The University of Pittsburgh at Greensburg (Pitt-Greensburg or UPG) is a state-related liberal arts college in Greensburg, Pennsylvania. It is a baccalaureate degree-granting regional campus of the University of Pittsburgh. Opened in 1963, Pitt-Greensburg was granted four-year degree-granting status in 1988. As of 2020, Pitt-Greensburg had 1,439 undergraduates and 96 faculty.
Phage QuinnAvery produces turbid plaques in Arthrobacter globiformis B-2979 lawns, displays a siphovirus morphology, and is clustered with FF actinobacteriophages. The 43,177 bp genome of QuinnAvery is predicted to contain a tRNA-Arg(TCT) gene and 69 protein-coding genes. Homologs of a subset of QuinnAvery's predicted genes have putative roles in viral structure, particle assembly, host cell lysis, and lysogeny. QuinnAvery's genome is predicted to contain two tyrosine integrases, similar to many other cluster FF phages. However, the area immediately surrounding the integration cassette in QuinnAvery is distinct from all other annotated members of cluster FF.
While lesbian, gay, bisexual, or transgender (LGBT) and Christian identities are often thought of as being politically conflicting, many LGBT Americans identify as Christian. Yet, there is limited research on how these identities interact to shape the political attitudes and behaviors of people at their intersections. Even less is known about how these dynamics vary by indicators of religious belonging and religiosity. Using 2020 Cooperative Election Study data, we examine whether politically conflicting LGBT and Christian identities correspond with higher levels of three indicators of political cross-pressures: ambivalence, moderation, and disengagement. Our findings reveal inconsistent patterns. While LGBT Christians and non-religious cisgender-heterosexual people exhibit more signs of being cross-pressured than non-religious LGBT people, cisgender-heterosexual Christians were often more cross-pressured than other groups. These findings suggest that (1) the influence of cross-pressures on political attitudes and behaviors may be more complex than previously theorized, and (2) who engages in politics and vocalizes their policy preferences may have implications for whose policy preferences are enacted.
Traditional undergraduate science courses often prioritize content mastery over authentic engagement with the scientific process. Course-based research, also referred to as course-based undergraduate research experiences (CUREs), addresses this limitation by immersing students in authentic scientific practice. In course-based research, assessment practices can also mirror the authentic scientific practice, where extensive formative feedback supports refinement of skills and understanding. Here, we present two rubrics designed to support the teaching and assessment of science communication in a way that reflects how scientists prepare to disseminate their research findings. One rubric is for creating scientific posters and another for writing short-format manuscripts. Developed by approximately 100 faculty members who collaboratively implement CUREs through the Howard Hughes Medical Institute (HHMI) Science Education Alliance (SEA) program, these rubrics outline the authentic steps scientists take when preparing to communicate their research and provide performance levels that clarify expectations for both students and instructors. Together, these tools aim to further align undergraduate science education and authentic scientific practice.
In higher education, students increasingly compose with generative Artificial Intelligence (AI) technologies amid evolving institutional expectations and uncertain guidelines for AI use. While existing scholarship often focuses on the technical or ethical implications of AI, less attention has been paid to the affective conditions through which students navigate AI-mediated literacy practices. Drawing on a postdigital perspective, this study examines how students’ encounters with AI unfold within entangled relations among human and nonhuman actors, including peers, instructors, institutional policies, and technological systems. Drawing on focus group interviews with undergraduate students across four campuses of a public university in Midatlantic United States, this study identified three affective assemblages: First, ambiguous and uneven AI policies generated uncertainty and prompted students to develop self-made guidelines for AI use. Second, student–peer–faculty interactions produced distributed forms of response-ability, as students negotiated trust, frustration, and ethical judgment within relational networks. Third, students articulated affective imaginaries of AI-mediated futures and expressed both anxieties about neoliberal ideologies of automation and hopeful visions of new forms of critical and relational literacy. The study contributes to AI literacy research by illustrating how students’ engagements with AI are formed through postdigital affective assemblages of people, technologies, policies, and emotions. It concludes by discussing how educators might design learning environments that support students in developing critical and ethical AI literacy within postdigital educational contexts.
