The dataset contains 18,944 entries with columns for Entity (country/region), Code (ISO code), Year, and Population estimates. Each row represents the population estimate for a specific country and year, spanning from 1950 to recent years, capturing global demographic changes over time.

According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.

Wellbeing statistics: 2021 (supplementary) presents supplementary data from the 2021 General Social Survey (GSS), adding to the data released in Wellbeing statistics: 2021 in July 2022.

The United States had a population of 76.3 million people in 1900. Approximately 67 million of these were white, of whom the majority were native born, while most of the remaining nine million people were Black. At this time, the United States Census included persons of Hispanic origin along with its white population, however the Hispanic share of the population in 1900 was much lower than it is today.

DaKultur: Evaluating the Cultural Awareness of Language Models for Danish with Native Speakers

This repository covers the anonymized dataset + optional demographic information from the cultural evaluation study "DaKultur" (Müller-Eberstein et al., 2025). It includes the following fields:

input: The user input, prompting the models for knowledge of Danish culture. output_[ID]: The output generated by one of the evaluated models. judgment_[ID]: The user's judgment of the model's… See the full description on the dataset page: https://huggingface.co/datasets/NLPnorth/dakultur-demographics.

Data on ethnic or cultural origin by gender and age for the population in private households in Canada, provinces and territories, and census subdivisions with 5,000-plus population.

Explore demographic data on the Massachusetts executive branch workforce. Track our progress toward our goals to reflect the diversity of the people we serve, and to stand out as an employer of choice.

Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students

About Dataset

The dataset you provided, titled "Report Card Enrollment 2023-24 School Year," appears to be a comprehensive collection of information regarding student enrollment and demographics within educational institutions for the specified academic year. Here are some observations about the dataset:

1. Granularity: The dataset seems to be quite granular, providing detailed information not only about overall student enrollment but also about various demographic categories such as gender, race/ethnicity, English language learners, students with disabilities, and socioeconomic status.

2. Demographic Diversity: It captures the diversity of the student population by including counts for various racial/ethnic groups, as well as categories such as gender X, indicating a recognition of diverse gender identities.

3. Socioeconomic Indicators: The dataset includes indicators of socioeconomic status such as students in foster care, homeless students, and those from low-income families, which can provide insights into equity and access issues within the educational system.

4. Special Education and Gifted Programs: It tracks the enrollment of students with disabilities and those identified as highly capable, which are important metrics for evaluating the inclusivity and effectiveness of special education and gifted programs.

5. Geographical Context: The dataset includes information about the county, educational service district, and school district, providing a geographical context for the enrollment data.

6. Temporal Aspect: The "DataAsOf" column indicates that the data has a temporal aspect, suggesting that it may be periodically updated to reflect changes in enrollment and demographics throughout the academic year.

**columns : ** SchoolYear: Indicates the academic year for which the data is reported, in this case, it's 2023-24.

OrganizationLevel: Specifies the level of educational organization, which could be school, district, or any other relevant level within the educational system.

County: Refers to the county where the educational organization is located.

ESDName: Stands for Educational Service District Name, which represents the intermediate level of educational administration in some states.

ESDOrganizationID: ID assigned to the Educational Service District.

DistrictCode: Code assigned to the district within the educational system.

DistrictName: Name of the school district.

DistrictOrganizationId: ID assigned to the district organization.

SchoolCode: Code assigned to the school within the district.

SchoolName: Name of the school.

SchoolOrganizationID: ID assigned to the school organization.

CurrentSchoolType: Indicates the current type of the school, such as elementary, middle, or high school.

GradeLevel: Specifies the grade level(s) served by the school.

All Students: Total number of enrolled students in the school.

Female: Number of female students enrolled.

Gender X: Number of students who identify as gender X, indicating a non-binary or non-conforming gender identity.

Male: Number of male students enrolled.

American Indian/ Alaskan Native: Number of students identifying as American Indian or Alaskan Native.

Asian: Number of students identifying as Asian.

Black/ African American: Number of students identifying as Black or African American.

Hispanic/ Latino of any race(s): Number of students identifying as Hispanic or Latino of any race.

Native Hawaiian/ Other Pacific Islander: Number of students identifying as Native Hawaiian or other Pacific Islander.

Two or More Races: Number of students identifying as belonging to two or more races.

White: Number of students identifying as White.

English Language Learners: Number of students who are learning English as a second language.

Foster Care: Number of students in foster care.

Highly Capable: Number of students identified as highly capable or gifted.

Homeless: Number of students experiencing homelessness.

Low-Income: Number of students from low-income families.

Migrant: Number of students from migrant families.

Military Parent: Number of students with parents serving in the military.

Mobile: Number of students who frequently change residences.

Section 504: Number of students covered under Section 504 of the Rehabilitation Act, which provides accommodations for students with disabilities.

Students with Disabilities: Number of students with disabilities.

Non-English Language Learners: Number of students who are not learning English as a second language.

Non-Foster Care: Number of students who are not in foster care.

Non-Highly Capable: Number of students who are not identified as highly capable or gifted.

Non-Homeless: Number of students wh...

Author: Joseph Kerski, post_secondary_educator, Esri and University of DenverGrade/Audience: high school, ap human geography, post secondary, professional developmentResource type: lessonSubject topic(s): population, maps, citiesRegion: africa, asia, australia oceania, europe, north america, south america, united states, worldStandards: All APHG population tenets. Geography for Life cultural and population geography standards. Objectives: 1. Understand how population change and demographic characteristics are evident at a variety of scales in a variety of places around the world. 2. Understand the whys of where through analysis of change over space and time. 3. Develop skills using spatial data and interactive maps. 4. Understand how population data is communicated using 2D and 3D maps, visualizations, and symbology. Summary: Teaching and learning about demographics and population change in an effective, engaging manner is enriched and enlivened through the use of web mapping tools and spatial data. These tools, enabled by the advent of cloud-based geographic information systems (GIS) technology, bring problem solving, critical thinking, and spatial analysis to every classroom instructor and student (Kerski 2003; Jo, Hong, and Verma 2016).

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

This web map summarizes racial and ethnic diversity in the United States. The Diversity Index shows the likelihood that two persons chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity). The diversity score for the entire United States in 2010 is 60. This data variable is included in Esri’s Updated Demographics (2010/2015). Diversity in the U.S. population is increasing. The states with the most diverse populations are California, Hawaii, and New Mexico. This map shows Esri's 2010 estimates using Census 2000 geographies. The geography depicts States at greater than 25m scale, Counties at 1m to 25m scale, Census Tracts at 250k to 1m scale, and Census Block Groups at less than 250k scale.Esri's Updated Demographics (2010/2015) – Population, age, income, sex, and race are among the variables included in the database. Each year, Esri's data development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of geographies. See Updated Demographics for more information. Information about the USA Diversity Index map service used in this map is here.

This table provides statistical information about people in Canada by their demographic, social and economic characteristics as well as provide information about the housing units in which they live.

Diversity index information by neighborhoods in Johns Creek, GA.Neighborhood boundaries are created and maintained by Johns Creek, GA.Demographics data is from Esri GeoEnrichment Services.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Census Division (CD) and Census Subdivision (CSD) level data from the 2021 Census Program. Includes most of the information released as part of the Complete Profiles for the Ethnic Diversity and Religions release. Due to the complexity of the data, changes were made to the field names in order to accommodate the limitations of the database. This makes some uses harder as it requires careful use of the field names and totals to provide accurate values and analysis.

Dataset

This dataset was created by Research Zone

Released under CC0: Public Domain

Contents

Cultural_Diversity_Org_Performance

Experimental statistics for population estimates by ethnic group broken down into age and sex at a national regional level for England and Wales.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

A data set of all employees that have previously worked for, currently work for, or who were offered employment by the Town of Gilbert highlighting demographics. This data set contains the following information for each individual. Names and any identifiable information have been removed from this data set.ID - A unique identifier for each record. This ID is not the employee ID of the individual.Department - The department that the individual works in and is assigned to in the organization.Division - The division within the main department in which the individual works and is assigned to.Organization - The internal organization or work group in which the individual works.Active Status Code - Whether the individual is currently active in the organization. An inactive employee may have previously been employed by Gilbert or may have been offered employment but never hired. Inactive employees are listed as "I" and active employees are listed as "A".Gilbert Resident - Whether the individual's primary residence is in Gilbert. Gilbert residents are listed as "Y" while all others are listed simply as "N".Employee Status - The type of position and status of the individual. Possible options for Employee Status include "Elected", "Full Time Sworn", "Full Time Non-Sworn", "Limited Term", "Part Time 0.5 Non-Benefited", "Part Time 0.75 Benefited", and "Seasonal".Degree Code - The highest level of educational degree attained by the individual. Options are "Associate", "Bachelor's", "Doctorate", "Elementary", "GED", "High School", "Juris Doctor", "Master's", "Master of Laws" or blank (if the individual chose not to respond)."Ethnicity" - The self-identified race or ethnicity of the individual. Possible choices are "Asian", "Black", "Hispanic", "Native American", "Other", "White", or "N/A" (if the individual was offered employment but never hired). Gilbert does not currently differentiate race from ethnicity when hiring.Age Group - The age group to which the individual belongs. Age groups include "Under 18", "18-24", "25-34", "35-44", "45-54", "55-64", "65+", and "N/A" (if the individual was offered employment but never hired).Gender - The self-identified gender of the individual. Genders in the data include "Female", "Male", and "N/A" (if the individual was offered employment but never hired).This data set is updated on the 15th of every month and the last day of every month.