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Association of residents’ personality traits with clinical performance in an orthopedic physical therapy residency program
No full textPurpose: Despite the lack of validity and reliability, residency programs use various assessments to admit residents and anticipate their future performance that include admission interviews and letters of recommendation. The purpose of this study is to examine whether there is a valid, reliable, or predictive association between physical therapy residents’ personality traits and their clinical performance in the domains of live patient examination, clinical productivity, and patient satisfaction during residency training.
Methods: This study was an observational cohort study. Each resident completed a standardized 16 Personal Factors Questionnaire (16 PF) on their respective hire date prior to matriculation in the physical therapy residency program.
Results: Results of the Spearman’s rho correlation indicated there was a strong positive association between those residents who were classified as more even-keeled (r = 0.473; p = 0.02) and meeting clinical productivity goals at 3 months. Better performance on the live patient examination was associated with residents who were identified as being people-oriented (r = 0.531; p = 0.02), gregarious (r = 0.464; p = 0.04), and fearless (r = 0.521; p = 0.02), while worse performance was associated with residents who were self-disclosing (r = -0.673; p = 0.00) and self-confident (r = -0.520; p = 0.02).
Conclusions: Identification of residents’ personality traits may be helpful in determining whether residents are likely to meet expectations in the domains of clinical productivity and performance on a live patient examination during the first 3 months of a post-professional physical therapy residency program
White Camphor and Peppercorn Hair: Blackness in Medieval Arabo-Asia
No full textReading classical Arabic and Chinese sources at once comparatively and intersectionally, this article initiates an investigation of Black labor—specifically Black sailors and slaves—employed in medieval trade networks that connect Africa, Arabia, and Persia to South Asia, Southeast Asia, and China. It does not presume a homogeneous definition of Blackness, nor a generalized notion of slavery. While informed by concepts developed in scholarly studies of transatlantic slavery and Euro-American colonial history, this article strives to expand our understanding of the global articulation of Blackness beyond both the modern period and the Atlantic world. I draw on numerous genres of classical literature—Islamic ḥadīth commentaries, stories of marvels, geographical works, poetry, Buddhist dictionaries, and polemical treatises—and corroborate them with visual evidence from the same or adjacent periods. Rather than aiming for a social history of Black labor, I suggest that we harness the magical qualities of these half-true, half-invented narratives, capitalize on their marvelousness, and instead of laying claim to a definitive account of who the Black sailors were and what they did, create new avenues of research and imagination that may help us regain access to the breathtakingly rich and layered world of a Black subalternity articulated translingually across the medieval Indian Ocean world
Indian Ocean Histories: Connections and Reflections
No full textIntroduction to the Special Dossier on Indian Ocean Historie
Faith, Freedom, and Favors
No full textThis essay aims to situate Shannon Chakraborty's work within the broader tradition of American Muslim science fiction and fantasy literature. 
Khaana Khazana: Food Labor in Cosmopolitan India
No full textThis work aims to understand the relationship between food workers, gender norms, and class dynamics within economically and culturally diverse Indian cities. While food workers, specifically chefs and line cooks, inhabit a central role in urban food economies and cultural systems, their labor and positionality transcend the spatial confines of a restaurant. However, present research solely focuses on food workers as laborers, rather than considering how their positionality shapes local and regional sociopolitical processes. This gap has manifested in both the subjugation of food workers to the boundaries of the restaurant and a dearth of insight into their perspective regarding the experiences, principles, and values that govern their work. The physical space thus provides ethnographic glimpses of restaurants in India; the consumers and food workers present in a restaurant interact with the spatial boundaries of the eatery in significant ways. Interviews with the food laborers reveal wider implications about social values from their position in both local and global political economies.
I contend that the experiences of food workers display characteristics of broader sociopolitical frameworks, where food workers contribute to the creation of sociopolitical cleavages within domestic and professional spaces. This research bridges these gaps through the triangulation of participant observation, qualitative interviews, and menu analysis at four eateries in Mumbai conducted over a week. I find that occupational limitations and systemic inequity of urban India faced by chefs have contributed to their views on gender, language, and westernization, thus impacting the larger political economy. The research suggests that Western ideals and influence shaped how some food workers in the Mumbai restaurant scene approached their work, while fiscal necessity motivated others. My study suggests important findings about the interplay between political economy and social factors—such as class, gender, and westernization—for food workers in major cities of the Global South. Through this project, I hope to highlight the agency of food workers: rather than viewing them through their occupation, this paper endeavors to view their occupation from the perspectives of food workers themselves
On Manifold Dimension Estimation
Full text linkThis thesis is a review of algorithms and statistical complexity results for the manifold intrinsic dimension (ID) estimation problem. The task is as follows: given an independent and identically distributed sample of points from a low-dimensional submanifold embedded in high-dimensional Euclidean space, determine the dimension of the submanifold. This problem is of key interest in data science, as many algorithms can be made to depend on the intrinsic dimension of data, rather than the dimension of its ambient space. We pay close attention to the linear case of this problem, which reduces to principle component analysis (PCA). In the general manifold case, the kinds of approaches become much more diverse. We distinguish two very different kinds of methods: (1) those which isolate a local statistic (e.g., number of neighbors within a certain radius) and analyze its scaling behavior in varying neighborhood sizes, and (2) those which analyze a global statistic and its scaling behavior independent of local information (e.g., the Wasserstein distance between two independently-formed empirical distributions, and how it scales with the size of their samples). We then compare lower bounds on the sample complexity of ID estimation, in a model with noise and a model without