U.S. Women Faculty in the Social Sciences Also Face Gender Inequalities.

There is a national interest in United States women's underrepresentation in science, technology, engineering, and mathematics (STEM); however, gender inequality in the social sciences has not received similar attention. Although women increasingly earn postgraduate degrees in the social sciences, women faculty still experience gender inequities. Consistent gender inequities include slower career advancement, blunted salaries, unequal workloads, work-life conflict, systemic gender biases, underrepresentation in positions of power, and hostile work environments. Cultural biases suggest that once women have achieved parity, gender bias no longer exists. This review challenges that notion by providing evidence from social science domains in which women are well-represented but continue to face systemic gender biases. We examine cultural influences on gender representation and career advancement in psychology, economics, political science, sociology, and anthropology. We make interdisciplinary comparisons of career trajectories and salaries using national data, documenting patterns across the social sciences. For example, women economists face gendered standards in publishing, and women political scientists are less likely to have their work cited than men. Furthermore, data show that salaries become stagnant as the representation of women in these fields increases. These disparities reflect cultural biases in perceptions of women's competence stemming from social role theory. We discuss best practices to address these problems, focusing on the ADVANCE organizational change programs funded by the National Science Foundation that target (a) improving academic climate, (b) providing professional development, and (c) fostering social networking. Federally supported interventions can reveal systemic gender biases in academia and reduce gender disparities for women academics in the social sciences.

Screening Accuracy of the Brief Infant Toddler Social-Emotional Assessment to Identify Autism Spectrum Disorder in Toddlers Born at Less Than 30 Weeks' Gestation.

Despite the higher prevalence of autism spectrum disorder (ASD) in children born preterm, valid screening tools for use in preterm populations are lacking. We aimed to evaluate the screening accuracy of the Brief Infant Toddler Social-Emotional Assessment (BITSEA) and to compare it to the Pervasive Developmental Disorders Screening Test-II, Stage 2, Developmental Clinic Screener (PDDST-II-DCS) in identifying ASD diagnosis in toddlers born at < 30 weeks' gestation. Caregivers (94% mothers) of 555 children completed questionnaires (BITSEA, PDDST-II-DCS, socio-demographics) when the children (58% male) were 18-36 months. Medical charts were abstracted 3.5 years later and showed that 4% (n = 24) of children had an ASD diagnosis. BITSEA competence (sensitivity = .74; specificity = .76) and ASD (sensitivity = .70; specificity = .73) subscales demonstrated better accuracy in identifying ASD compared to the recommended PDDST-II-DCS cut-score (sensitivity = .73; specificity = .64), specifically as it related to specificity. Additional studies are needed in other preterm populations to replicate these findings.