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Social science research about non‐Native attitudes and beliefs about Native Americans (NA) shows that stereotypes are widely endorsed and that their racist content has changed little from the original imperial conception of "the Indian" described in critical historiography and Native studies. What we understand less is how non‐Natives understand NA in relation to the self and how this relationship might reproduce or challenge racial hierarchy. We explored attitudes toward NA among a multi‐racial sample from Arizona using a perspective‐taking exercise, asking interviewees, "If you were to become a Native American person for just a few days, how do you think your life would be different?" Responses expressed stereotypes, recognition of discrimination, and claims of sameness. Stereotypes reflect an endorsement of both negative and positive stereotypes of NA by interviewees. Recognition of discrimination reflects participants' awareness of inequality in the experiences and circumstances of NA relative to non‐NA. Claims of sameness reflect colorblind views of NA. We demonstrate perspective‐taking questions as useful for the sociology of the self and other.

Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we've collected. Although there are a few exceptions, less focus is on transparency regarding decision-making processes in the course of research. In this article, we argue that scholars should create a living codebook, which is a set of tools that documents the data analysis process. It has four parts: (1) a processual database that keeps track of initial codes and a final database for completed codes, (2) a "definitions and key terms" list for conversations about codes, (3) memo-writing, and (4) a difference list explaining the rationale behind unmatched codes. It allows researchers to interrogate taken-for-granted assumptions about what data are focused on, why, and how to analyze it. To that end, the living codebook moves beyond discussions around intercoder reliability to how analytic codes are created, refined, and debated.