Fostering Transformative Learning, Self-reflexivity and Medical Citizenship Through Guided Tours of Disadvantaged Neighborhoods

Background and objectives: Medical school curricula increasingly seek to promote medical students’ commitment to redressing health disparities, but traditional pedagogical approaches have fallen short of this goal. The objective of this work was to assess the value of using community-based guided tours of disadvantaged neighborhoods to fill this gap. Methods: A total of 50 second-year medical students participated in a guided tour of disadvantaged public housing neighborhoods in Richmond, Virginia. Students completed self-reflexive writing exercises during a post-tour debriefing session. Student writings were analyzed to assess the tour’s effect on their awareness of poverty’s impact on vulnerable populations’ health and wellbeing, and their personal reactions to the tour. Results: Student writings indicated that the activity fostered transformative learning experiences around the issue of poverty and its effects on health and stimulated a personal commitment to working with underserved populations. Themes from qualitative analysis included: increased awareness of the extent of poverty, enhanced self-reflexive attitude towards personal feelings, biases and misperceptions concerning the poor, increased intentional awareness of the effects of poverty on patient health and well-being, and, encouragement to pursue careers of medical service. Conclusions: This pilot demonstrated that incorporating self-reflexive learning exercises into a brief community-based guided tour can enhance the social consciousness of medical students by deepening understandings of health disparities and promoting transformative learning experiences

Engaging with the Dory Fleet: A Panel Discussion on a Collaborative College and Community Oral History Project

This peer-reviewed program was presented at the annual Northwest Communication Association Conference in Coeur d’Alene Idaho on April 15, 2016. The presentation features an overview of the Launching through the Surf: The Dory Fleet of Pacific City project and includes detailed notes from each speaker. Special thanks go to Mary Beth Jones and Brenda DeVore Marshall, who served as transcriber and editor for the detailed speaker notes

Gender and the construction of identity within climate technology innovation in Kenya

This paper undertakes an analysis of the discursive construction of the entrepreneurial identity within media on climate technology(CT) innovation in Kenya. Using the STEPS pathways approach along side a post-structuralist feminist identity framework, it explores the way that the narrative of entrepreneur-led innovation may include or exclude the framings of particular actors. The paper draws on ideas of antagonism in identity construction, legitimacy, and access to resources, in order to identify those actors that may perceive themselves as, or be perceived as, more or less legitimate as CT entrepreneurs, thus being more or less likely to gain access to resources for CT innovation. Although the climate technology entrepreneur aligns in some ways with more normatively feminine notions of the caring social entrepreneur, overall the CT entrepreneur remains a masculine identity. Women are underrepresented in media portrayals of CT entrepreneurship.Further, portrayals of women CT entrepreneurs tend to question their legitimacy, depicting them as either requiring the support of men, or as taking up masculine characteristics in order to gain credibility. The paper demonstrates that this might translate into more favourable attitudes towards men CT entrepreneurs when seeking access to institutional support. It recommends further research into the capacity for CT entrepreneurship to effectively incorporate marginalised framings, and where entrepreneurship will fail to meet their needs, it calls for increased support for appropriate alternative processes of climate technology innovation

Mitigating Advocacy Bias: The Effect Of The Reviewer Role On Tax Professional Judgment

Prior literature finds tax professionals exhibit advocacy bias, a threat to tax professionals’ objectivity, which can expose accounting firms and their clients to penalties for overly aggressive tax reporting decisions. Mitigating this bias has been the topic of several prior studies; however, research thus far has focused on how reviewers identify bias within tax research memorandums (e.g., stylized writing or other obvious cues). In an experiment administered to seventy-five tax professionals, this study isolates the effect of the reviewer role and compares professionals’ evidence evaluation and conclusions by role (i.e., reviewer or preparer). I find professionals who occupy the reviewer role are significantly less likely to exhibit advocacy bias than those who are in a preparer role, which suggests the reviewer role changes how professionals approach evidence evaluation. In addition, I examine the influence of accountability on tax professionals’ judgments. I find initial evidence that accountability influences the likelihood of professionals’ exhibiting advocacy bias

The Committee Chair's Role.

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Exploring the Mathematical Thinking of Bilingual Primary-Grade Students: CGI Problem Solving From Kindergarten Through 2nd Grade

This study explores the mathematical thinking of native Spanish-speaking, primary-grade Latina/o students learning in bilingual classrooms where the majority of their mathematics instruction has been in Spanish. Guided by sociocultural theory, which emphasizes the important connection between language and conceptual development (Mahn, 2008; Sfard, 2001; Van Oers, 2001; Zack & Graves, 2001), and the theory and methods of Cognitively Guided Instruction [CGI] (Carpenter, Ansell, Franke, Fennema & Weisbeck, 1993; Carpenter, Fennema & Franke, 1994; Carpenter, Fennema & Franke, 1996; Carpenter, Fennema, Franke, Levi & Empson, 1999; Fennema, Franke, Carpenter & Carey, 1993; Turner, Celedón-Pattichis & Marshall, 2008), data were collected on students developing abilities to solve CGI problems and explain their thinking about their solutions. An expanded notion of mathematical explanations and discourse was used in the analysis that goes beyond student language to include their gestures, the tools they selected as problem solving aids, and their drawings and equations (Gee & Green, 1998; Moschkovich, 2002). This qualitative, longitudinal study is based on individual CGI interviews with four students over the course of their first three years in school and follows a grounded theory tradition (Creswell, 1998; Glaser & Strauss, 1980) to uncover themes in their mathematical thinking. The overarching motivation for this research was one of equity where the broader methodology sought to encourage a high-quality mathematics learning environment for Spanish-speaking, Mexican immigrant students in bilingual classrooms (Secada & De La Cruz, 1996). Groundbreaking findings from this study add to the literature on how young students make sense of the numbers in mathematical word problems (Fuson, 1988). The findings demonstrate that students are making sense of the numbers in fundamentally different ways and carry major implications for CGI theory, mathematics teaching and learning, and sociocultural theory. Of particular interest to the field of bilingual education is the way students engage with CGI problems when the problems have been contextualized within students\u27 native language and culture (Cummins, 2001; Secada & De La Cruz, 1996). Additionally, this study demonstrates how bilingual students use two languages, Spanish and English, to explain their mathematical thinking and describe their problem solving strategies.\u2

Improving Advertisement Delivery in Video Streaming

Generally, the present disclosure is directed to improving advertisement delivery based on the content of a video. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a non-intrusive location for an advertisement based on the content of a video