Analyzing the Lives of LGBTI People - Survey Approaches to LGBTI Persons, Couples and Families 2 |
|
| Session Organisers | Dr Stephanie Steinmetz (University of Amsterdam) Ms Mirjam Fischer (University of Amsterdam) Dr Nancy Bates (U.S. Census Bureau) |
| Time | Wednesday 17th July, 11:00 - 12:30 |
| Room | D21 |
In recent years, much progress has been made in the US, Europe and beyond with regard to legislation that is supportive and protective of LGBTs (Lesbian, Gay, Bisexual, Trans persons). While these achievements are laudable, it is important to keep evaluating to what extent structural obstacles to equality remain. Compared to research on other minority groups, sexual minorities have been studied quantitatively much less in the social sciences. Yet, scholars have continuously made efforts to overcome the methodological challenges associated with studying this population quantitatively. This is an important development which should be encouraged and continued.
This session invites contributions showcasing research around the challenges, successes, and best practices when collecting data on sexual minorities. In particular contributions addressing one of the four areas are welcome:
1) How to sample LGBT populations? (e.g. what are common strategies for designing sampling frames intended at capturing LGBT populations? Which advantages and disadvantages in terms of data quality can be detected?);
2) How to measure sexual orientation and gender identity (SOGI) in large-scale, general-population surveys and polls? (e.g. Can sexual orientation be collected by proxy in surveys that use a single household informant? How can issues of cross-cultural validity, language and interviewer effects be addressed? Does the addition of SOGI items harm unit response rates in surveys that do not typically collect such items?);
3)How to estimate the size of LGBT populations (e.g. are there besides surveys alternative inventive methods, such as administrative records or internet web-scraping, for producing valid LGBT population estimates? In the absence of large representative demographic survey data, are there ways to extrapolate from non-random, small area, snowball, or convenience samples?;
4) as issues around SOGI are increasingly visible on the agenda of governments and governmental organizations around the globe the session also invites contributions which highlight best practices how the SOGI topic can most efficiently and successfully be approached?
In addition, this session also invites submissions that focus on topical survey results around LGBT populations such as physical and mental health disparities, income inequality, hate crimes, and household and family structures. The session hopes to draw a cross-section of submissions from different countries and different survey experiences.
Keywords: hard-to-reach populations, SOGI, samplingand estimating LGBT populations
Dr Alessandra Gaia (University of Milan-Bicocca) - Presenting Author
Dr Tarek Al Baghal (Institute for Social and Economic Research)
Providing sound statistical information on the gay, lesbian, or bisexual populations (also called “sexual minorities”) is needed to inform policy makers on disadvantage and discrimination. However, obtaining good quality data is methodologically challenging, as sexuality is one of the most sensitive topics when asked about directly in social surveys. In order to minimize measurement error in the estimate of the gay, lesbian, and bisexual population we propose and test empirically a new technique: the Longitudinal Item Count Technique (LICT); this is a variation of the Item Count Technique (ICT) which overcomes the ICT limitation of not providing an indicator of the behavior at the respondent level. We discuss the assumptions, implementation, limitations, and ethical implications of this novel technique. We present an application of the method to estimate sexual minorities in the UK, using experimental data from a large scale nationally representative survey: the Understanding Society Innovation Panel. We compare the estimates of the lesbian, gay and bisexual population obtained with the LICT, the ICT, and direct questioning. Furthermore, we compare population estimates of sexual minorities obtained with direct questioning using different modes of data collection (CASI, CAPI with showcards and Web). Finally, comparing direct questions and micro-level LICT indicators, we perform multivariate analyses to identify socio-demographic factors associated with misreporting a gay, lesbian, or bisexual sexual orientation. We conclude pointing to routes for further research.
Dr Frances Barlas (Ipsos Public Affairs) - Presenting Author
Mr Randall Thomas (Ipsos Public Affairs)
Dr Mansour Fahimi (Ipsos Public Affairs)
Gender identity is an important indicator in research investigations across an array of substantive topics, such as health and employment, yet few national surveys include questions on gender identity. There is a growing body of research testing various methods of asking gender identity for inclusion in surveys. KnowledgePanel, Ipsos’ online probability-based panel, is one of the first national surveys that asked questions about gender identity as part of its profile surveys since 2010. Initially, we asked respondents a yes/no question about whether or not they identified as transgender. Results showed a likely overestimate of the transgender population likely due to comprehension problems, particularly among Spanish survey takers. We subsequently conducted a series of surveys to test alternative ways of asking about gender identity, most recently testing a two-step method for assessing gender identity first proposed by the Center of Excellence for Transgender Health at University of California – San Francisco in which respondents are asked their sex assigned at birth and their current gender identity. A sample of 2,874 KnowledgePanel members completed a survey with random rotation of the order in which these two questions were asked, as well as randomly varying response categories for the question on current gender identity, testing a simpler as well as a more detailed version. Respondents were also asked a series of follow-up questions to gauge their comprehension and comfort with the gender identity questions, as well as the extent to which they felt the survey questions allowed them to accurately tell us their gender identity. Results indicate that the two-step gender identity questions produced an estimate of the transgender population that is more in line with best national estimates. Respondents also found the new questions easy to understand and answer.
Ms Jessica Holzberg (U.S. Census Bureau) - Presenting Author
Dr Renee Ellis (U.S. Census Bureau)
Dr Robin Kaplan (U.S. Bureau of Labor Statistics)
Mr Matt Virgile (U.S. Census Bureau)
Dr Jennifer Edgar (U.S. Bureau of Labor Statistics)
Within the United States Federal Statistical System, there has been interest in capturing sexual orientation (SO) and gender identity (GI), collectively known as SOGI, on surveys to allow researchers to estimate the size and distribution of sexual and gender minority populations. SOGI measurement in federal surveys may also help to identify disparities between people who identify as lesbian, gay, bisexual, and transgender (LGBT) and those who do not in domains such as health, crime, or employment.
Although research has been conducted on best practices for SOGI measurement in surveys, it has largely been limited to examination of self-reports. Many federal surveys in the United States use proxy reports, when one person generally responds for all household members. In this presentation, we describe results from cognitive interviews and focus groups conducted to explore proxy response to SOGI questions. We explored potential sources of measurement error in proxy responses to SOGI questions, including sensitivity, difficulty, as well as the willingness and ability of respondents to answer SOGI questions about other household members. We also conducted paired interviews with members of the same household to assess level of agreement for SOGI questions. Findings suggest that measuring SOGI by proxy may be feasible in federal large-scale, general population surveys.
Dr Rose Kreider (US Census Bureau) - Presenting Author
Dr Benjamin Gurrentz (US Census Bureau)
This presentation will describe upcoming changes to the household relationship data in the Current Population Survey (CPS). Since 2007, we have added a direct cohabitation question, changed the way we ask respondents to identify parents in the household, changed how we edit same-sex couples, and revised the answer categories on the relationship to householder question. The presentation will describe the changes, explain their benefits, and provide some comparisons to illustrate the changes.
The changes relate directly to the LGBT population since they were implemented to improve measurement for same-sex couples, both married and unmarried, as well as same-sex parents. In Census 2010, we discovered that misreporting by opposite-sex married couples was having a large effect on the estimates of same-sex married couples. The changes to the relationship to householder question, and to the editing process for the data, work to improve these estimates. In this presentation, we plan to provide some comparisons of key characteristics by couple type. The CPS asks how each household member is related to the householder. The revised question expands the ‘spouse’ and ‘unmarried partner’ categories, and lists ‘opposite-sex husband/wife/spouse,’ ‘same-sex husband/wife/spouse,’ ‘opposite-sex unmarried partner,’ and ‘same-sex unmarried partner.’
In addition, we changed how we ask the parent identification questions. From roughly the mid-1980s through 2006, CPS contained one question asking for the identification of a parent. If that parent was married, the person was considered to have two parents present. In 2007, we began asking for the identification of a mother and a father. The new questions ask for the identification of a parent, and a second parent, regardless of sex. This allows respondents to easily report two mothers or two fathers.