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Item 3: Assignment 1: Civic Engagement and Citizenship Matter: Write an Op-Ed
No full textThis assignment allows students to demonstrate active citizenship because it provides students with an opportunity to develop their writing skills by writing a persuasive op-ed about civic engagement and citizenship. American political culture embodies the role of the citizen in the democratic process and writing an op-ed is one way for a citizen to articulate their beliefs about issues in society
Item 4: Activity 3: Surfacing Values Through Moral Foundation Conversations
No full textThis activity explores the concept of motivated reasoning and the moral foundations people hold that make them believe wicked issues are “wicked.” Students will explore their own values and think about how their values change depending on the issue. Students will also practice talking with people who have different values than them on any given issue
Item 6: Assignment 1: Deliberating Across Divides to Find Common Ground
No full textMany students struggle to engage in conversations with people who hold different views. Fear of saying the wrong thing—or being “canceled”—can discourage open dialogue, yet democratic societies rely on the ability to deliberate across divides. This assignment gives students the opportunity to practice deliberation, a structured way of discussing complex, “wicked” issues while fostering mutual understanding, respect, and hopefully finding common ground to act together. Following the deliberation, students will write a reflection analyzing their experience, exploring what they learned from listening to diverse perspectives, and how civic leaders can use deliberation to foster productive dialogue in divided communities
Item 6: Activity: Information Literacy and Advocacy Groups
No full textThis activity guides students in reviewing an advocacy organization. Using critical information literacy skills, students will evaluate the organization’s mission, activities, leadership, and funding, analyzing how it presents information. Students will also consider the role of power in shaping the information presented by the organization, examining how power dynamics may influence the framing of an issue and the strategies used for advocacy
Multiple View Neural Regression of a Facial Shape Model
Full text linkCreating re-topologized 3D facial meshes is a critical step in high-quality facial animation pipelines, yet it remains a labor-intensive and time-consuming task. Traditional approaches typically rely on multiview stereo reconstruction and specialized photometric environments to acquire accurate geometric and reflectance data under controlled conditions. This dissertation presents work toward more efficient capture of production-ready meshes including (1) developmental aspects of VarIS, a custom-designed light sphere capable of capturing high-resolution stereo geometry and reflectance maps—including diffuse, specular, and normal components under programmable illumination; (2) a study of the effects of camera parameters on automatic 2D and 3D landmarking methods, (3) methods for using synthetic data to train neural face regression, and (4) techniques proposed to improve neural multi-view regression of face shape.
While VarIS enables photorealistic face capture, its operational cost and the need for manual processing of its acquired data highlight the need for a more scalable solution. To address this, a deep learning–based framework is proposed, enabling direct prediction of re-topologized facial meshes from synthetic multiview images. Training data was generated using Visage Craft, an in-house rendering system built upon a physically based Appearance 3D Morphable Model (A3DMM). The method infers dense mesh geometry in a standardized format ready to rig and animate.
Results demonstrate that integrating precise camera intrinsics and extrinsics during training markedly improves landmark accuracy and geometric consistency, and incorporating 3D landmarks themselves in the regularization of the network also improves results. The final system presents a robust, data-driven alternative to conventional face analysis/synthesis workflows, capable of producing facial meshes with minimal human supervision
Gender and Entrepreneurial Success: Examining the Relationships Among Risk Aversion, Loss Aversion, Risk Propensity, and Venture Performance
Full text linkGender disparities in entrepreneurship persist despite increased participation by women entrepreneurs. Traditional research has attributed these disparities to gender differences in risk-taking behavior, with women entrepreneurs typically characterized as more risk-averse. However, recent evidence suggests this oversimplifies a complex phenomenon and may reinforce harmful stereotypes. This study examined the relationships among risk aversion, loss aversion, risk propensity, and venture performance for male and female entrepreneurs, while considering moderating effects of industry gender-type and previous experience.
A quantitative cross-sectional design was employed with 157 entrepreneurs (93 female, 64 male) recruited from entrepreneurial organizations. Risk aversion was measured using the Domain-Specific Risk-Taking (DOSPERT) scale (α = .943), loss aversion using the Loss Aversion Measurement (LAM) scale, and risk propensity using the Risk Propensity Scale (α = .760). Venture performance was assessed through growth metrics and subjective performance measures. Data analysis included independent samples t-tests, correlation analysis, and moderation analysis using interaction terms.
Contrary to hypotheses, no significant gender differences were found in risk aversion (t(155) = -0.478, p = .317, d = -0.078), loss aversion (t(151) = 1.11, p = .865), or risk propensity (t(155) = 0.84, p = .799, d = 0.136). Female entrepreneurs did not demonstrate superior venture performance compared to males (U = 2810, p = .667, d = ‑0.044). Loss aversion did not have a stronger influence on female entrepreneurs’ risk propensity than males’ (β = 0.002, p = .762). Industry gender composition and previous experience did not significantly moderate the relationship between risk propensity and venture performance. However, risk propensity was positively correlated with venture growth intention (r = .341, p \u3c .001) and perceived success (r = -.224, p = .005), regardless of gender.
These findings challenge traditional assumptions about gender differences in entrepreneurial risk-taking, suggesting that male and female entrepreneurs are more similar than different in their risk attitudes and behaviors. The results indicate that gender-based stereotypes about risk aversion may be unfounded and call for more nuanced approaches to understanding entrepreneurial decision-making. Implications include the need for gender-neutral entrepreneurship training programs, unbiased investment evaluation criteria, and support systems based on individual rather than gender-based characteristics. Future research should employ longitudinal designs and explore alternative explanations for persistent gender disparities in entrepreneurial outcomes
