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 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

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

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.

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.

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.

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.

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

Context

Every year, along with the State-Sponsored Homophobia report, ILGA World publishes also maps of sexual orientation laws in the world.

https://ilga.org/maps-sexual-orientation-laws

Content

A useful tool for LGB human rights defenders, these images expose the arbitrariness of persecutory laws, and starkly indicate the absence of positive law in most parts of the world.

https://ilga.org/maps-sexual-orientation-laws

Acknowledgements

https://ilga.org/maps-sexual-orientation-laws

Photo by Sharon McCutcheon on Unsplash

Inspiration

LGBTQIA community.

"The negative attitudes and feelings toward homosexuality or people who are identified or perceived as being lesbian, gay, bisexual or transgender (LGBT). The prejudice, aversion, hatred or antipathy, may be based on irrational fear and ignorance, and is often related to religious beliefs against LGBTQIA community." https://en.wikipedia.org/wiki/Homophobia

Cities are in constant competition for residents, businesses, and employees, and inclusiveness is a crucial 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 evaluate a municipality on six categories, with bonus points available: Non-Discrimination Laws: This category evaluates whether discrimination based on 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 Information Source: Contact: Wydale HolmesContact E-Mail: wydale_holmes@tempe.govData Source Type: ExcelPreparation Method: Publish Frequency: Annually, OctoberPublish Method: ManualData Dictionary

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.

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

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

LGBT HateSpeech Comments Dataset (Korean)

Background

Hate speech becomes a major social issue, breaking our relationships and threating our society members. However, in most Korean datasets about hate speech, there're very few samples related to LGBT(and other minorities, too).

Content

This dataset contains the contents column and label column, 1 labeled as "hate speech" and 0 as negative samples(NOT-Hatespeech comments).

Data gathering & Tagging

Train Data

• Hate Speech (label 1): Augmented dataset with user information - comments in target news, who spoke the hate speech previously(in relevant news articles)
• Non-hate speech (label 0): BEEP Paper, non-biased, non-hate speech in trainset ( from https://www.kaggle.com/c/korean-hate-speech-detection/overview )

Test Data

• Hate Speech (label 1): HateSpeech tagged by researcher
• Non-Hate speech (label 0): Non-hate speech or pro-LGBT texts tagged by researcher + BEEP Paper, non-biased, non-hate speech in dev set ( from https://www.kaggle.com/c/korean-hate-speech-detection/overview )

Acknowledgements

This dataset has NOT cross-validated by several researchers. This dataset will be updated with another validation.

The EU LGBTI II survey is a large-scale web-administered survey of the experiences and views of lesbian, gay, bisexual, transgender and intersex (LGBTI) individuals, using an anonymous online questionnaire. The survey was conducted between 27 May and 22 July 2019 via the platform www.lgbtisurvey.eu and collected valid responses from 139 799 participants from the European Union (EU) Member States, North Macedonia and Serbia. The survey provides comparative evidence on how LGBTI people in the EU experience discrimination, violence and harassment in various areas of life, including employment, education, healthcare, housing and other services.

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).

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.

The survey was carried out by the ZHAW, Department of Social Work (project manager: Peter Streckeisen), as a mandate by the Pink Cross Association. The latter is the largest organization of gay and bisexual men in Switzerland. Pink Cross wanted to carry out a survey among their members and other gay, bi and queer men in order to better understand their perception of their own community and to have an insight into their relationships and some areas of their living conditions.

Marginalized groups face major challenges in mobilizing the public, including how to frame their own identities. Should groups emphasize how similar they are to the dominant majority? Or can they focus on what makes them different without losing support? And do these frames affect internal communities and outsider allies in different ways? These questions have been particularly fraught for the LGBTQ movement, which has oscillated between presenting themselves as “just like” straight people and stressing the distinctiveness of LGBTQ identities. In this paper, I test the effectiveness of these identity frames with a unique survey experiment. Separate samples of LGBT and straight cisgender respondents were shown appeals from a (fictitious) LGBTQ interest group. The appeal emphasized either LGBTQ similarities with, or differences from, straight identities. Contrary to pre-registered expectations, how the group framed their identity had no effect on interest in joining the group’s action, views of its politics, or beliefs about its effectiveness. This was true for LGBT and straight cisgender respondents alike. Although claims about the importance of identity framing are commonplace in the literature, this suggests that the choice between emphasizing similarities or differences may have fewer consequences for contemporary LGBTQ groups.