The TransPop study is the first national probability sample of transgender individuals in the United States (it also includes a comparative cisgender sample). A primary goal of this study was to provide researchers with a representative sample of transgender people in the United States. The study examines a variety of health-relevant domains including health outcomes and health behaviors, experiences with interpersonal and institutional discrimination, identity, transition-related experiences, and basic demographic characteristics (age, race/ethnicity, religion, political party affiliation, marital status, employment, income, location, sex, gender, and education). Co-investigators (in alphabetical order): Walter O. Bockting, Ph.D. (Columbia University); Jody L. Herman, Ph.D. (UCLA); Sari L. Reisner, Ph.D. (Harvard University and The Fenway Institute, Fenway Health).

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.

The IPUMS Contextual Determinants of Health (CDOH) data series includes measures of disparities, policies, and counts, by state or county, for historically marginalized populations in the United States including Black, Asian, Hispanic/Latina/o/e/x, and LGBTQ+ persons, and women. The IPUMS CDOH data are made available through ICPSR/DSDR for merging with the National Couples' Health and Time Study (NCHAT), United States, 2020-2021 (ICPSR 38417) by approved restricted data researchers. All other researchers can access the IPUMS CDOH data via the IPUMS CDOH website. Unlike other IPUMS products, the CDOH data are organized into multiple categories related to Race and Ethnicity, Sexual and Gender Minority, Gender, and Politics. The CDOH measures were created from a wide variety of data sources (e.g., IPUMS NHGIS, the Census Bureau, the Bureau of Labor Statistics, the Movement Advancement Project, and Myers Abortion Facility Database). Measures are currently available for states or counties from approximately 2015 to 2020. The Sexual and Gender measures in this release include the proportion of a state's population identifying as LGBTQ+ in the U.S. Census Bureau's Household Pulse Survey, Phases 3.2 (07/21/2021-10/11/2021), 3.3 (12/01/2021-02/07/2022), 3.4 (03/02/2022-05/09/2022), and 3.5 (06/01/2022-08/08/2022). To work with the IPUMS CDOH data, researchers will need to first merge the NCHAT data to DS1 (MATCH ID and State FIPS Data). This merged file can then be linked to the IPUMS CDOH datafile (DS2) using the STATEFIPS variable.

Attribute Description NY 2010-2019

County: Location where the crime was reported.

Year: Year the crime incident was reported.

Crime Type: Category of crime defined by the FBI, including Crimes Against Persons (crimes targeting individuals or groups of individuals), and Property Crimes.

Anti-Male: Count of incidents with a reported Anti-Male bias. Male: An individual that produces small usually motile gametes (as spermatozoa or spermatozoids) which fertilize the egg of a female. (Merriam-Webster Dictionary)

Anti-Female: Count of incidents with a reported Anti-Female bias. Female: An individual of the sex that bears young or produces eggs. (Merriam-Webster Dictionary)

Anti-Transgender: Count of incidents with a reported Anti-Transgender bias. Transgender: Of or relating to a person who identifies as a different gender from their gender as determined at birth. The person may also identify himself or herself as “transsexual.” A transgender person may outwardly express his or her gender identity all of the time, part of the time, or none of the time; a transgender person may decide to change his or her body to medically conform to his or her gender identity.

Anti-Gender: Identity Expression Count of incidents with a reported Anti-Gender Identity Expression bias. Gender Nonconforming: Describes a person who does not conform to the gender-based expectations of society, e.g., a woman dressed in traditionally male clothing or a man wearing makeup. Note: A gender nonconforming person may or may not be a lesbian, gay, bisexual, or transgender person but may be perceived as such.

Anti-Age*: Count of incidents with a reported Anti-Age bias (60 years old or more). Age (60 years old or more): A preformed negative opinion or attitude toward a person or group of persons based on their actual or perceived age of 60 years old or more. The two bias types included under New York State’s Hate Crime Law (Penal Law Article 485) that are not included in the list of federally-defined bias types are noted with an asterisk(*).

Anti-White: Count of incidents with a reported Anti-White bias. White: A person having origins in any of the original peoples of Europe, the Middle East, or North Africa. This category includes persons from the following nationalities: Irish, German, Italian, Lebanese, Arab, Moroccan, or Caucasian. (Census)

Anti-Black: Count of incidents with a reported Anti-Black of African American bias. Black or African American: A person having origins in any of the Black racial groups of Africa. This category includes persons from the following nationalities or groups: African American, Kenyan, Nigerian, or Haitian. (Census)

Anti-American Indian/Alaskan Native: Count of incidents with a reported Anti-American Indian or Alaskan Native bias. American Indian or Alaska Native: A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment. This category includes persons from the following tribal affiliations: Navajo, Blackfeet, Inupiat, Yup’ik, or Central American Indian groups or South American Indian groups. (Census)

Anti-Asian: Count of incidents with a reported Anti-Asian bias. Asian: A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. This category includes persons from the following nationalities: Asian Indian, Bangledeshi, Bhutanese, Bermese, Cambodian, Chinese Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian, specified; Other Asian, not specified. (Census)

Anti-Native Hawaiian/Pacific Islander: Count of incidents with a reported Anti-Native Hawaiian/Pacific Islander bias. Native Hawaiian or Other Pacific Islander: A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. This category includes persons from the following nationalities: Fijian, Guamanian or Chamorro, Marshallese, Native Hawaiian, Other Micronesian, Other Pacific Islander, not specified; Other Polynesian, Samoan, Tongan. (Census)

Anti-Multi-Racial Groups: Count of incidents with a reported Anti-Multi-Racial Groups bias. Multiple Races, Group: A group of persons having origins from multiple racial categories.

Anti-Other Race: Count of incidents with a reported Anti-Other Race bias. Other Race/Ethnicity/Ancestry: A person of a different race/ethnicity/ancestry than is otherwise included in this combined category.

Anti-Jewish: Count of incident...

Given that an estimated 0.6% of the U.S. population is transgender (trans) and that large health disparities for this population have been documented, government and research organizations are increasingly expanding measures of sex/gender to be trans inclusive. Options suggested for trans community surveys, such as expansive check-all-that-apply gender identity lists and write-in options that offer maximum flexibility, are generally not appropriate for broad population surveys. These require limited questions and a small number of categories for analysis. Limited evaluation has been undertaken of trans-inclusive population survey measures for sex/gender, including those currently in use. Using an internet survey and follow-up of 311 participants, and cognitive interviews from a maximum-diversity sub-sample (n = 79), we conducted a mixed-methods evaluation of two existing measures: a two-step question developed in the United States and a multidimensional measure developed in Canada. We found very low levels of item missingness, and no indicators of confusion on the part of cisgender (non-trans) participants for both measures. However, a majority of interview participants indicated problems with each question item set. Agreement between the two measures in assessment of gender identity was very high (K = 0.9081), but gender identity was a poor proxy for other dimensions of sex or gender among trans participants. Issues to inform measure development or adaptation that emerged from analysis included dimensions of sex/gender measured, whether non-binary identities were trans, Indigenous and cultural identities, proxy reporting, temporality concerns, and the inability of a single item to provide a valid measure of sex/gender. Based on this evaluation, we recommend that population surveys meant for multi-purpose analysis consider a new Multidimensional Sex/Gender Measure for testing that includes three simple items (one asked only of a small sub-group) to assess gender identity and lived gender, with optional additions. We provide considerations for adaptation of this measure to different contexts.

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. There are no publicly available data files for this study. The naming conventions were maintained from the original pre-ICPSR release and the PUDS file is restricted use along with the qualitative data (MS Excel) file. Before applying for access to these data please refer to the Approved Requests for USTS Data. These abstracts describe work currently in progress, and we provide them to help reduce the risk of duplication of research efforts.

Demographic characteristics of study participants, comparing transgender women and cisgender men.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of the 2017 Discrimination in the United States Survey, a survey from Harvard T.H. Chan School of Public Health/Robert Wood Johnson Foundation/National Public Radio conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include:Belief in discrimination against racial/ethnic minoritiesDiscrimination against men/womenDiscrimination against lesbian/gay/bisexual peopleDiscrimination against transgender peopleBiggest problem with discrimination against lesbian/gay/bisexual/transgender/queer (LGBTQ) peopleLive on tribal landsLocal/tribal government Discrimination based on raceDiscrimination based on genderDiscrimination based on being part of the LGBTQ communityReasons for avoiding seeking health careExperiences with discriminationDiscrimination resulting in fewer employment opportunitiesDiscrimination resulting in unequal payDiscrimination resulting in fewer chances for quality educationEncouraged to/discouraged from applying to collegePredominant groups living in respondent's areaNot feeling/being welcomed in neighborhood due to raceNot feeling/being welcomed in neighborhood due to being part of LGBTQ communityConsidered moving to another area because of discriminationComparing respondent's area to othersPolice using unnecessary force based on race/ethnicityAvoiding activities to avoid discrimination from policeExperiences caused by racial discriminationExperiences caused by gender discriminationExperiences caused by discrimination against LGBTQ communityLocal police force does/does not reflect racial/ethnic background of communityContacted by political representatives about voting/supporting causeRegistered to voteVote in 2016 presidential electionPhysical health statusMental health statusDisabilityChronic illnessVeterans AdministrationIndian Health ServicesSeeking health careInsurance coverageThe data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31114655]. Frequencies and summary statistics for the 235 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

This dataset was collected as part of the HARP study: HIV care Access and Retention in Paraguay. It was collected from men who have sex with men and transgender women attending the HIV clinic in the Institute of Tropical Medicine in Asunción, Paraguay, from August 2017 to July 2018. The study was funded by amfAR, the American Foundation for AIDS Research. It was approved by the University of Pittsburgh IRB in Pittsburgh, PA, USA and by the Universidad Nacional de Asunción IRB in Asunción, Paraguay. It was done with the support of the Paraguayan Program for Control of AIDS and the Paraguayan Institute of Tropical Medicine. The Principal Investigator was Dr. Antonio Spagnolo-Allende, with co-investigators from from the University of Pittsburgh Center for LGBT Health Research, and from Fundación Vencer in Asunción, Paraguay.

This dataset was collected as part of the HARP study: HIV care Access and Retention in Paraguay. The study was funded by amfAR, the American Foundation for AIDS Research. It was approved by the University of Pittsburgh IRB in Pittsburgh, PA, USA and by the Universidad Nacional de Asunción IRB in Asunción, Paraguay. It was done with the support of the Paraguayan Program for Control of AIDS and the Paraguayan Institute of Tropical Medicine. The Principal Investigator was Dr. Antonio Spagnolo-Allende, with co-investigators from from the University of Pittsburgh Center for LGBT Health Research, and from Fundación Vencer in Asunción, Paraguay.

HIV risk behaviors during reference period1, comparing transgender women and cisgender men.

HIV prevalence and odds ratios for trans feminine individuals compared to all adults (age 15+) in US-based studies, according to whether data was collected before or after the introduction of PrEP (2012).

Context

Popularly known as the "Trans Law", it is one of the most controversial projects of the left-wing coalition government. Even within the coalition there are opposing opinions. If the bill is passed, Spain would become the largest European country to allow people to legally change the name and gender on their identity documents without the need for years of hormone therapy or medical diagnosis. This has provoked a great deal of debate and/or strong positioning on the matter, which has also been reflected in social media such as Twitter.

Content

This dataset contains about 1.5 million tweets collected from the social network Twitter around the Spanish Transsexuality Law. The dates range from January 13, 2021 to October 12, 2022. The data will be updated periodically. To get an idea of the data, making a network based on retweets, the number of users or nodes are 257,887 and 738,651 edges.

Inspiration

To link social groups with (discursive) practices around the debate on the Trans Law. To find differences and similarities in the frames used by each community. 1. Describe communities of users by their interactions and their similarities. 2. Find which are the most common frames used in this discussion: 2.a Find the social frameworks and analysis of their discourse: 2.b Obtain word clusters and relate them to the previously obtained frames. 3. Analyze the relationships between frames and communities in order to find: 3.a. Common and specific frames for each community. 3.b. Bridges through the frameworks with communities other than those analyzed. 3.c. Evolution of the social frameworks in time.

The authors would be pleased to know that this dataset has been useful for any research inside or outside Kaggle. Do not hesitate to contact us: Álvaro Martínez García-Salmones: alvaro.martinezgs@gmail.com Héctor Fernández Rodríguez: hectorfr1984@gmail.com

Substance use during reference period1, comparing transgender women and cisgender men.

Weighted descriptive statistics by marital status and gender, transmen.

HIV care continuum outcomes during reference period1, comparing transgender women and cisgender men.

Changes to the PURPOSE 2 study design and protocol based on stakeholder and Global Community Advisory and Accountability (GCAG) feedback.

Sample sociodemographic characteristics, Canadians age 14 and over.

Summary of qualitative studies included in review.