Challenging the White = Neutral Framework in Psychology

In the United States, White samples are often portrayed as if their racial identities were inconsequential to their thoughts, feelings, and behaviors, and research findings derived from White samples are often portrayed as if they were generalizable to all humans. We argue that these and other practices are rooted in a White = neutral framework (i.e., the conceptualization of White samples as nonracial). First, we review existing data and present some new data to highlight the scope of the White = neutral framework. Second, we integrate research from across psychological science to argue that the continued use of the White = neutral framework will prevent psychology from becoming a truly objective and inclusive science for at least three reasons: (a) Research with White samples will be valued over research with samples of color, (b) norms that maintain White neutrality will remain unchallenged, and (c) the role of White identity in psychological processes will remain underspecified and underexamined. Third, we provide recommendations for how to move beyond the White = neutral framework in hopes of encouraging all psychological scientists to move toward a White not equal neutral framework in which all samples are identified for the unique and diverse perspectives that they bring to the world.

Automated summary

In the United States, white samples are often treated as if their racial identities have no impact on their thoughts, feelings, and behaviors, and research findings from white samples are often assumed to apply to all humans. This is due to a white = neutral framework that fails to acknowledge racial differences. This framework hinders psychology from being an objective and inclusive science by favoring research with white samples, maintaining white neutrality norms, and neglecting the role of white identity in psychological processes. Recommendations are provided to move beyond the white = neutral framework and recognize the unique perspectives of all samples.