Sexism and Severity: An Examination of Teacher\u27s Attitudes About Autism Symptomology in the Classroom

Girls continue to be underdiagnosed and under-researched in the study of autism spectrum disorder (ASD). This is the result of a systemized preference towards masculine symptomology of ASD examined and created to diagnose ASD. The ideas produced by the research trickle down to teachers who then are in charge of flagging students for signs of ASD, however this step is not only limited by understanding, but their own inherent gender biases on behaviors. Our sample consisted of 139 current or former teachers. Each participant received one of three, (varying from severity levels and gender), rating scale of behavior association, rating scale of levels of concern about behaviors indicated in the vignettes, rating scales of likelihood of follow up on behaviors, modern sexism scale items. For each rating item, a 2 (gender of target: male or female) by 3 (symptom severity: mild, moderate, or severe) ANCOVA was conducted with participants’ scores on the Modern Sexism Scale as a covariate. The results indicated severity biases in perceptions of behaviors as well as in the types of interventions sought out. There was a significant positive correlation between scores on the modern sexism scale and higher likelihood of seeking out disciplinary actions through administration. In addition, there was a significant positive correlation between gender and likelihood of giving referrals for special education, as well as diagnostic services. Future research should continue evaluating how gender and severity biases act independently, as well as together within diagnostic systems of ASD, in addition to racial biases

Supporting a Racially Diverse Facial Dataset: Normative Valence and Arousal Ratings Across Race and Moderation by Race

The primary goal of this project was to collect normative emotional valence and arousal ratings using the RADIATE facial database. The RADIATE database is one of the few that is racially diverse, yet it is underutilized, due in part to a lack of normative valence and arousal ratings. A secondary goal was to explore whether the race of the rater moderated emotion ratings. As part of an ongoing study, 204 participants (Asian: 9, Black: 25, Latinx: 39, White: 131) were randomly assigned to one of 10 blocks of 36 faces. Each block included faces counterbalanced on race, gender, and emotion so that each participant rated an identical number of faces with respect to these categories. Participants viewed faces in Qualtrics and rated each on valence (from 1-9, unpleasant to pleasant) and arousal (from 1-9, low to high). A 4-way Race of Rater x Race of Face x Emotion x Gender repeated-measures ANOVA with repeated-measures on the last 3 factors was used for valence and arousal ratings. As expected, across racial face categories, happy faces were rated as more pleasant (M = 6.50) and sad faces as more unpleasant (M = 3.03). In addition, happy (M = 4.29) faces were rated more emotionally arousing than sad (M = 3.76) and neutral faces (M = 3.29). The race of the rater moderated valence but not arousal ratings. Black raters rated Asian females as happier than Asian males and Latinx raters rated Latinas as sadder than Latinos, with no other evident effects. Present results contribute to sparse valence and arousal data for the RADIATE dataset. Results further suggest that emotional faces are not rated in a universal manner as some emotion theories presume. Implications of the results and future research directions are discussed