Drew is a member of Fors Marsh Group’s (FMG) Diversity and Inclusion (D&I) committee and has been at FMG since July 2018. He has more than five years of social science research experience in both academic and applied areas. Drew’s prior research includes morality, social cognition, and aggression. He has been involved in initiatives on improving research practices and social responsibility in science. As part of FMG’s Military Recruiting Research team, Drew studies attitudes and perceptions of the U.S. Military as well as youths’ career consideration processes.
As discussed in Labels and Identities in Research Reports, the language that social scientists and researchers choose to use in their reports is an important first step to reducing bias. In many cases, the research produced in these reports has far-reaching implications. Using person-centric, specific language can help reduce bias and ensure the presentation of research is clear and accurate. Social scientists should also take precautions when comparing social groups to avoid inflicting indirect group harm and creating unintended consequences from their research.
How to Compare Social Groups
One of the goals of sampling research is to generalize results to a wider population, but it should be noted that findings cannot be universalized. Practicing scientific responsibility can help avoid making inappropriately sweeping generalizations about social group differences that can lead to unintentional negative outcomes for those groups studied.
What to consider when comparing social groups:
- Researchers should avoid “essentialism” or group homogenizing. Although certain social groups may have similar trends across findings and constructs, members of that group may not universally share characteristics and motivations.
- Example: Including wording such as “the Black community” suggests that Black respondents are a single-minded homogenous group.
- Consider how your comparisons are structured within analyses. Refrain from creating false hierarchies or false binaries.
- False hierarchy: If researchers set White participants as the standard comparison group against all other racial groups when comparing racial groups, then it can create a false hierarchy in which White participants are implicitly framed as the “normal” group.
- False binary: If researchers reduce group differences to pairwise comparisons, then it suggests that there are only two mutually exclusive categories. For instance, using the term “opposite sex” creates a false binary that excludes the full spectrum of sexual identities. Instead, consider using “another sex” or more directly naming the sexual identity studied.
How to Avoid Group Harm
Group harm refers to the possibility that scientific findings may have a negative impact on a social group beyond those who directly participated in the study. This can take the form of economic harm, cultural harm, sociopolitical harm, or other forms of harm. Science has an unfortunate history of causing harm to already disenfranchised groups through unintentionally harmful research. For instance, an infamous 1979 epidemiological study on alcoholism in Alaskan Natives in the city of Barrows reported that indigenous people who had traditional tribal jobs were more likely to be detained while being intoxicated. This led to an economic devaluing of the city, making it more difficult for the city to borrow money from the state or federal government. A more recent study on human genetics reported several genetic markers that were correlated with homosexual behavior. The reporting of a possible “gay gene” could lead to conceptualizations of homosexual genetic determinism or even hark back to the United States’ history of eugenics.
When discussing research on social groups—and especially of historically discriminated groups—researchers should take steps to mitigate the possibility of unintentional group harm by considering the following:
- Collaborate with members of potentially impacted groups during the planning and reporting phases of the projects.
- Group harm should also be a critical factor for Institutional Review Boards (IRB) when assessing the ethical concerns of a project and could involve target group members to independently review possible negative effects.
Social Consciousness Leads to Better Results
By being more aware about how we discuss findings, we can reduce bias in scientific reporting and more carefully consider the potential effects of our research. At FMG, our core company values encourage employees to produce impactful work the right way. As such, researchers are encouraged to consider and apply best practices in measuring identity in survey research and be mindful of how we communicate our results. Researchers should strive to have greater social consciousness in science and use research to promote positive changes in society.