First, this paper argues that applications of SCOT in feminist science and technology studies have largely focused on analyzing how gender and technology are coproduced, resulting in lack of scholarship that examines the mutually constitutive relationship between technology, gender and other intersecting categories, such as race, ethnicity, class, sexual orientation, and ability. Second, this paper argues that an intersectional view of technology can dismantle the language of objectivity deeply embedded in technological artifacts by revealing how identity categories, such as gender, race, and ethnicity, are integral components of “the social shaping of technology” and by extension participation in technological initiatives (Faulkner, p. 90, 2001). Finally, through a brief discussion of CompuGirls, a culturally responsive technology program for girls of color, this paper demonstrates how an intersectional, social constructionist approach to technology education can challenge stereotypes of girls of color as passive victims of technology and provide a counter-narrative that can empower girls of color to form generative relationships with technology.

The practical relevance of neonatal imitation for social development has remained largely unaddressed as most studieshave been conducted in highly controlled, laboratory conditions. Utilizing the Lookit online infant experiment platform,we aim to demonstrate the feasibility of measuring neonatal imitation of caregivers in the home environment. Our between-subjects design, adapted from Meltzoff and Moore (1983), focuses on two of the most commonly studied neonatal gestures,tongue protrusion and mouth opening. Caregivers and their newborn are videotaped as caregivers model either gestureto their newborn. Coders, who are blind to condition, record newborns gesture frequencies. To analyze these data,we ultimately plan to specify a Bayesian hierarchical log-linear model testing whether the frequency of each neonatalgesture increased when caregivers modeled that specific gesture. Pilot data collection and behavioral coding are currentlyunderway and will focus on inter-rater reliability, attrition, and recruitment rates of online data collection for neonatalimitation.