Clarifying the meaning of symbolic racism

Abstract

We examined whether symbolic racism is associated with anti-Black affect or more general anti-liberal affect. Across six studies (N = 14,078), we determined that symbolic racism is associated with more positive attitudes toward conservatives and more negative attitudes toward liberals, regardless of the target’s race. While high scorers on the symbolic racism scale show a slight preference for White vs. Black conservatives (d = .15) and White vs. Black liberals (d = .12), low scorers show a considerable preference for Black vs. White liberals (d = .42) and Black vs. White conservatives (d = .50). Lingering questions about the validity of the symbolic racism construct are justified on the basis that symbolic racism does not reliably measure anti-Black affect.

Keep your enemies close: Adversarial collaborations will improve behavioral science.

“…The patterns of attitude–behavior correlations reveal a messier story. On the one hand, low scorers on the scales have the strongest race-based preferences—and in favor of Black people over White people (Wright et al, 2021)—and research increasingly shows that conservatives treat people of different races more similarly than do liberals (Clark et al, 2020). On the other hand, liberalism is also associated with stronger desires to live in racially diverse communities (e.g., Motyl et al, 2020) and stronger commitments to racial equality (Pew Research Center, 2021), highlighting how conclusions can vary as operationalizations vary.…”

The road less traveled: Understanding adversaries is hard but smarter than ignoring them.

“…As Ceci and Williams (2022) pointed out, many accurate interpretations of findings are still misleading because scholars are free to highlight and ignore different parts of the same information in their framing of the findings. Misleading-but-not-technically inaccurate interpretations of findings are not uncommon (for discussions of examples, see Blanton et al, 2009;Clark et al, , 2022Clark & Tetlock, 2021;Clark & Winegard, 2020;Dawson & Arkes, 2009;Purser & Harper, 2020;Sniderman & Tetlock, 1986;Wright et al, 2021), but these are not widely regarded as QRPs, nor would we expect many scholars to detect this tendency in themselves. Whereas Open Science practices can constrain QRPs that are easily detected with increased transparency, such as unplanned data exclusions and abuses of analyst degrees of freedom, ACs can help constrain subtler practices such as refusals to run certain tests, rigging methods, file drawering, and tendentious framing of conclusions.…”