Movement on Data Standards to Better Measure Real Lives

At Metopio, we partner with our clients to think about what data is important to address the questions that are most pressing for them and offer insights on how they should think about getting answers to close the knowledge gap. 

For any kind of equity assessment, demographic data is extremely important so you can see specific populations in the data. While government entities sometimes collect race, ethnicity, and age data, we often get the question, “how do I ask about sexual orientation and gender?”

So it was exciting to see Karin Orvis, who is the Chief Statistician of the United States, announce recommendations on the best practices for the collection of sexual orientation and gender identity (SOGI) data this week. This step is critical because government data plays a vital role in how the public, businesses, elected officials and government agencies make decisions.

Evolution of Data Standards

It’s important to note this report does not include any mandates and specifically states that these best practices will continue to evolve. Nevertheless, it is significant progress towards recognizing, respecting and protecting the diversity within our communities.

The report included recent analyses relative to data collected with SOGI stratifications and showed:

  • the lesbian, gay, bisexual, or transgender communities were hit harder by the economic impact of the COVID-19 pandemic – read more here.
  • LGBT adults struggled more with mental health during the COVID-19 pandemic than non-LGBT adults – learn more here.
  • college students who identify as gender minorities have had more difficulty finding safe and stable housing – see the report.
  • the rate of violent crime victimization of lesbian or gay persons has been more than two times the rate for straight persons – read more here.

Again, stratifications allow you to understand how different variables impact different populations and are critical for advancing both health and wealth equity.

Importance of Self-Identification

Self-identification refers to the process by which individuals are able to identify and express their own identity without the influence of societal expectations or stereotypes.  Self-identification helps reduce the inaccuracies in data that can occur when individuals are forced to choose a category that does not align with their self-identified race, ethnicity, sexual orientation or gender identity.

This approach is being adopted by the federal government and other organizations to collect data on race and ethnicity, as well as sexual orientation and gender identity, and is seen as a best practice for data collection in these areas.

One way that the US Census has continued to evolve data collection categories is by including “Other” as a write-in.  Director Rob Santos has said this enables the agency to evaluate first-person identification in addition to their research efforts.  For example, for ethnicity when a person responds to the Census that they are Hispanic or Latino or Spanish origin, they then have a separate question for race.

Considerations for Collection Data

The report outlined best practices for the collection of sexual orientation and gender identity (SOGI) data as it relates to federal statistical surveys. However, it is also a great framework for all organizations to consider when striving to collect similar data.

Language suggestions

  • Use inclusive language: Surveys should use inclusive language that respects the diversity of SOGI identities, rather than using binary or stereotypical terms. See samples in the report here.
  • Provide multiple response options: Surveys should provide multiple response options for SOGI identity, rather than limiting respondents to a binary choice such as “Other”. This includes options such as “transgender,” “queer,” and “none” for sexual orientation and gender identity questions.
  • Allow for non-response:  Allowing respondents to skip SOGI questions or choose not to answer them, rather than requiring them to provide a response helps avoid creating inaccurate data.

Response options

  • Test the questions: Surveys should pilot test SOGI questions with diverse groups of respondents to ensure they are inclusive and provide valid and reliable data.
  • Provide context: Surveys should provide context for the SOGI questions in order to help respondents understand why the data is being collected and how it will be used.

Privacy considerations

  • Consider the data quality: Surveys should consider the data quality, as SOGI data is sensitive, and some respondents may not be comfortable answering the question.
  • Pay attention to sample size: Surveys with open fields may result in small sample sizes that should be handled with care in order to protect the privacy of respondents and ensure their SOGI identity is kept confidential. Responses could still be aggregated into larger groupings to maintain sufficient sample size and preserve privacy.

Overall, it’s important for surveys to be inclusive and respectful when collecting data on SOGI. The data collected must be valid and reliable, and the rights and privacy of all respondents must be protected.  Following these best practices promotes inclusivity and supports the rights of marginalized groups.

To learn more about data curation and how Metopio can help with equity analysis, please contact angie@metop.io today.

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