However, only around three percent of age-eligible people donate blood yearly. The percentage of adults who donated blood in the United States has not fluctuated much for the past two decades. In 2021, around 15 percent of U.S. adults donated blood, the same share reported in the year 2003.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study examined differences in youth's mental health and substance abuse needs in seven different racial/ethnic groups of justice-involved youth. Using de-identified data from the Survey of Youth in Residential Placement (SYRP), it was assessed whether differences in mental health and substance abuse needs and services existed in a racially/ethnically diverse sample of youth in custody. Data came from a nationally representative sample of 7,073 youth in residential placements across 36 states, representing five program types. An examination of the extent to which there were racial/ethnic disparities in the delivery of services in relation to need was also conducted. This examination included assessing the differences in substance-related problems, availability of substance services, and receipt of substance-specific counseling. One SAS data file (syrp2017.sas7bdat) is included as part of this collection and has 138 variables for 7073 cases, with demographic variables on youth age, sex, race and ethnicity. Also included as part of the data collection are two SAS Program (syntax) files for use in secondary analysis of youth mental health and substance use.

Working with partners across NIH, led by NIMHD and the NLM OBSSR-Behavioral Ontology Working Group, MeSH on November 29, 2022 added Federally recognized American Indian and Alaskan Native (AI/AN) tribal names and ethnic/ethnolinguistic minority terms as newly created type 5 SCR designated as “Population Groups”. These minority names (1,700+ terms) were mapped and reviewed by subject matter experts and scientists within NIH and from outside including Network of the National Library of Medicine members. Structure: All type 5 SCRs have common fields 1. CC=5 Population Group 2. ST=T098 Population Groups 3. HM= At least one HM is to an MH under Population Groups [M01.686] 4. TH= NIMHD(2023)

From 1995, the General Household Survey (GHS) is conducted in between 2 Population Censuses as a mid-decade mini-Census.

The General Household Survey (GHS) 2015 is the third in the series of mid-decade national survey. It covers a wide range of topics and provides comprehensive data on Singapore’s population and households in between the population censuses that are conducted once in ten years.

This study describes how racial/ethnic group differences in self-neglect incidence varied across metropolitan and rural regions of Texas. The data included 134,538 cases of self-neglect validated by adult protective services among people 65+ years old from 2020 to 2023. We aggregated county population figures from US Census Bureau estimates and used negative binomial regression models to estimate the association of race/ethnicity, gender, and region type with self-neglect case counts. Self-neglect incidence among Black older adults was about twice that of White older adults, a difference that persisted across metropolitan regions. Black-White differences were more pronounced in Northwest rural regions but were absent in the El Paso region. Hispanic-White differences varied across both metropolitan and rural regions. In the Arlington region, for example, self-neglect incidence among Hispanic older adults was less than that of White older adults, whereas in San Antonio it was greater. Addressing self-neglect among Black and Hispanic older adults should anticipate that different communities may require distinct approaches. Future studies with more geographic units should build on this descriptive study to explain variation in racial/ethnic group differences in self-neglect incidence.

39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

This table contains data on all people who have been arrested by the police as suspects of crimes and who also appear in the Municipal Personal Records Database (GBA). Detained suspects whose personal data are not included in the GBA are not included in this table. The table shows per population group in absolute and relative figures how many suspects of crimes there are. The relative figures indicate how many people per 1,000 people of the selected population group are suspected of committing a crime. The population groups can be selected by origin, age group and gender. The suspects can also be distinguished according to the type of crime they are suspected of. Persons suspected of multiple types of crimes are listed in a separate category. The data concern suspects and not convicts. It is estimated that more than 90% of the suspects are offered a transaction by the Public Prosecution Service (OM) or are declared guilty by the court at a later stage. The data on the suspects come from the Herkenningsdienstsystemen (HKS) of the police. Data are available from 1999. Status of the figures: The figures up to and including 2009 are final. The figures for 2010 and 2011 are provisional. The HKS is updated annually with new and improved data. For example, persons who turned out to be falsely suspected are removed from the HKS. In addition, registration backlogs are cleared. 2010 is expected to change slightly. The number of suspects in 2011 will in reality be higher than the number presented in the table. When will new figures become available: This table has been discontinued on 11-01-2013 and continued as Suspects; gender, age, ethnic group and type of crime

This data package consists of 26 datasets all containing statistical data relating to the population and particular groups within it belonging to different countries, mostly the United States.

This dataset includes information on mental health and addiction services (care) provided by secondary organisations funded by Te Whatu Ora (and prior to 1 July 2022, the Ministry of Health). Specifically, it covers demographic and geographic information, client referral pathways, the types of services provided, the outcome of the services and legal status and diagnosis information.