Sponsor
Portland State University. Department of Psychology
First Advisor
Kimberly Barsamian Kahn
Term of Graduation
Winter 2024
Date of Publication
1-23-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (Ph.D.) in Applied Psychology
Department
Psychology
Language
English
Subjects
Islamophobia -- United States, Prejudices -- United States, Ideology -- United States, Muslims -- United States -- Race relations, Social psychology
DOI
10.15760/etd.3713
Physical Description
1 online resource (viii, 313 pages)
Abstract
This dissertation consists of two manuscripts addressing the multifaceted nature of Islamophobia in the United States by examining explicit and implicit anti-Muslim bias on individual and structural levels. The first manuscript tests an ideology-threat-attitude-behavior model by estimating the simultaneous mediating effects of threat perceptions on the relationships between individual differences in ideology, Islamophobia (fear of Muslims), and support for an anti-Muslim police surveillance policy. This study (N = 603) finds that individuals who are higher in Social Dominance Orientation (SDO), Right-wing Authoritarianism (RWA), and Nationalism are more likely to perceive Muslims as realistic (power), symbolic (value), and terroristic (safety) threats. Higher perceived threats are then associated with higher levels of Islamophobia, which mediates the relationships between perceived threats and anti-Muslim policy support. This detailed framework on anti-Muslim prejudice underscores the distinct and combined influences of ideology and perceived threats on prejudice and discrimination against Muslims. The results suggest that policy decisions that emphasize perceived threats may be particularly influential among individuals with strong tendencies toward SDO, RWA, and Nationalism.
The second manuscript takes a contextual approach to implicit bias and examines the effects of a real-world United States immigration policy that targeted Muslims (the "Muslim ban") on implicit anti-Muslim bias across different political contexts and among people with different political beliefs in the United States. Using a large dataset of Implicit Association Test (IAT) scores from Project Implicit (N = 263,168), this study utilized multilevel modeling to examine how Muslim ban activity (e.g., President Trump signing the Muslim ban) influenced state-level implicit bias across political contexts (i.e., state-level margin of victory for Democrat or Republican candidates in previous presidential elections) and how this interacted with participants’ individual political beliefs. Results find that, while the Muslim ban was associated with lower levels of anti-Muslim implicit bias overall, this effect was primarily driven by those who are more liberal. Further, a cross-level interaction between state voting behaviors and individual political orientation revealed that more conservative individuals in Democrat-voting states had marginally higher levels of anti-Muslim implicit bias during Muslim ban periods. These findings point to several types of backlash effects, including a general policy backlash effect (i.e., lower levels of bias during ban periods for liberals) and a potential context backlash effect (i.e., marginally higher levels of bias for conservatives in Democrat-voting states), which hold implications for how people with different political beliefs implicitly react to the same policy across different political contexts. Together, these studies investigate the implicit and explicit components of anti-Muslim bias that occur on individual and structural levels in the United States. Results provide a foundation for considering how policies can be presented in different contexts and among people of differing political backgrounds and ideological beliefs. Collectively, these studies offer insight into how to anticipate responses to discriminatory policies, as well as how to better communicate different policies to manage reactance among different political and ideological groups in the United States.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
https://archives.pdx.edu/ds/psu/41475
Recommended Citation
Granger, Aeleah M., "Individual and Structural Contributors to Implicit and Explicit Anti-Muslim Bias in the United States" (2024). Dissertations and Theses. Paper 6581.
https://doi.org/10.15760/etd.3713