We value the experiences of individuals of every age, national origin, race, ethnicity, gender, sexual orientation, ability status, and other identities. Positionality statements makes transparent how the identities of the authors relate to the research topic and to the identity of the participants.
Scholars are not mandated to disclose any aspect of their identities, only encouraged. They may choose to disclose one or more of their identities, in as much or as little detail as possible.
What is a Positionality Statement?
A positionality statement makes clear how the identities of the authors relate to the research topic and to the identities of the participants, and how these identities are represented.
Recommendations for Drafting Positionality Statements
Scholars are encouraged to draft a positionality statement that helps clarify how the scholars are positioned regarding the research and the researched. Scholars may choose to include only whatever is most relevant to the specifics of the research topic.
If, for instance, scholars are drawing conclusions about Asian Americans, yet the author list consists exclusively of White Americans, that could be made clear. Or, if gender is being examined, and research participants are members of the LGBTQIA+ community yet the research team consists only of individuals who identify as heterosexual and cisgender, a positionality statement can discuss that.
Scholars may choose to disclose information related to their positionality statements collectively. For example: “one author self-identified as U.S. Black-White American, and four authors self-identified as U.S. White American” (see Roberts et al., 2020). None of these recommendations are limited to the study of one subject.
Alternatively, if scholars would prefer not to disclose specifics of their position/conditions, a more general statement such as “I have lived experience in …” would be more than appropriate.
These statements should be included together with any other relevant disclosure.
Positionality Statements: Examples
Davis, S. M. (2018) The aftermath of #BlackGirlsRock vs. #WhiteGirlsRock: considering the disrespectability of a Black women’s counterpublic. Women’s Studies in Communication 41, 269–290. doi=10.1080/07491409.2018.1505678
Before I present the findings, and in the spirit of self-reflexivity, I acknowledge my standpoint as an educated Black American woman. I am not an avid participant in Black online spaces such as comments sections, but I have observed the interactions of other users, advocated for Black online spaces, and am intrigued by the use of language to mark and protect cultural identities. I acknowledge that my positionality influenced this project to some extent; my member resources proved to be important tools that helped me make meaning of the text.
Roberts, S. O., Bareket-Shavit, C., Dollins, F. A., Goldie, P. D., & Mortenson, E. (2020). Racial inequality in psychological research: Trends of the past and recommendations for the future. Perspectives on Psychological Science, 15, 1295–1309.
When the manuscript for this article was drafted, one author self-identified as U.S. Black-White American, and four authors self-identified as U.S. White American.
Su-Russell, C., & James, A. (in press). Chinese international scholars’ work-life balance in the U.S.: Stress and strategies. Journal of International Students.
There are two authors for the current study. The primary author, led the data collection and analysis processes, is bilingual in English and Mandarin Chinese, which allowed for the study participants to feel comfortable sharing their lived experiences in a way they felt could best express their thoughts and feelings. The second author is an ethnic minority scholar in the U.S. and contributed to refining the theoretical framework. Both study authors contributed to interpreting findings and the implications of the study. It is likely, however, our ethnoracial backgrounds influence our interpretations of the data. To avoid speaking for the data, both authors made efforts to bracket existing biases or assumptions. To avoid bias, notes were taken on all preconceptions that arose about the study population in order to bracket these existing assumptions during data collection and analysis process (Lincoln & Guba, 1985).
Originally conceptualized by Melissa Curran and Ashley K. Randall of the International Association for Relationship Research (IARR)