You Are What You Speak? Language Discrimination and Regard of Asian International Students

157955-Thumbnail Image.png
Description
Despite the increasing number of Asian international students in the United States, American society remains discriminatory against the population. Asian international students are exposed to ethnic-racial discrimination against Asians, as well as language discrimination against non-native English speakers. The purpose

Despite the increasing number of Asian international students in the United States, American society remains discriminatory against the population. Asian international students are exposed to ethnic-racial discrimination against Asians, as well as language discrimination against non-native English speakers. The purpose of this study was to examine whether the two types of discrimination relate to Asian international students’ regard, which refers to their positive or negative evaluations about Asians in American society. It was hypothesized that language discrimination, a particularly relevant form of discrimination for non-native English-speaking immigrants, will be associated with public and private regard, after controlling for ethnic-racial discrimination and English proficiency. The present study tested two hypotheses by conducting hierarchical multiple regression with a sample of 195 self-identified Asian international students. The results supported the first hypothesis, which predicted higher levels of language discrimination would explain a significant amount of additional variance in negative public regard after controlling for ethnic-racial discrimination and English proficiency. The second hypothesis was not supported—language discrimination was not significantly associated with positive private regard after controlling for ethnic-racial discrimination and English proficiency. Limitations, implications, and future directions are discussed.
Date Created
2019
Agent

Understanding and predicting activist intentions: an extension of the theory of planned behavior

157272-Thumbnail Image.png
Description
Despite the societal importance of activism, the understanding of activist intentions remained limited (Liebert, Leve, & Hu, 2011; Klar & Kasser, 2009). The current study used the Theory of Planned Behavior (TPB) to examine two structural models of low-risk

Despite the societal importance of activism, the understanding of activist intentions remained limited (Liebert, Leve, & Hu, 2011; Klar & Kasser, 2009). The current study used the Theory of Planned Behavior (TPB) to examine two structural models of low-risk activist intentions and high-risk activist intentions (Ajzen, 1991). The traditional TPB model was tested against a hybrid commitment model that also assessed past activist behaviors and activist identity. Participants (N = 383) were recruited through social media, professional list-serves, and word of mouth. Results indicated a good model fit for both the traditional TPB model (CFI = .98; RMSEA = .05; SRMR = .03; χ2(120) = 3760.62, p < .01) and the commitment model (CFI = .97; RMSEA = .05; SRMR = .04; χ2(325) = 7848.07, p < .01). The commitment model accounted for notably more variance in both low-risk activist intentions (78.9% in comparison to 26.5% for the traditional TPB model) and high-risk activist intentions (58.9% in comparison to 11.2% for the traditional TPB model). Despite this, the traditional TPB model was deemed the better model as the higher variance explained in the commitment model was almost entirely due to the inclusion of past low-risk activist behaviors and past high-risk activist behaviors. A post-hoc analysis that incorporated sexual orientation and religious affiliation as covariates into the traditional model also led to a good-fitting model (CFI = .98; RMSEA = .04; SRMR = .04; χ2(127) = 217.18, p < .01) and accounted for increased variance in low-risk activist intentions (29.7%) and high-risk activist intentions (18.7%) compared to the traditional model. The merits of each of the structural models and the practical implications for practice and research were discussed
Date Created
2019
Agent