Though Frank O’Hara’s poetry is widely recognized as an important queer poet and read for its queer content, little work has explicated the ways in the poems serve as an example of a queer poetics. As such, this project reads O’Hara’s poetic thinking, focusing on his college journal and early writing, his poems to and about Bunny Lang, his poems that explicitly address poems and readers, his love poems to Vincent Warren, and his poetic statements. In doing so, I argue that his poetic statement, “Personism: A Manifesto,” is the culmination of a long history of thinking about poetry in which I read his concept of Personism as a poetics of queer defiance. I trace the figure of the poetic “speaking voice,” a concept popularized by Reuben Brower—who himself drew upon a history of scholars whose work separated the poet from the “I” of a poem—which was coalescing at the same time O’Hara was emerging as a poet. This critical ethos would become a dominant model for thinking about poetry which would be institutionalized into a norm, but at the time of his writing, I argue, O’Hara’s work pushed back on this model. Instead of presenting a “speaking voice” detached from the poet and the poet’s life, I argue that O’Hara’s poetics of Personism allow him to assert historical presence as a queer person, fugitively documenting his life into history. His work defies New Critical logic around a poetry belonging to a reading public, which depends upon universalizing the poetic speaker, stripping the social specificity away from the “I” of a poem, instead writing poetry that refused that sort of removal. It can be difficult to see this resistance without reading O’Hara’s work alongside its contemporary poetic thinking, because many current approaches in queer theory rely on a normative understanding of how to read a poem, which is informed by the New Critical model and can lead to a failure to recognize the ways in which O’Hara poems are inherently queer. My aim, then, is to recontextualize O’Hara’s work, to trace his thinking about and against a “speaking voice,” and present his poetics of Personism as a poetics of queer defiance.

Economics is primarily a non-experimental science. Typically, we cannot generate new data sets on which to test hypotheses independently of the data that may have led to a particular theory. The common practice of using the same data set to formulate and test hypotheses introduces data-snooping biases that, if not accounted for, invalidate the assumptions underlying classical statistical inference. A striking example of a data-driven discovery is the presence of calendar effects in stock returns. There appears to be very substantial evidence of systematic abnormal stock returns related to the day of the week, the week of the month, the month of the year, the turn of the month, holidays, and so forth. However, this evidence has largely been considered without accounting for the intensive search preceding it. In this paper we use 100 years of daily data and a new bootstrap procedure that allows us to explicitly measure the distortions in statistical inference induced by data-snooping. We find that although nominal P-values of individual calendar rules are extremely significant, once evaluated in the context of the full universe from which such rules were drawn, calendar effects no longer remain significant.

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Introduction: E-learning is widely used in medical education. To maximize the potential of E-learning tools, every effort should be made to encourage adoption by optimizing usability. We created Learning Moment (LM), a web-based application that integrates principles of asynchronous learning and learning portfolios into a platform on which students can document and share learning experiences that occur during clinical work. We sought to evaluate the usability of LM and identify features that optimize adoption by users.

Methods: We implemented LM in August 2016 at a busy, urban, tertiary care emergency department that hosts an emergency medicine residency, robust third and fourth year medical student clerkships as well as a physician assistant student rotation. We conducted a single-center, mix-methods study using the System Usability Scale (SUS) questionnaire and qualitative interviews. We sent e-mail invitations with subsequent reminders to all students who rotated in our emergency medicine clerkship from August 2016 to April 2017 to complete the SUS questionnaire anonymously and to participate in qualitative interviews. We employed purposive sampling to recruit students who used LM during their rotation to participate in our qualitative interviews. We conducted semi-structured interviews with 13 participants (10 individual interviews and one 3-person group interview) between January and March 2017 using an ethnographic approach and utilized a general inductive method to analyze and code for potential themes.

Results: Thirty of the seventy students invited to participate completed the SUS questionnaire (Response rate of 42.8%). The mean SUS score is 80.9 (SD 18.2, 80% CI 76.5 – 85.3). The internal consistency of the responses achieved the Cronbach’s Alpha of 0.95. The participants stressed the importance of the following in the adoption of LM: maximal simplicity and usability, compatibility with learning preferences, and department-wide acceptance and integration.

Conclusion: The overall perceived usability of LM was high. Our qualitative data revealed important implications for future designers to maximize adoption: include target users in every step of the design and development process to maximize simplicity and usability; build features that cater to a diversity of learning preferences; involve the entire department and find ways to incorporate the tool into the educational infrastructure and daily workflow.