Important notice

The Office for Statistics Regulation confirmed on 12/09/2024 that the gender identity estimates from Census 2021 are no longer accredited official statistics and are classified as official statistics in development.

For further information please see: Sexual orientation and gender identity quality information for Census 2021

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

Gender identity

Gender identity refers to a person's sense of their own gender, whether male, female or another category such as non-binary. This may or may not be the same as their sex registered at birth.

Non-binary

Someone who is non-binary does not identify with the binary categories of man and woman. In these results the category includes people who identified with the specific term "non-binary" or variants thereon. However, those who used other terms to describe an identity that was neither specifically man nor woman have been classed in "All other gender identities".

Sex

This is the sex recorded by the person completing the census. The options were "Female" and "Male".

Trans

An umbrella term used to refer to people whose gender identity is different from their sex registered at birth. This includes people who identify as a trans man, trans woman, non-binary or with another minority gender identity.

Trans man

A trans man is someone who was registered female at birth, but now identifies as a man.

Trans woman

A trans woman is someone who was registered male at birth, but now identifies as a woman.

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 and was outside the UK and intended to be outside the UK for less than 12 months.

Notes:

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

• Percentages have been calculated using rounded data.

About this dataset

Context

The dataset tabulates the population of Howell by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Howell. The dataset can be utilized to understand the population distribution of Howell by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Howell. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Howell.

Key observations

Largest age group (population): Male # 25-29 years (672) | Female # 20-24 years (700). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Howell population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Howell is shown in the following column.
• Population (Female): The female population in the Howell is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Howell for each age group.

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 Howell Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of West Plains by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for West Plains. The dataset can be utilized to understand the population distribution of West Plains by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in West Plains. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for West Plains.

Key observations

Largest age group (population): Male # 25-29 years (579) | Female # 35-39 years (570). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the West Plains population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the West Plains is shown in the following column.
• Population (Female): The female population in the West Plains is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in West Plains for each age group.

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 West Plains Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Clarkston by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Clarkston. The dataset can be utilized to understand the population distribution of Clarkston by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Clarkston. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Clarkston.

Key observations

Largest age group (population): Male # 30-34 years (320) | Female # 0-4 years (345). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Clarkston population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Clarkston is shown in the following column.
• Population (Female): The female population in the Clarkston is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Clarkston for each age group.

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 Clarkston Population by Gender. You can refer the same here

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.

Selected socioeconomic characteristics of the transgender or non-binary population aged 15 and older, by age group. Marital status, presence of children under age 12 in the household, education, employment, personal income, Indigenous identity, the visible minority population, immigrant status, language(s) spoken most often at home, place of residence (population centre/rural), self-rated general health, and self-rated mental health. Estimates are obtained from combined cycles of the Canadian Community Health Survey, 2019 to 2021.

The 2015 U.S. Transgender Survey (USTS) was conducted by the National Center for Transgender Equality (NCTE) to examine the experiences of transgender adults in the United States. The USTS questionnaire was administered online and data were collected over a 34-day period in the summer of 2015, between August 19 and September 21. The final sample included respondents from all fifty states, the District of Columbia, American Samoa, Guam, Puerto Rico, and U.S. military bases overseas. The USTS Public Use Dataset (PUDS) features survey results from 27,715 respondents and details the experiences of transgender people across a wide range of areas, such as education, employment, family life, health, housing, and interactions with police and prisons. The survey instrument had thirty-two sections that covered a broad array of topics, including questions related to the following topics (in alphabetical order): accessing restrooms; airport security; civic participation; counseling; family and peer support; health and health insurance; HIV; housing and homelessness; identity documents; immigration; intimate partner violence; military service; police and incarceration; policy priorities; public accommodations; sex work; sexual assault; substance use; suicidal thoughts and behaviors; unequal treatment, harassment, and physical attack; and voting. Demographic information includes age, racial and ethnic identity, sex assigned at birth, gender and preferred pronouns, sexual orientation, language(s) spoken at home, education, employment, income, religion/spirituality, and marital status.

This collection comprises mixed-methods data from a study exploring the use of abusive behaviours by partners in same-sex, bisexual and/or transgender relationships and practitioners' accounts of and perspectives on developing suitable and inclusive interventions for, and responses to, perpetrators of domestic violence and abuse in same-sex, bisexual and/or transgender relationships. In recent years in the UK there has been recognition that domestic violence and abuse (DVA) takes place in same-sex, bisexual and/or transgender relationships and a parallel and emerging body of research which has begun to explore and develop understandings about how and why this occurs, and whether and how victim/survivors seek help. However, despite this growing literature, there has been no dedicated research on those who are the abusive partners in same-sex, bisexual and/or trans relationships, and consequently there has been little evidence to inform the development of services to address their behaviours. This study, which we have named the Coral Project, is the first UK study to collect data specifically about the perpetration of violent and abusive behaviours in lesbian, gay, bisexual and/or transgender (LGB and/or T) relationships. The aims of the Coral Project were to: explore similarities and differences across sexuality and gender of those who enact ‘abusive’ behaviours in LGB and/or T and heterosexual relationships; do this with those who have enacted ‘abusive’ behaviours as well as practitioners who provide interventions for predominantly heterosexual male perpetrators; explore what methods might work best to elicit data to address these aims; and share key findings with key stakeholders to develop best practice guidance for work with those who use ‘abusive’ behaviours in LGBT relationships. A mixed-methods approach was taken in order to gather both quantitative and qualitative data about the use of abusive behaviours in same-sex, bisexual and/or transgender relationships through a national online survey and follow-up in-depth interviews with volunteers from the survey, respectively. Semi-structured interviews and focus groups with practitioners were also conducted in order to elicit practitioners’ understandings of the use of abusive behaviours within LGB and/or T relationships and their views on the suitability of existing domestic violence perpetrator interventions (designed primarily for heterosexual men) for addressing the abusive behaviour of LGB and/or T individuals, as well as what to find out about the nature of any current provision for LGB and/or T perpetrators and barriers to developing LGB and/or T interventions. This is a mixed-methods study involving a quantitative survey (n=872), individual interviews with selected survey respondents (n=36), interviews with practitioners involved in the design and delivery of services for domestic violence and abuse perpetrators (n=23), and focus groups with practitioners in a range of field including domestic violence services, LGBT support services, relationship support and counselling and education (n=8).

This study explores the relationship between gender identity and the use of creaky voice (a non-modal phonation commonly referred to as "vocal fry.") While early research suggested that men were more likely to use creaky voice, more recently its use has been associated with the language use of young, urban, American women. This study explores the relationship between creaky voice and gender identity in American English, and investigates the social stratification of creaky voice for additional social factors like sexual orientation, age, and socioeconomic status. Production and perception data were gathered from 69 participants with a range of gender identities (including men, women, and non-binary individuals, as well as individuals who identify as both cis and trans) in 2013. The dataset contains audio files and tabular data.

Human sexuality is a complex reality, characterised by gender identity and sexual orientation. A widespread approach to study human sexuality is to compare groups with opposite sexual gender identity and sexual orientation such as cisgenders vs transgenders and heterosexuals vs homosexuals. Cisgenderism refers to individuals whose sense of gender identity corresponds to their natal sex, while transgenderism is characterized by an incongruity between biological sex and psychological gender with cross-gender identification. Heterosexuality refers to those who feel an emotional, romantic or sexual attraction towards the opposite sex, while homosexuality is characterized by an emotional, romantic or sexual attraction towards same sex individuals. Neuroimaging studies have found brain differences between these groups of individuals. Nevertheless, their results are conflicting, and limitations such as small samples' sizes and the considerable overlap between such groups, makes it difficult to draw accurate conclusions. This systematic review and meta-analysis explored structural, functional and metabolic features of the 'cisgender brain' compared with the 'transgender brain' before hormonal treatment and the 'heterosexual brain' compared to the 'homosexual brain' from the analysis of the neuroimaging literature. Processing the information that conform this dataset suggests that neuroanatomy, neurophysiology and neurometabolism in transgenders resemble those of their natal sex rather than those of their experienced gender and in homosexuals these resemble those of their same sex heterosexual population rather than their opposite sex heterosexual population. However, the small number of studies that contributed data, their small sample size, the incompleteness of the data, and the heterogeneity of the investigations that were included in this systematic review do not allow drawing general conclusions. This dataset contains all data extracted from the publications included, as well as the search strategy and the results of processing the information extracted from the articles

Additional file 3. Title: Data used for meta-analyses of mean differences. Description: Data used for meta-analyses of mean differences.

This study undertakes an analysis of the conceptualization of gender identity in neuroscientific studies of (trans)gender identity that contrast the brains of cisgender and transgender participants. The analysis focuses on instances of epistemic injustice that combine scientific deficiencies and the exclusion of relevant bodies of knowledge. The results of a content analysis show how the ignoring of biosocial, developmental, mosaicist, contextualist, and depathologizing approaches leads to internal conceptual inconsistencies, hermeneutical deficiencies and the upholding of questionable paradigms in the research field. Interviews with researchers involved in these brain studies reveal targeted and diffuse forms of testimonial injustice against alternative approaches, promoted by the hierarchical arrangements of research teams in combination with the careerist and economic logic of research. The analysis points to the exclusion of critical epistemologies of science and the historical oppression of trans people as epistemic agents as the underlying hermeneutical deficiencies.

This is a search hedge for identifying transgender and gender nonconforming individuals in the medical literature. This search hedge is NOT validated. The notes field contains the Ovid search for Medline. The file in this dataset contains the full MEDLINE (Ovid), Embase (OVID), PsycInfo (OVID) and CINAHL (Ebsco) searches (2024-10-30)

This data set contains EIIHA populations who received services funded by Ryan White Part A Grant. EIIHA is Early Identification of Individuals with HIV/AIDS (EIIHA) The special populations (EIIHA) with HIV are: Black MSM = Black men and Black transgender women who have sex with men. Latinx MSM = Latinx men and Latinx Transgender women who have sex with men. Black Women - Black women Transgender - Transgender men and women. These populations have the biggest disparities of people living with HIV. Other data is the number of clients and units used in each service category in the Ryan White Part A, a grant that provides services for those with HIV.

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

This data set includes tables on persons living with HIV/AIDS, newly diagnosed HIV cases and all cause deaths in HIV/AIDS cases by gender, age, race/ethnicity and transmission category.

In all tables, cases are reported as of December 31 of the given year, as reported by January 9, 2019, to allow a minimum of 12 months reporting delay.

Gender is determined by both current gender and sex at birth variables; transgender values are assigned when current gender is identified as "Transgender" or when a discrepancy is identified between a person's sex at birth and their current gender (e.g., cases where sex at birth is "Male" and current gender is "Female" will become Transgender: Male to Female.) Prior to 2003, Asian and Native Hawaiian/Pacific Islanders were classified as one combined group. In order to present these race/ethnicities separately, living cases recorded under this combined classification were split and redistributed according to their expected proportional population representation estimated from post-2003 data.

PurposeTransgender (TG) women face violence, discrimination, and stigma, which affect their mental health and hinder their access to targeted intervention (TI) services. This lack of access may increase the risk of human immunodeficiency virus/sexually transmitted infections (HIV/STIs). However, the utilization of TI services among transgender women in Uttarakhand, as well as across the country, remains understudied. The purpose of this study is to explore the utilization of TI services by the transgender community in Uttarakhand.MethodsThis qualitative study focused on non-government organizations (NGOs) that implement TI projects in Haridwar and Roorkee, Uttarakhand, India. From September 2023 to January 2024, 5 focus group discussions (FGDs) involving 24 transgender women and 9 in-depth interviews (IDIs) involving NGO staff were conducted. Thematic analysis, guided by the Anderson and Newman healthcare utilization model, was employed.ResultsSeveral barriers to service utilization were identified, including ritual beliefs, low health literacy, stigma, social isolation, financial insecurity, privacy concerns, and inefficient service delivery. Challenges in the implementation of the STI program and neglect of transgender women in health facilities were also reported. However, enabling factors such as trusted providers, supportive laws, and initiatives by NGOs and government agencies were recognized. Nonetheless, there remains a significant need for information on gender-affirming services and addressing other prevalent health issues within the transgender female community.ConclusionThe study underscores the interplay of individual, social, and service-related factors affecting healthcare access among transgender women. Inclusive and high-quality healthcare services are necessary to address the complex sociocultural aspects influencing transgender women’s healthcare access and utilization.

The EU LGBTI II survey was carried out by the European Union Agency for Fundamental Rights (FRA) in 2019. It is a large-scale survey into experiences and views of lesbian, gay, bisexual, trans and intersex (LGBTI) individuals. The survey provides comparative evidence on how LGBTI persons in the EU experience discrimination, violence and harassment in different areas of life, including employment, education, healthcare, housing and other services.

The EU LGBTI II survey is a follow-up of the first–ever major international survey on LGBT people, which the Agency conducted in 2012. The EU LGBTI II survey is a follow-up to the first major international survey of LGBT people conducted by the Agency in 2012. The EU LGBTI II survey is a web-based opt-in survey using an anonymous online questionnaire. The survey is based on a self-selective sample. The survey was conducted between 27 May and 22 July 2019 via the website www.lgbtisurvey.eu and collected valid responses from 139,799 respondents from the Member States of the European Union (EU), Northern Macedonia and Serbia (in this context, the United Kingdom is included in the group of EU Member States, reflecting the situation at the time of data collection in 2019). Following an EU-wide open call for tenders, the FRA contracted a consortium of Agilis SA (http://www.agilis-sa.gr/) and Homoevolution (https://homoevolution.com/), based in Greece, to carry out the survey according to the FRA´s technical specifications and under the supervision of FRA staff who monitored compliance with strict quality control procedures.

The EU LGBTI II survey asked a number of questions about the experiences of LGBTI people in the following areas: (1) Perceived increase or decrease in intolerance, prejudice and violence against LGBTI people; (2) Discrimination at work, looking for work and in several other areas of life; (3) Safe environment; (4) Physical or sexual victimisation; (5) Harassment; (6) Social context of being LGBTI; (7) Background information (age, education, income, civil status); (8) Specific sections dedicated to issues related to the life of trans as well as intersex persons.

1. Sexual orientation and sexual behaviour: to whom is the respondent sexually attracted; sex of sexual partners in the last five years; country of current residence and length of stay; citizen of the country; citizenship; country of birth; age at realisation of sexual orientation; age at first outing.

2. Trans respondents: Age at realisation that feelings about one´s own sex do not match the sex assigned at birth; age at first outing; measures taken to change body to better match one´s own sex identity and age at first intervention; reasons why no measures were taken to change body; medical treatment abroad to change one´s appearance, including buying hormones via the internet; avoiding expressing one´s own sex (or desired sex) by means of appearance and clothing for fear of being attacked, threatened or harassed; changing one´s legal sex; reasons for not changing one´s legal sex so far.

3. Intersexual respondents: type of existing variants of sexual characteristics or treatment for them; diagnosis of variants of sexual characteristics by health professionals; time of diagnosis (before birth, at birth, in childhood, adolescence or at a later age); time of first diagnosis in adolescence or at a later age; age at first realisation of variants of one´s own sexual characteristics; age at first outing; medical treatment to change sexual characteristics; age at first medical treatment; age at first medical treatment; consent given to treatment; type of treatment; informing the interviewee or his/her parents about possible positive or negative consequences; difficulties in registering civil status or sex in public documents; nature of difficulties; greatest difficulties encountered by intersexuals in the country.

4. Developments and responses to homophobia, transphobia, biphobia and intersex phobia: perceived increase or decrease in intolerance, prejudice and violence against LGBTI persons in the country over the last five years; main reasons for decrease or increase in prejudice and intolerance or violence; effectiveness of government action in combating prejudice and intolerance

5. Discrimination at work, when looking for work and in various other areas of life: Experience of discrimination in different spheres of life; situation at the time of the most recent discrimination; reasons for discriminat...

Do laws affect attitudes? Traditional models of policy creation emphasize how public opinion shapes policy but isolating the effect of one on the other is empirically challenging. The unexpected and exogenous nature of the Bostock v. Clayton County Supreme Court decision, which banned employment discrimination for LGBT (Lesbian, Gay, Bisexual, and Transgender) people, lends credibility to the notion of isolating the effect of policies on attitudes. Additionally, the Bostock decision affects labor market policy, while prior work on the relationship between policies and attitudes has primarily examined changes in social policy. I use the Supreme Court’s ruling in Bostock, paired with state variation in LGBT employment protections to estimate difference-in-differences and event study models to demonstrate that states that were “bound by Bostock” experienced a reduction in unfavorable attitudes towards LGBT people, supporting a legitimacy model of policy effects on attitudes. Finally, I examine heterogeneity in effects and find suggestive evidence that those who are interested in government, are male, or are Republican drive effects.

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 2023.