About this dataset

Context

The dataset tabulates the Gay population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Gay across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Gay was 116, a 4.13% decrease year-by-year from 2022. Previously, in 2022, Gay population was 121, an increase of 5.22% compared to a population of 115 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Gay decreased by 37. In this period, the peak population was 153 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Gay is shown in this column.
• Year on Year Change: This column displays the change in Gay population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Year. You can refer the same here

The survey asked lesbian, gay, bisexual and transgender (LGBT) people whether they had experienced discrimination, violence, verbal abuse or hate speech on the grounds of their sexual orientation or gender identity. The results reflect the experiences of more than 93,000 individuals who completed the online survey across Europe.

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

This report, Coming out in the Kingdom: Lesbian, gay, bisexual and transgender people in Cambodia, is an output of the LGBT Rights Project implemented by the Cambodian Center for Human Rights. The Report uses the LGBT terminology to discuss the situation of LGBT people in Cambodia, it is important to bear in mind that such terminology is new for Cambodian society, including LGBT individuals themselves, who may not identify themselves as lesbian, gay, bi‐sexual or transgender (as discussed in Section 2 of this Report). The concepts of sexual orientation and gender identitythat have developed in the West may not do justice to the flexible way sexuality is perceived in Cambodia. Accordingly, another challenge to advancing LGBT rights in Cambodia is finding the appropriate language to use when engaging in dialogue with Cambodians about sexual orientation and gender identity.

Sexual identity estimates by occupation 2014. This is presented at a UK level, and broken down by England, Wales, Scotland and Northern Ireland.

Objective. Support for gay rights has increased in the publics of many countries over recent decades, but the scholarship on the topic has been hindered by the limited available data on these trends in public opinion. The goal of the Support for Gay Rights (SGR) dataset is to overcome this problem. Method. The SGR dataset is constructed by combining a comprehensive collection of survey data with a latent-variable model to provide annual time-series estimates of public support for gay rights across 118 countries and over as many as 51 years that are comparable across space and time. Results. We show these data perform well in validation tests and demonstrate their potential by replicating the influential but recently questioned finding of Andersen and Fetner (2008) that more income inequality yields less tolerant and supportive attitudes toward gay people. Conclusion. We anticipate that the SGR data will become a crucial source for cross-national, cross-regional, and longitudinal research that improves our understanding of the sources and consequences of public support for gay rights.

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Gay, the largest racial group is White alone with a population of 84 (98.82% 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 Gay
• Population: The population of the racial category (for Non-Hispanic) 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 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 Gay Population by Race & Ethnicity. You can refer the same here

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.Only residents age 16+ were asked this question. Residents age 15 or less are not included in the data.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.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsSexual OrientationThis dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales by sexual orientation. The estimates are as at Census Day, 21 March 2021. This dataset includes information for Leicester City and England overall.Definition: Classifies people according to the responses to the sexual orientation question. This question was voluntary and was only asked of people aged 16 years and over.

Name: LGBTQIAphobia_dataset_augmented_balanced
Description: Labeled dataset with phrases retrieved from different digital sources (X/twitter, Instagram, TikTok) containing diverse messages directed towards the LGBTQIA+ community. It has 1000 phrases classified as {Non-LGBTQIAphobic (0), LGBTQIAphobic (1)} . It is the balanced version of LGBTQIAphobia_dataset_augmented.
Language: Spanish
Format: CSV (UTF-8)
Structure: id; phrase; class {0,1}
Purpose: Be used for fine-tuned models that detect language offensive to Spanish or Latin LGBT communities in digital environments.
Sources: X/Twitter, Instagram, TikTok, Youtube comments
Size: 20Kb
Ethical considerations: This dataset was created strictly for academic and research purposes. We oppose any type of digital violence, in this case, against the LGBTQIA+ community. The person who was the target of the hate speech has been anonymised, and there is no intention to harm them in any way, either them or the person who delivered the speech. We prioritise the protection of the privacy and confidentiality of vulnerable individuals. To safeguard privacy, we carefully remove any identifying details, such as user IDs, phone numbers, and addresses, before sharing the data with our annotators. All the data we collect is from publicly available sources and does not contain any personal or sensitive information that may jeopardise anyone’s privacy. I request researchers to commit to abiding by ethical guidelines so as not to unnecessarily harm individuals.
¿How was it created?
- Starting recovery of discriminatory phrases for the LGBTQIA+ community from X/Twitter, Instagram, and Tiktok (197 phrases).
- Labelling by 3 raters as non-LGBTphobic (0) and LGBTphobic (1).
- Text augmentation was applied through backtranslation and random synonym replacement.
- Translating to Spanish part of McGiff, J., & Nikolov, N. S. (2024) dataset and was added under licence CC-BY-4.0
- To balance the majority class, we applied the undersampling technique.
- Finally, we obtained 1000 tagged phrases for version 1.0.2 of LGBTQIAphobia_augmented_balanced

Class distribution

class

 instances

0

513

1

487

where class is
0: non-lgbtphobic
1: lgbtphobic

This table presents a socio-demographic and socio-economic statistical profile of the population aged 15 and older by sexual orientation, geographic region, sex and age group. The characteristics included are: marital status, presence of children under 12 in the household, education, employment, household income, Indigenous identity, belonging to a population group designated as a visible minority, language(s) spoken at home, and place of residence (urban/rural). These estimates are obtained from Canadian Community Health Survey, 2015 to 2018 pooled data.

Cities are in constant competition for residents, business and employees and inclusiveness is an important factor that attracts all three. The Municipal Equality Index (MEI) specifically measures laws and policies of municipalities to examine how inclusive cities are of LGBTQ (Lesbian, Gay, Bisexual, Transgender and Questioning) people.Administered by the Human Rights Campaign, the MEI scorecard criteria annually evaluates a municipality on six categories with bonus points available: Non-Discrimination Laws: This category evaluates whether discrimination on the basis of sexual orientation and gender identity is prohibited by city, county or state in areas of employment m housing and public accommodations.Relationship Recognition: Marriage, civil unions, and comprehensive domestic partnerships are matters of state policy; cities and counties have only the power to create domestic partner registries.Municipality as Employer: By offering equivalent benefits and protections to LGBTQ employees, and by awarding contracts to fair-minded businesses, municipalities commit themselves to treating LGBTQ employees equally.Municipal Services: The section assesses the efforts of the city to ensure LGBTQ constituents are included in city services and programs.Law Enforcement: Fair enforcement of the law includes responsible reporting of hate crimes and engaging with the LGBTQ community in a thoughtful and respectful way.Relationship with the LGBTQ Community: This category measures the city leadership’s commitment to fully include the LGBTQ community and to advocate for full equality.Additional information available at hrc.org/meiThis page provides data for the Municipality Equality Index performance measure.The performance measure dashboard is available at 3.12 Municipal Equality Index.Additional InformationSource: Contact: Wydale HolmesContact E-Mail: wydale_holmes@tempe.govData Source Type: ExcelPreparation Method: Publish Frequency: Annually, OctoberPublish Method: ManualData Dictionary

Abstract copyright UK Data Service and data collection copyright owner.

The Northern Ireland Life and Times Survey (NILT) series began in 1998, and was the successor to the previous Northern Ireland Social Attitudes series, which was discontinued in 1996.
The main aims of the NILT series are:

• to monitor public attitudes towards social policy and political issues in Northern Ireland;
• to provide a time series on attitudes to key social policy areas;
• to facilitate academic social policy analysis;
• to provide a freely available resource on public attitudes for the wider community of users in Northern Ireland.

NILT originally had a companion series which also began in 1998, the Young Life and Times Survey (YLT), although the YLT methodology changed in 2003 and it is conducted separately each year. The Kids' Life and Times (KLT) survey of P7 children (10-11 year olds) is also part of the same suite of surveys as YLT and NILT.

NILT also forms part of the International Social Survey Programme (ISSP), although it does not do so every year. Unfortunately, NILT did not run in 2011 due to funding issues, though YLT ran as normal that year; NILT resumed in 2012 (SN 7408). In addition, several open access teaching datasets were created by ARK (Access Research Knowledge) from various years of NILT, covering different topics such as Lesbian, Gay, Bisexual and Transgender (LGBT) issues, politics and community relations, attitudes to ageing and ageism, and dementia.

Further information about the series may be found on the ARK NILT webpage.

SPSS Dataset and Codebook for survey of LGBT people conducted December 22, 2021 - January 17, 2022. The survey was approved by California Polytechnic State University IRB on November 14, 2021. IRB #2021-221-OL. Funding to conduct this survey was awarded through the California Polytechnic State University Research Scholarly and Creative Activities (RSCA) Grant Program administered by the Cal Poly division of Research, Economic Development & Graduate Education. The material contained in this collection include an anonymized dataset and codebook, a methodological appendix, statistical appendix, and supplemental online appendix for the book Yes Gawd! How Faith Shapes LGBT Identity and Politics (Temple University Press).

About this dataset

Context

The dataset tabulates the Gay household income by gender. The dataset can be utilized to understand the gender-based income distribution of Gay income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Gay, GA annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Gay, GA annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Gay income distribution by gender. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Fort Gay. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Fort Gay, the median income for all workers aged 15 years and older, regardless of work hours, was $18,125 for males and $21,071 for females.

Contrary to expectations, women in Fort Gay, women, regardless of work hours, earn a higher income than men, earning 1.16 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

Contrary to expectations, in Fort Gay, women, earn a higher income than men, earning 1.13 dollars for every dollar earned by men. This analysis showcase a consistent trend of women outearning men, when working full-time or part-time in the town of Fort Gay.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

The Generations study is a five-year study designed to examine health and well-being across three generations of lesbians, gay men, and bisexuals (LGB). The study explored identity, stress, health outcomes, and health care and services utilization among LGBs in three generations of adults who came of age during different historical contexts. This collection includes baseline, wave 1, and wave 2 data collected as part of the Generations study. The study aimed to assess whether younger cohorts of LGBs differed from older cohorts in how they viewed their LGB identity and experienced stress related to prejudice and everyday forms of discrimination, as well as whether patterns of resilience differed between different LGB cohorts. Additionally, the study sought to examine how differences in stress experience affected mental health and well-being, including depressive and anxiety symptoms, substance and alcohol use, suicide ideation and behavior, and how younger LGBs utilized LGB-oriented social and health services, relative to older cohorts. In wave 2, respondents were re-interviewed approximately one year after completion of the baseline (wave 1) survey. Only respondents who participated in the original sample of participants were surveyed at wave 2 (i.e., the enhancement oversample was not included in the longitudinal design of this study). In wave 3, respondents were re-interviewed approximately one year after the completion of the wave 2 survey. Demographic variables collected as part of this study include questions related to age, education, race, ethnicity, sexual identity, gender identity, income, employment, and religiosity.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Gay. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Gay, the median income for all workers aged 15 years and older, regardless of work hours, was $38,558 for males and $33,750 for females.

Based on these incomes, we observe a gender gap percentage of approximately 12%, indicating a significant disparity between the median incomes of males and females in Gay. Women, regardless of work hours, still earn 88 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.34 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Gay. The dataset can be utilized to gain insights into gender-based income distribution within the Gay population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Gay, among individuals aged 15 years and older with income, there were 51 men and 43 women in the workforce. Among them, 41 men were engaged in full-time, year-round employment, while 17 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 17.07% fell within the income range of under $24,999, while 5.88% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 12.20% of men in full-time roles earned incomes exceeding $100,000, while none of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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 median household income by race. 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.

!!!WARNING~~~This dataset has a large number of flaws and is unable to properly answer many questions that people generally use it to answer, such as whether national hate crimes are changing (or at least they use the data so improperly that they get the wrong answer). A large number of people using this data (academics, advocates, reporting, US Congress) do so inappropriately and get the wrong answer to their questions as a result. Indeed, many published papers using this data should be retracted. Before using this data I highly recommend that you thoroughly read my book on UCR data, particularly the chapter on hate crimes (https://ucrbook.com/hate-crimes.html) as well as the FBI's own manual on this data. The questions you could potentially answer well are relatively narrow and generally exclude any causal relationships. ~~~WARNING!!!For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 8 release notes:Adds 2019 and 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last UCR hate crime data they release. Changes .rda file to .rds.Version 7 release notes:Changes release notes description, does not change data.Version 6 release notes:Adds 2018 dataVersion 5 release notes:Adds data in the following formats: SPSS, SAS, and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Adds data for 1991.Fixes bug where bias motivation "anti-lesbian, gay, bisexual, or transgender, mixed group (lgbt)" was labeled "anti-homosexual (gay and lesbian)" prior to 2013 causing there to be two columns and zero values for years with the wrong label.All data is now directly from the FBI, not NACJD. The data initially comes as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. All work to clean the data and save it in various file formats was also done in R. Version 4 release notes: Adds data for 2017.Adds rows that submitted a zero-report (i.e. that agency reported no hate crimes in the year). This is for all years 1992-2017. Made changes to categorical variables (e.g. bias motivation columns) to make categories consistent over time. Different years had slightly different names (e.g. 'anti-am indian' and 'anti-american indian') which I made consistent. Made the 'population' column which is the total population in that agency. Version 3 release notes: Adds data for 2016.Order rows by year (descending) and ORI.Version 2 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The Hate Crime data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains information about hate crimes reported in the United States. Please note that the files are quite large and may take some time to open.Each row indicates a hate crime incident for an agency in a given year. I have made a unique ID column ("unique_id") by combining the year, agency ORI9 (the 9 character Originating Identifier code), and incident number columns together. Each column is a variable related to that incident or to the reporting agency. Some of the important columns are the incident date, what crime occurred (up to 10 crimes), the number of victims for each of these crimes, the bias motivation for each of these crimes, and the location of each crime. It also includes the total number of victims, total number of offenders, and race of offenders (as a group). Finally, it has a number of columns indicating if the victim for each offense was a certain type of victim or not (e.g. individual victim, business victim religious victim, etc.). The only changes I made to the data are the following. Minor changes to column names to make all column names 32 characters or fewer (so it can be saved in a Stata format), made all character values lower case, reordered columns. I also generated incident month, weekday, and month-day variables from the incident date variable included in the original data.