About this dataset

Context

The dataset tabulates the population of Gay by race. It includes the population of Gay across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Gay across relevant racial categories.

Key observations

The percent distribution of Gay population by race (across all racial categories recognized by the U.S. Census Bureau): 60.48% are white, 38.71% are some other race and 0.81% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Gay
• Population: The population of the racial category (excluding ethnicity) in the Gay is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gay total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gay Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Gay Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Gay, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Gay.

Key observations

Among the Hispanic population in Gay, regardless of the race, the largest group is of Mexican origin, with a population of 48 (100% of the total Hispanic population).

Content

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

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Gay
• Population: The population of the specific origin for Hispanic or Latino population in the Gay is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Gay total Hispanic or Latino population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gay Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Gays by race. It includes the distribution of the Non-Hispanic population of Gays across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Gays across relevant racial categories.

Key observations

With a zero Hispanic population, Gays is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 165 (96.49% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Gays
• Population: The population of the racial category (for Non-Hispanic) in the Gays is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gays total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gays Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Gays by race. It includes the population of Gays across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Gays across relevant racial categories.

Key observations

The percent distribution of Gays population by race (across all racial categories recognized by the U.S. Census Bureau): 94.80% are white and 5.20% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Gays
• Population: The population of the racial category (excluding ethnicity) in the Gays is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gays total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gays Population by Race & Ethnicity. You can refer the same here

Sexual orientation in the UK by region, sex, age, legal partnership status, and ethnic group. These are official statistics in development.

Analysis of ‘What Do Men Think It Means To Be A Man?’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/masculinity-surveye on 28 January 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

This directory contains data behind the story What Do Men Think It Means To Be A Man?.

masculinity-survey.csv contains the results of a survey of 1,615 adult men conducted by SurveyMonkey in partnership with FiveThirtyEight from May 10-22, 2018. The modeled error estimate for this survey is plus or minus 2.5 percentage points. The percentages have been weighted for age, race, education, and geography using the Census Bureau’s American Community Survey to reflect the demographic composition of the United States age 18 and over. Crosstabs with less than 100 respondents have been left blank because responses would not be statistically significant.

The data is available under the Creative Commons Attribution 4.0 International License and the code is available under the MIT License. If you do find it useful, please let us know.

Source: https://github.com/fivethirtyeight/data

This dataset was created by FiveThirtyEight and contains around 200 samples along with Adult Men, No Children, technical information and other features such as: - Age 35 64 - Race White - and more.

How to use this dataset

• Analyze Sexual Orientation Gay/ Bisexual in relation to Has Children
• Study the influence of Race Non White on Age 18 34
• More datasets

Acknowledgements

If you use this dataset in your research, please credit FiveThirtyEight

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

An induction of disgust can lead to more negative attitudes toward an entire social group: Participants who were exposed to a noxious ambient odor reported less warmth toward gay men. This effect of disgust was equally strong for political liberals and conservatives, and was specific to attitudes toward gay men—there was only a weak effect of disgust on people's warmth toward lesbians, and no consistent effect on attitudes toward African Americans, the elderly, or a range of political issues.

The LGBTQI+ Dataset 2020-2022_es is a collection of 410,015 original tweets extracted from the social network Twitter between January 1, 2020, and December 31, 2022. To ensure data quality and relevance, retweets, replies, and other duplicate content were excluded, retaining only original tweets. The tweets were collected by Jacinto Mata (University of Huelva, I2C/CITES) with the support of the Python programming language and using the twarc2 tool and the Academic API v2 of Twitter. Tbis data collection is part of the project “Conspiracy Theories and Hate Speech Online: Comparison of patterns in narratives and social networks about COVID-19, immigrants and refugees and LGBTI people [NON-CONSPIRA-HATE!]”, PID2021-123983OB-I00, funded by MCIN/AEI/10.13039/501100011033/ by FEDER/EU.

The search criteria (words and hashtags) used for the data collection followed the objectives of the aforementioned project and were defined by Estrella Gualda, Francisco Javier Santos Fernández and Jacinto Mata (University of Huelva, Spain). Terms and hashtags used for the search and extraction of tweets were: #orgullogay, #orgullotrans, #OrgulloLGTB, #OrgulloLGTBI, #Díadelorgullo, #TRANSFOBIA, #transexuales, #LGTB, #LGTBI, #LGTBIQ, #LGTBQ, #LGTBQ+, anti-gay, "anti gay", anti-trans, "anti trans", "Ley Anti-LGTB", "ley trans", "anti-ley trans".

This dataset collected in the frame of the NON-CONSPIRA-HATE! project had the aim of identifying and mapping online hate speech narratives and conspiracy theories towards LGBTIQ+ people and community. Additionally, the dataset is intended to compare communication patterns in social media (rhetoric, language, micro-discourses, semantic networks, emotions, etc.) deployed in different datasets collected in this project. This dataset also contributes to mapping the actors, communities, and networks that spread hate messages and conspiracy theories, aiming to understand the patterns and strategies implemented by extremist sectors on social media. he dataset includes messages that address a wide range of topics related to the LGBTQI+ community, such as rights, visibility, the fight against discrimination and transphobia, as well as debates surrounding the Trans Law and other related issues. It includes expressions of support and celebration of Pride as well as hate speech and opposition to LGBTQI+ rights, along with debates and controversies surrounding these issues.

This dataset offers a wide range of possibilities for research in various disciplines, as the following examples express:

Social Sciences & Digital Humanities:
- Analysis of opinions, attitudes, and trends toward the LGBTIQ+ people and community.
- Studies on the evolution of public discourse and polarization around issues such as transphobia, hate speech, disinformation, LGBTIQ+ rights and pride, and others.
- Analysis on social and political actors, leaders or organizations disseminating diverse narratives on LGBTIQ+
- Research on the impact of specific events (e.g., Pride Day) on social media conversations.
- Investigations on social and semantic networks around LGBTIQ+ people and community.
- Analysis of narratives, discourses and rethoric around gender identity and sexual diversity.
- Comparative studies on the representation of the LGBTIQ+ people and community in different cultural or geographic contexts.

Computer Science and Artificial Intelligence:
- Development of algorithms for the automatic detection of hate speech, discriminatory language, or offensive content.
- Training natural language processing (NLP) models to analyze sentiments and emotions in texts related to the LGBTIQ+ people and community.

For more information on other technical details of the dataset and the structure of the .jsonl data, see the “Readme.txt” file.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Gays. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Gays, the median household income for the households where the householder is White decreased by $12,758(19.18%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $66,508 in 2013 and $53,750 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in Gays, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Gays.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 Gays median household income by race. You can refer the same here

In early February 2024, we will be retiring the Mpox Case Summary dataset. This dataset will be archived and no longer update. A historic record of this data will remain available.

A. SUMMARY This dataset represents probable and confirmed mpox cases per CDC case definitions among San Francisco residents reported to the San Francisco Department of Public Health. Data are lagged by 4 days, based on the most recent date a case is received by the source system.

B. HOW THE DATASET IS CREATED Case information is based on confirmed or probable positive laboratory tests reported to the San Francisco Department of Public Health. Processes to provide quality assurance and other data verification are completed before the data are reported.

These data may not be immediately available for recently reported cases because of the time needed to process tests and validate cases. Data are continually updated to maximize completeness of information and reporting on San Francisco residents with confirmed or probable mpox.

To ensure data privacy, we suppress data when cumulative counts are between 1-4. The exception to this rule is for the response option “Unknown” which does not provide any identifying information. If only one response option has a count <5 we also suppress the response option with the second lowest count (including “Unknown” or a response option with a count of 0). If the second lowest response option is 0, both response options will display “<5”. If the second lowest response option is a number greater than 0 both response options will display “< [sum of two lowest counts]”.

Data notes for population characteristic types are listed below.

Race/ethnicity * The response option "Other" is categorized by the source system, and the response option "Unknown" refers to a lack of data.

Gender * The response option "Other" is categorized by the source system, and the response option "Unknown" refers to a lack of data.

Sexual orientation * The response option "Other" is categorized by the source system, and the response option "Unknown/Declined" refers to a lack of data or those who did not disclose their sexual orientation. * The response option “Gay, Lesbian, or Same-Gender Loving” is a standard reporting option and cannot be split into individual categories. This is a limitation of the data from the source system.

Sexual contact during incubation period * We track whether mpox cases had sexual contact during the 21 days prior to symptom(s) onset. This timeframe is the incubation period. * The response option "Unknown/Declined" refers to a lack of data or those who did not disclose their sexual contact history.

For convenience, we provide the 2020 5-year American Community Survey population estimates.

C. UPDATE PROCESS Updates to the data are made through automated and manual processes Monday through Friday.

D. HOW TO USE THIS DATASET This dataset shows total cases (probable and confirmed) by population characteristics. Filter the “characteristic_type” column to explore a topic area. Then, the “characteristic_group” column shows each group or category within that topic area and the total count of cases identified within that population subgroup.

E. CHANGE LOG

• 1/4/2023: Due to low case numbers, this page will no longer include cases after 12/31/2022.

Socioeconomic characteristics of the population aged 15 and older that is Two-Spirit, lesbian, gay, bisexual, transgender, and queer or who use other terms related to gender or sexual diversity (2SLGBTQ+), by gender, age group and geographic region. Marital status, presence of children under age 12 in the household, education, employment, personal income, Indigenous identity, the visible minority population, immigrant status, language(s) spoken most often at home, place of residence (population centre/rural), self-rated general health, and self-rated mental health. Estimates are obtained from combined cycles of the Canadian Community Health Survey, 2019 to 2021.

About this dataset

Context

The dataset tabulates the population of Gays Mills by race. It includes the population of Gays Mills across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Gays Mills across relevant racial categories.

Key observations

The percent distribution of Gays Mills population by race (across all racial categories recognized by the U.S. Census Bureau): 89.25% are white, 0.17% are American Indian and Alaska Native, 0.69% are some other race and 9.88% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Gays Mills
• Population: The population of the racial category (excluding ethnicity) in the Gays Mills is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gays Mills total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gays Mills Population by Race & Ethnicity. You can refer the same here

Socioeconomic characteristics of the population aged 15 and older whose reported sexual orientation is lesbian or gay, bisexual or pansexual, or another sexual orientation that is not heterosexual (LGB+), by gender, age group and geographic region. Marital status, presence of children under age 12 in the household, education, employment, personal income, Indigenous identity, the visible minority population, immigrant status, language(s) spoken most often at home, place of residence (population centre/rural), self-rated general health, and self-rated mental health. Estimates are obtained from combined cycles of the Canadian Community Health Survey, 2019 to 2021.

Background: Gay, bisexual, and other men who have sex with men (GBM) experience systemic marginalization and many barriers to healthcare, leading to significant healthcare disparities. It was unknown if they were more vulnerable to COVID-19, and if a failure to respond to their unique physical and mental health needs would exacerbate existing health disparities. The Engage-COVID-19 study leveraged the larger Engage Cohort Study conducted by researchers studying HIV and sexual health among GBM based at Canadian universities, public health, and community organizations. Aims of the CITF co-funded study: The study aimed to identify biomedical, behavioural, and psychosocial risk factors for contracting COVID-19, document SARS-CoV-2 immunity in HIV positive and negative participants, and characterize the clinical syndrome and severity of those with immunity. It also aimed to understand the application and understanding of COVID-19 mitigation strategies in GBM and investigate the impact of the pandemic on mental health, loneliness, sexual behaviours, substance use patterns, and access to essential healthcare. [1] Methods: This cohort study recruited individuals across Vancouver, British Columbia, Toronto, Ontario, and Montreal, Quebec who self-identified as a gay or bisexual man, including transgender GBM, and who reported having sex with another man in the past 6 months. Participants in the COVID-19 sub-study provided blood samples and responded to questionnaires in two waves of data collection, over the span of approximately 21 months. Contributed dataset contents: The datasets include 2,518 participants who completed baseline questionnaires since Feb 2017. A total of 1,564 participants had study visits during the Engage COVID-19 data collection period (09/2020–06/2022), and gave one or more blood samples in the same timeframe. A total of 2,719 serology samples were collected. Variables include data in the following areas of information: demographics (age, gender, ethnicity and indigeneity), general health (smoking; chronic disease diagnoses; flu vaccine), SARS-CoV-2 vaccination, adherence to COVID-19 prevention public health guidelines (physical distancing, remote working, wearing a mask), and serology. [1]: Please contact original study team for these mental health and behaviour data (daniel.grace@utoronto.ca).

This project uses data on same-gendered households (via the 2016 Australian Census) and cohabitation rates (via behavioural population surveys) to estimate the total number and prevalence of gay men and lesbian women living across Australia and in each postcode. The data and code for generating relevant outputs and analyses are contained here.(i) Stock datasets [Files: remoteness2012.dta; postcode_clusters.dta] This item contains files required to organize the Australian Census data: (i) the 'remoteness' classifications per the Australian Statistical Geography Standard (Australian Bureau of Statistics, 2011), and (ii) clustering of those postcodes with base total populations of less than 200 people. The clustering process was undertaken manually by reviewing postcodes in that bracket and combining them with neighboring postcodes within the same jurisdictions and remoteness classification until the threshold of 200 was met. Preference was given for clustering postcodes that shared the largest geographic border and/or with the smallest population sizes.(ii) Underlying datasets [Files: pop_sex_0-9.xlsx; pop_sex_10-19.xlsx; pop_sex_18.xlsx; pop_sex_19.xlsx; pop_sex_20-24.xlsx; pop_sex_25-29.xlsx; pop_sex_all.xlsx; ss_couples_all.xlsx]This item contains tables created by and extracted from the Australian Bureau of Statistics 'TableBuilder' platform, which allows access to and organization of aggregate data from the 2016 Australian Census. The tables exist in two groups (i) total number of Census participants, stratified by postcode, age group and gender, and (ii) total number of same-gendered households, stratified by postcode and gender.(iii) Organizational code [File: generate dataset and analysis.do]This file contains the code (Stata, version 15.0) to organize the 'underlying datasets' and combine them with information collated from behavioral survey data. To account for remoteness classification via the Australian Statistical Geography Standard, it merges by postcode on a separate 'stock dataset' (remoteness2012). To account for clustering of postcodes with small overall populations, it merges by postcode on a separate 'stock dataset' (postcode_clusters). The code additionally produces outcomes of descriptive analyses and relevant tables, and generates a final dataset of, by-postcode, population sizes and prevalences.(iv) Final dataset [File: Appendix B - dataset.xlsx]This final dataset contains organized, merged and interpreted outcomes, presented as variables of, by-postcode, the estimated absolute number and prevalence of gay men and lesbian women in Australia. A data dictionary is included.

About this dataset

Context

The dataset tabulates the population of Fort Gay by race. It includes the population of Fort Gay across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Fort Gay across relevant racial categories.

Key observations

The percent distribution of Fort Gay population by race (across all racial categories recognized by the U.S. Census Bureau): 97.60% are white and 2.40% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Fort Gay
• Population: The population of the racial category (excluding ethnicity) in the Fort Gay is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Fort Gay total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Fort Gay Population by Race & Ethnicity. You can refer the same here

These datasets provide Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales by sexual orientation by sex, sexual orientation by age and sexual orientation by sex and age.

LGB+

An abbreviation used to refer to people who identify as lesbian, gay, bisexual, and other minority sexual orientations (for example, asexual).

_Sexual orientation _

Sexual orientation is an umbrella term covering sexual identity, attraction, and behaviour. For an individual respondent, these may not be the same. For example, someone in an opposite-sex relationship may also experience same-sex attraction, and vice versa. This means the statistics should be interpreted purely as showing how people responded to the question, rather than being about whom they are attracted to or their actual relationships.

We have not provided glossary entries for individual sexual orientation categories. This is because individual respondents may have differing perspectives on the exact meaning.

The question on sexual orientation was new for Census 2021. It was voluntary and was only asked of people aged 16 years and over.

In total, 44.9 million people answered the sexual orientation question (92.5% of the population aged 16 years and over).

Usual resident

A usual resident is anyone who on Census Day, 21 March 2021, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more or had a permanent UK address.

Notes

• To ensure that individuals cannot be identified in the data, population counts have been rounded to the nearest five and counts under 10 have been suppressed.

• Percentages have been calculated using rounded data.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Gays Mills by race. It includes the distribution of the Non-Hispanic population of Gays Mills across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Gays Mills across relevant racial categories.

Key observations

Of the Non-Hispanic population in Gays Mills, the largest racial group is White alone with a population of 489 (92.79% of the total Non-Hispanic population).

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Gays Mills
• Population: The population of the racial category (for Non-Hispanic) in the Gays Mills is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Gays Mills total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gays Mills Population by Race & Ethnicity. You can refer the same here

This dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project. The SOERE PRO is a French research observatory on organic residues recycling in agriculture. It is a network of long-term field experiments, including QualiAgro and PROspective devices, which has been created to evaluate benefits and risks associated with organic residue (OR) application in agriculture. It has been certified as SOERE PRO (a network of long-term experiments dedicated to the study of impacts of organic waste product recycling) in 2011 and 2015 by ALLENVI (Alliance Nationale de Recherche pour l'Environnement). Since 2014, it has also been integrated as a service of the ‘‘Investment for future’’ infrastructure AnaEE-France, overseen by the French National Research Agency (ANR-11-INBS-0001). In 2018, it has been certified as Collective Scientific Infrastructure by the INRA (National Institute for Agricultural Research). QualiAgro which has been initiated in 1998 is located in the Paris Bassin. The objectives are to characterize the agronomic value of composts from the urban origin and their environmental impacts. The field experimental design is a complete randomized block experiment with 450 m² plots and four replicates of five organic treatments: three urban composts (municipal solid waste, MSW; green waste and sludge, GWS; biowaste, BIOW), farmyard manure as organic control treatment (FYM) and a control without organic inputs (CN). QualiAgro data included in the H2020 Landmark project were the physico-chemical properties of soils sampled in 2015, field management practices and yields for the period 2010-2015. PROspective which has been initiated in 2000 is located in Colmar (Est of France). The objectives are to characterize the agronomic value of composts and the environmental impacts of 3 different types of ORs frequently amended in Est of France and to highlight the composting effect on these impacts. PROspective data included in the H2020 Landmark project were the physico-chemical properties of soils sampled in 2018, field management practices and yields for the period 2014-2018. 2 tables provided by France are available: One table of fact-gathering the results of the chemical and physical analyses of the soil profiles and monitoring. One table of fact-gathering the results of the cultural management practices related to soil data. Both tables are connected with the same id attribute. To link soil data to management practices, you just need to use the "profile_id" of the soil table and the "management_id" of the management table. For soil data, the same id may come more than one time if multiple layers are described. Moreover, the names of the crops have been coded into the management table with the "Eurostat Handbook for Annual Crop Statistics (Regulation (EC) No 543/2009, Commission Delegated Regulation (EU) 2015/1557 and ESS agreement for Annual Crop Statistics) - Revision 2017 - (Released 9 February 2017)". All the codes and their meaning are into the table "eurostat_crops_list".

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During July-August 2008 NOAA completed hydrographic survey H11922 west of Gay Head, Massachusetts, in Rhode Island Sound and during July and September 2010 bottom photographs and surficial sediment data were acquired as part of ground-truth reconnaissance surveys of this area. Interpretations were derived from the multibeam echo-sounder data and the ground-truth data used to verify them. For more information on the ground-truth surveys see http://quashnet.er.usgs.gov/data/2010/10033/ and http://quashnet.er.usgs.gov/data/2010/10005/