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 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 75 (98.68% 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 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

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

Abstract copyright UK Data Service and data collection copyright owner. This research project examined the experiences of Irish lesbian, gay, bisexual and transgendered (LGBT) people living in London. There is a long history of Irish migration to the UK, particularly London. This has coincided historically with many Irish LGBT people feeling compelled to emigrate in search of a more supportive social climate. The appeal of global cities to LGBT people has long been acknowledged. Metropolitan centres are associated with tolerance of sexual diversity and established queer communities. This study will explore Irish queer migrants' reasons for moving to London and experiences there. The research questions will focus on notions of home, identity, belonging, familial relationships and subjectivity. By exploring the relationship between sexuality, ethnicity and diaspora, the study intended to uncover the ways in which contemporary sexual citizenship, migration and queer imaginaries of the metropolis are mutually implicated in complex ways. A qualitative dataset is produced containing interviews with 38 Irish LGBT participants who have been living in London for at least five years. In addition to generating new theoretical work on sexuality and migration, the research findings will be used to inform policy and debate regarding processes of social exclusion. Volunteer sample Face-to-face interview focus group

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.

Data collected between 2014 and 2016 from self-identified lesbian, gay, bisexual, trans and queer (LGBTQ) individuals in India and the UK. This data was collected at specific workshops held in India and the UK, and via the project's website (see Related Resources). The study used a 7 phase mixed methods design: 1. Project planning and research design, including formally establishing the advisory group and meeting 1, setting milestones and setting in place all agreements/ethical approvals 2. Literature review exploring key measures used to rate and assess LGBTQ 'friendliness'/inclusion nationally, supra-nationally and internationally 3. A spatial assessment of LGBTQ liveabilities that includes, but moves beyond, the measures identified in phase 2, applying these at a local scale e.g. policy indicators and place based cultural indicators 4. Twenty focus groups (80 participants, sample targeting marginalised LGBTQ people), coupled with online qualitative questionnaires (150), and shorter SMS text questionnaires (200)/App responses (200) to identify add to the liveability index created in phase 3 and what makes life un/liveable for a range of LGBTQ people and how this varies spatially 5. Participants in the data collection will be invited to reconfigure place through UK/India street theatre performances. These will be video recorded, edited into one short video and widely distributed. Data will be collected by observing interactions; on the spot audience surveys; reflections on the event 6. The research will analyse the data sets as they are collected. At the end of the data collection phase time will be taken to look across all 4 data sets to create a liveability index 7. Research dissemination will be targeted at community and academic audiences, including end of project conferences in India/UK, collating policy/community reports, academic outputs. The impact plan details the short (transnational support systems; empowerment of participants), medium (policy changes, inform practice) and long-term (changing perceptions of LGBTQ people) social impacts and how these will be achieved.The main research objective is to move beyond exclusion/inclusion of Lesbian, Gay, Bisexual, Trans, Queer (LGBTQ) communities in UK and India creating a liveability model that can be adapted globally. Whilst work has been done to explore the implications of Equalities legislation, including contesting the normalisations of neo-liberalisms, there has yet to be an investigation into what might make every day spaces liveable for LGBTQ people. This project addresses social exclusion, not only through identifying exclusions, but also by exploring how life might become liveable in everyday places in two very different contexts. In 2013 the Marriage (Same Sex) Act passed in the UK, and in India the Delhi High Court's reading down Indian Penal Code 377 in 2009 to decriminalize sexual acts between consenting same-sex people was overturned by the Supreme Court. Yet bullying, mental health and safety continue to be crucial to understanding British LGBTQ lives, in contrast the overturned the revoke of Penal Code 377 2013, this has resulted in increased visibilities of LGBTQ people. These different contexts are used to explore liveable lives as more than lives that are just 'bearable' and moves beyond norms of happiness and wellbeing. This research refuses to be fixed to understanding social liberations through the exclusion/inclusion, in place/out of place dichotomies. Using commonplace to move beyond 'in place' towards being common to the place itself. Place can then be shared in common as well as collectively made in ways that do not necessarily impose normative agendas/regulatory conditionalities. Social liberations are examined in the transformation of everyday encounters without conforming to hegemonies or making 'normal' our own. Whilst the focus is sexual and gender liberations, the project will enable considerations of others social differences. It will show how places produce differential liveabilities both where legislative change has been achieved and where it has just been repealed. Thus, the project offers academic and policy insights into safety, difference and vibrant and fair societies. Mixed-methods data generation via: a) Project workshops in the UK (including free writing; collage-making; timeline creation; local, national and global mapmaking; recorded individual interviews; recorded group discussions). b) Project workshops in India (including free writing; collage-making; timeline creation; individual written questionnaires; recorded group discussions). c) Individual In-Depth Interviews (IDIs) in India. d) Online surveys for registered members of Liveable Lives website. e) Bulletin board discussions for registered members of Liveable Lives website.

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

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

Police-reported hate crime, by type of motivation (race or ethnicity, religion, sexual orientation, language, disability, sex, age), selected regions and Canada (selected police services), 2014 to 2024.

This research project examined the experiences of Irish lesbian, gay, bisexual and transgendered (LGBT) people living in London. There is a long history of Irish migration to the UK, particularly London. This has coincided historically with many Irish LGBT people feeling compelled to emigrate in search of a more supportive social climate. The appeal of global cities to LGBT people has long been acknowledged. Metropolitan centres are associated with tolerance of sexual diversity and established queer communities. This study will explore Irish queer migrants' reasons for moving to London and experiences there. The research questions will focus on notions of home, identity, belonging, familial relationships and subjectivity. By exploring the relationship between sexuality, ethnicity and diaspora, the study intended to uncover the ways in which contemporary sexual citizenship, migration and queer imaginaries of the metropolis are mutually implicated in complex ways. A qualitative dataset is produced containing interviews with 38 Irish LGBT participants who have been living in London for at least five years. In addition to generating new theoretical work on sexuality and migration, the research findings will be used to inform policy and debate regarding processes of social exclusion.

The EU Lesbian, Gay, Bisexual and Transgender Survey (EU LGBT) was conducted by the European Union Agency for Fundamental Rights (FRA). It is the first ever EU-wide online survey to establish an overview concerning the lives of lesbian, gay, bisexual and trans people (18 years or older) and their experiences with regard to fundamental rights in the 28 EU Member States. Up until now, there has been very little comparable data collected across the EU about the everyday experiences of LGBT people with respect to discrimination, and lot of the available information is limited to occasional news reports and court judgements. As the first EU-wide survey of its kind, the results support the development of equal treatment policies for LGBT people in the European Union and set the agenda for years to come. Based on the survey results, national and European policy makers, as well as non-governmental organisations, are able to better target their advocacy strategies and activities to support LGBT communities to live and express themselves freely in a non-discriminatory environment. The survey was completely anonymous (no additional data on the participants and their sessions were logged in any way). The survey data collection operated by Gallup Europe, a professional survey and consultancy firm. In order to ensure that the survey delivers evidence needed for policy making, the EU LGBT Survey counted on the participation of a large and diverse group of lesbian, gay, bisexual and trans people from each country. Hence, it was vitally important for the success of the survey that FRA and Gallup worked together with civil society organisations to reach a wide audience and raise awareness concerning the survey, including participants emailing the survey, sharing it through social media or simply inviting LGBT friends to take part. More information can be found on the FRA website The data represents a self-selected sample and not a random sample. Please see technical report for details on data collection and dissemination of survey to potential respondents. Web-based survey

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

Why do unthreatening social groups become targets of state repression? Repression of LGBT people is especially puzzling since sexual minorities, unlike many ethnic minorities, pose no credible violent challenge to the state. This article contends that revolutionary governments are disproportionately oppressive toward sexual minorities for strategic and ideological reasons. Since revolutions create domestic instability, revolutionaries face unique strategic incentives to target “unreliable” groups and to demonstrate an ability to selectively punish potential dissidents by identifying and punishing “invisible” groups. Moreover, revolutionary governments are frequently helmed by elites with exclusionary ideologies. Exclusionary ideologies—such as communism, fascism, and Islamism—represent collectivities rather than individuals, and elites adhering to these views are likely to construct sexual minorities as liberal, individualistic threats to their collectivist projects. Statistical analysis using original data on homophobic repression demonstrates that revolutionary governments are more likely to target LGBT individuals and that this effect is driven by exclusionary ideologues. Case study evidence from Cuba further indicates that the posited strategic and ideological mechanisms mediate the relationship between revolutionary government and homophobic repression.

*Respondents could select more than one race.†Other race includes American Indians/Alaskan Native, Asians/Native Hawaiians/Pacific Islanders, and people reporting “other” race.‡Two respondents reported >10 male partners.§For this question, n = 777 because 3 respondents answered ‘don't know.’

*Respondents could select more than one race.†Other race includes American Indians/Alaskan Native, Asians/Native Hawaiians/Pacific Islanders, and people reporting “other” race.‡Five uncircumcised respondents did not provide data for the perceived risks and benefits statements, therefore N = 127.

PurposeIntimate partner violence (IPV) is becoming more recognized as a public health concern among sexual minority men, including bisexual and gay men. Guided by the Minority Stress Model, we assessed the relationship between perceived discrimination and three forms of IPV among a sample of bisexual and gay men living in the United States.MethodsWe analyzed data as part of the Men’s Body Project, a cross-sectional study launched in 2020 to assess health behaviors of bisexual and gay men.ResultsA total of 549 individuals participated in the survey, of which 52% were gay and 48% were bisexual men. Perceived discrimination was significantly associated with elevated odds ratios ranging from 1.15 to 1.18 across three forms of IPV, with Physical IPV odds ratio being highest.ConclusionGiven the significant association between perceived discrimination and IPV, interventions aimed at addressing IPV experiences among sexual minority men must consider the role of minority stress.

This research aims to offer better understanding of how lesbian, gay, bisexual and transgender (LGBT plus) employee networks are run and what they can do to improve relationships between colleagues, and ultimately, improve the wellbeing of LGBT employees. In doing so, the research focuses on LGBT employee networks within the NHS in nine different institutions by administering surveys, interviewing network members and taking part in network activities. The National Health Service Human Resources and Equality Diversity and Inclusion survey (NHS HR & EDI Survey) is an online survey of the organisational culture and workforce structure at NHS trusts in England. The survey required one response per trust from Human Resources (HR) staff and/or Equality, Diversity and Inclusion (EDI) leads working in NHS trust in England.In recent years, the British workplace has become more diverse. Lesbian, gay, bisexual and transgender (LGBT) individuals form an important part of this diversity. Most large organisations have established LGBT employee networks to support gender and sexual minorities and run training programs to inform employees about equality and diversity related matters. Despite this, we still know little about LGBT networks and why adversity against this group of employees has not yet been stamped out. To address this problem, this project aims to offer better understanding of how LGBT networks are run and what they can do to improve relationships between colleagues, and ultimately, improve the wellbeing of LGBT employees. In doing so, we focus on LGBT employee networks within the NHS in nine different institutions by administering surveys, interviewing network members and taking part in network activities. To achieve our research aims, the following objectives have been set: 1) Establish baseline understanding of how LGBT employee networks operate; 2) Map network membership and explore ways of addressing insufficient representation of different groups within the networks; 3) Explore what support is in place to achieve network's vision and what barriers exists to realise this vision; 4) Examine ways of using LGBT employee networks to address negativity towards sexual and gender minorities more effectively. With support from our research partners, NHS Employers; Stonewall; Employers Network for Equality & Inclusion (enei); a theatre production team and through our academic networks, the results of the research will be published, debated and applied to target LGBT employees in and outside of the NHS, HR practitioners, policy makers, and scholars in the field of diversity in organisations, and gender and sexualities studies together with the general public. Research outputs include an APP connecting LGBT employee networks, practitioners report and academic journal articles. They further include a dedicated website hosting discussion forums and social media activities, on the road regional workshops, national and international conference presentations, a press conference and a theatre production. Project outcomes will further help to shape programs delivered by enei to public, private and third sector organisations, and to support ongoing campaigns on behalf of Stonewall to improve work experiences of LGBT employees.

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.

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).

IntroductionAmong US men, oropharyngeal cancer (cancer of the back of the mouth and throat) is the 8th most common cancer. If detected early, human papillomavirus (HPV)-16-associated oropharyngeal cancer has a high 5-year survival rate. Risk factors such as high numbers of oral sex partners, disparities in smoking and drinking, and low rates of HPV vaccination may put gay and bisexual men at even higher risk for oropharyngeal cancer.MethodsWe recruited 21 healthcare providers in Minneapolis-St. Paul, Minnesota and Houston, Texas to participate in semi-structured interviews. Nurses, physician assistants, dental hygienists, and dentists were asked about their clinical experiences serving gay and bisexual men and opinions on potential interventions for the early detection of oropharyngeal cancer.ResultsProviders typically did not tailor health screenings and examinations for gay and bisexual men. Participants lacked confidence in their ability to effectively implement routine screening for oropharyngeal cancer. The extent to which oropharyngeal cancer screening was incorporated into clinical practice varied by specialty, and practices necessary to detect it were scattered across clinical environments. HIV- and LGBTQ-focused healthcare providers were more aware of HPV-associated oropharyngeal cancer in gay and bisexual men, and appeared readier to act and lead on this issue.DiscussionFurther studies should (1) evaluate protocols for oropharyngeal cancer detection; (2) identify and assess the acceptability of screening in the community; and (3) study how to best close gaps in health services for gay and bisexual men which might contribute to low early detection rates of oropharyngeal cancer.