Highest Rated Papers
CodeAct: Your LLM Agent Acts Better when Generating Code - Apple Machine Learning Research
Unknown Author
Apple Machine Learning Research
Large Language Model (LLM) agents, capable of performing a broad range of actions, such as invoking tools and controlling robots, show great…
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View paper →Queer Fear: Vampirism and the Transmittable Evil of Homoeroticism
Carmona, Carla
etd.library.emory.edu·2021
The alluring vampire has consistently been one of media’s most resourceful monsters. As a human-monster hybrid, authors ascribe communal human fears to the vampiric figures—fears that often resort to villainizing the unknown or the dissenting. Vampires are often queer-coded individuals who transgress heteronormative hegemony. This queer-coding resulted in the vampire becoming a figure of excess and ultimately, the utilization of the vampire to communicate the fear of the queer. This thesis explores the intersection between queerness and vampirism. While vampirism can be a metaphor for the transgression of the status quo, the vampire’s grim fate invites speculation over queer-coding’s effectiveness—and ultimately, its intentions. To audiences, the lines between fiction and reality may blur. Therefore, the analysis of homophobic messages in vampiric fiction is necessary to understand why these tropes are employed. This thesis analyzes monumental vampiric texts, such as Dracula, Carmilla, and Interview with the Vampire to understand how each text’s manifestations of queerness mold narrative human fears.
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View paper →A Meta-Analysis of Group Interventions for Trauma and Depression Among Immigrant and Refugee Children
Maryam Rafieifar, Mark J. Macgowan
Research on Social Work Practice·2021·22 citations
Purpose:
A meta-analysis of group interventions to reduce post-traumatic stress symptoms (PTSS) and/or depression among refugee and immigrant children and adolescents.
Methods:
A systematic search was followed by independent reviews of each study for risk of bias. The meta-analysis pooled between- and within-condition effect sizes on PTSS and depression across studies using a random effects model.
Results:
The search yielded 16 studies utilizing eight interventions involving 976 participants. For all studies, within conditions, there were good effects on PTSS ( d = −0.66, 95% CI [−0.86, −0.46]) and depression ( d = −0.51, 95% CI [−0.79, −0.23]) with substantial heterogeneity. For studies with control groups, the between-group effect sizes yielded a small effect on PTSS ( d = −0.31, 95% CI [−0.65, 0.03]) with no significant effect on depression.
Conclusions:
The interventions helped to reduce PTSS and depression. Most studies lacked rigorous designs and provided little information on group variables needed for replication.
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