by Emilia Dunham
Reporting on Creating Change
This morning I attended a workshop on what has become an important but broken record in our community: LGBT data collection with Cristy Mallory, Jody Herman, and Masen Davis.
They discussed some of the best practices for developing and including questions on sexual orientation and gender identity. You may be familiar with recommendations of the Sexual Minority Assessment Research Team (SMART) for instance.
In this workshops the presentors discussed the survey process in the form of questions to ask your research team when planning surveys:
- what is the goal?
- who is the target?
- what resources are available?
- how will you reach people? (what is your promotion strategy?)
- how to get high response rate? (incentive: start with money; next is community based appeal)
- how do you design your survey and what questions do you ask? (consider existing surveys, define terms, do not use jargon, add “don’t know/refused to answer”)
- how will you collect and analyze the data? (clean data to remove non-target)
- how will you write-up and distribute the results?
- how will you utilize the results to achieve original goal? (to advocate, improve programs, etc)
California Case Study
Masen Davis of the Transgender Law Center discussed their study of trans Californians. The strategy was to use existing strong networks, effectivelymade practical use of staff time and volunteers, incentives and many other means. Fortunately the results of the survey was very successful as it can show what’s needed for other surveys and more importantly it gives you data you need. For instance it showed that among CA trans people, there are significant issues of homelessness, income gaps, health disparities, etc.
The need for data may be familiar to most of us: It’s hard to show proof of discrimination, unemployment, health disparities without data, even when that is known in communities. The end goal being that data can be used to access funding from government.
The California State Trans Study Report is a great example of what can be done to successfully achieve research, data and policy goals.