| | 01 | M------ | 9:00A-12:00P | TBA | Eyler | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | --W---- | 9:00A-12:00P | TBA | Eyler | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 03 | -T----- | 1:00P-4:00P | TBA | Shields | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 04 | -T----- | 9:00A-12:00P | TBA | Shields | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -T----- | 1:00P-4:00P | TBA | Mckay | Default - none | 24 | 0 | 0 | | |
| 02 | --W---- | 9:00A-12:00P | TBA | Caburnay | Default - none | 24 | 0 | 0 | | |
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| | 01 | M------ | 5:30P-8:30P | TBA | Tabak | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | -T----- | 5:30P-8:30P | TBA | Tutlam | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 04 | --W---- | 1:00P-4:00P | TBA | Effah | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 02 | --W---- | 5:30P-8:30P | TBA | Brugger | Default - none | 25 | 0 | 0 | Desc: | Instruction in this course will utilize R for statistical computing.
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| | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 03 | -T----- | 1:00P-4:00P | Remote / SW | Harris | Default - none | 25 | 0 | 0 | Desc: | Instruction in this course section will utilize R for statistical computing.
This is a REMOTE course.
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| | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 04 | M------ | 9:00A-12:00P | TBA | Steensma | Default - none | 25 | 0 | 0 | Desc: | Instruction in this course section will utilize SPSS for statistical computing. |
| | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 05 | M------ | 1:00P-4:00P | TBA | Steensma | Default - none | 25 | 0 | 0 | Desc: | Instruction in this course section will utilize SPSS for statistical computing. |
| | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | [TBA] | Default - none | 25 | 0 | 0 | | |
| 02 | M------ | 9:00A-12:00P | TBA | Moreland-Russell | Default - none | 25 | 0 | 0 | | |
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| | 01 | --W---- | 1:00P-4:00P | TBA | Serrano | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | ---R--- | 1:00P-4:00P | TBA | Serrano | Default - none | 25 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -----S- | 9:00A-12:00P | TBA | Cameron | Default - none | 20 | 0 | 0 | Desc: | This course will be taught in a hybrid format.
Course Dates: 9/14 & 9/28 |
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| | 01 | --W---- | 1:00P-4:00P | TBA | Cameron | Default - none | 18 | 0 | 0 | | |
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| | 01 | --W---- | 9:00A-12:00P | TBA | Cameron | Default - none | 18 | 0 | 0 | | |
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| | 01 | ---R--- | 1:00P-4:00P | TBA | Tetteh | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | Policy has a well-documented, powerful and sustained effect on public health indicators. This course covers the epidemiologic basis for health policy, types of policy evidence, policy theories, study designs for understanding the effects of policy, methods of policy communication, and current controversies. Course content will be covered through readings, individual and group exercises, case studies, lectures, and discussions. Prerequisite: S55-5002
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| | 01 | --W---- | 9:00A-12:00P | TBA | Brownson | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -T----- | 1:00P-4:00P | TBA | Brown | Default - none | 16 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | This course aims to provide participants with an in-depth understanding of the current debates that are shaping Global Mental Health (GMH) in Low and Middle Income Countries (LMICs). It examines the history of GMH, its key principles, policies and practices alongside the challenges inherent to their implementation in some of the most challenging contexts. Using practical examples of GMH interventions in the area of stigma, depression, trauma and the mental health of marginalized populations, students will be encouraged to critically engage with concepts relevant to, social work, public health, sociology and anthropology so as to reflect on the design, applicability and relevance of such interventions. Furthermore, the course will examine several key issues inherent to the field, such as the cultural validity of modern psychiatric diagnosis, as well as its research methods and assessment techniques. Guest speakers will include individuals working on the forefront of GMH application. The course is designed to compel future social workers to "think globally" but "act locally" when debating and addressing mental health issues in an international context. |
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| | 01 | -T----- | 5:30P-8:30P | Remote / SW | Bayetti | Default - none | 26 | 0 | 0 | | |
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| | 01 | ---R--- | 5:30P-8:30P | Remote / SW | Bayetti | Default - none | 18 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | [TBA] | Default - none | 18 | 0 | 0 | | | |
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| | 01 | ---R--- | 5:30P-8:30P | TBA | Cameron | Default - none | 20 | 0 | 0 | Desc: | This course will be taught in a hybrid format.
Course Dates: 9/12 & 9/26 |
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| | 01 | ---R--- | 9:00A-11:00A | TBA | [TBA] | Default - none | 20 | 0 | 0 | Desc: | All students enrolled in Section 01 must also enroll in Lab A.
Instruction in this course section will utilize R for statistical computing.
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| | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| A | ---R--- | 11:00A-12:00P | TBA | [TBA] | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -T----- | 1:00P-4:00P | TBA | Levy | Default - none | 24 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | --W---- | 1:00P-4:00P | TBA | Han, Barbier | Default - none | 24 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | ---R--- | 1:00P-4:00P | TBA | Johnson | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | --W---- | 1:00P-4:00P | TBA | Johnson | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | This transdisciplinary problem-solving course explores the complexity and reciprocity of human nutrition and a changing environment. Globally, food systems contribute over 30% of greenhouse gas emissions, 70% of freshwater retrievals, and 40% of land use, yet enormous inequities persist in terms of access to high quality foods, malnutrition prevalence, and the impacts of climate change on food security. This course provides foundational knowledge in public health nutrition from cells to society and the skills necessary to critically analyze sustainability issues related to food systems. We then cover novel as well as evidence-based solutions to achieving sustainable, healthy, and equitable food systems. Learning labs (dietary assessment, anthropometric measures, etc.), field trips (WashU edible plant tour, community gardens, etc.) and guest lectures from leaders in the field are integral to course learning. |
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| | 01 | ---R--- | 9:00A-12:00P | TBA | Iannotti | Default - none | 18 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| | 01 | -T----- | 1:00P-4:00P | TBA | Steensma | Default - none | 16 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -T----- | 1:00P-4:00P | TBA | Jonson-Reid, Drake | Default - none | 16 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | This course has controlled registration for all students. Priority is given based on degree requirements. All students who wish to enroll in this course should add themselves to the waitlist. This course will provide an overview of the critical issues in global reproductive health, covering basic reproductive biology and epidemiological trends related to contraceptive use, fertility, and adverse birth outcomes. Additionally, applying a solutions-based approach, we will use key theoretical frameworks and cases studies from the field to understand the influence of social, behavioral, and environmental factors on adverse reproductive health outcomes. Finally, students will be engaged in topics related to what the field has achieved thus far, including: changes in policies, laws, and development approaches; the use of new technologies; the promotion of constructive male engagement; and overall improvements in outcomes related to family planning, fertility, maternal health, violence, sexually transmitted infections, and HIV/AIDS. Obstacles to progress such as waning political commitment, trends in funding, weakened health systems, and cultural opposition, will also be discussed. |
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| | 01 | --W---- | 9:00A-12:00P | TBA | Levy | Default - none | 24 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | ---R--- | 1:00P-4:00P | TBA | Ballard | Default - none | 18 | 0 | 0 | | |
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| Description: | Data are now available to social scientists in a way and quantity that has never existed before, presenting unprecedented opportunities for advancing social research and practices through state-of-the-art data analytics. On the other hand, dealing with extensive, complex, unconventional "big data" (e.g., free text, image, video/audio recording) requires revolutionary analytic tools only made available during the past decade. Artificial intelligence (AI), characterized by machine and deep learning, has become increasingly recognized as an indispensable tool in modern social and behavioral sciences. For example, AI methodologies have been applied to enhance the effectiveness of diagnosis and prediction of disease conditions, advance understanding of human development and functioning, and improve the effectiveness of data management in various social and human services.
As a subdomain of AI, deep learning is based on artificial neural networks in which multiple ("deep") layers of processing are used to extract higher-level features progressively from data. This layered representation enables modeling more complex, dynamic patterns than the traditional machine learning (which sometimes are called "shallow learning" as in contrast to deep learning), which finds its utility in analyzing the "big data"-data massive in scale and "messy" to work with (e.g., unstructured texts, images, audios, and videos).
This course contributes to the overarching goal of training next-generation researchers in modern data analytics. It aims to equip students with the core knowledge and essential skills to apply deep learning models to address real-world problems. Through the course, students will familiarize themselves with computer programming in data science, learn state-of-the-art deep learning models, and apply them to social and behavioral questions. In addition, one essential field of deep learning applications is assisting decision-making through identifying patterns and trends, improving prediction precision, and automating evidence collection, synthetization, and dissemination. Students who master deep learning tools will be at the frontier to leverage the power of AI in analytics and practices. |
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| | 01 | -T----- | 9:00A-12:00P | TBA | An | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | This course introduces the state-of-the-art applications of generative artificial intelligence (Gen AI) using Python, with a focus on creating innovative solutions in various domains. Gen AI represents a cutting-edge subset of AI, which involves machines generating new data, such as text or images, by learning patterns from existing data. The emergence of advanced deep learning techniques has revolutionized this field, leading to numerous practical applications. Python, an interpreted, high-level, and general-purpose programming language, plays a pivotal role in implementing Gen AI models due to its simplicity and powerful libraries. Prerequisite: S55-5601 (Applied Deep Learning Using Health Data), S55-5139 (Applied Machine Learning Using Health Data), proficiency in Python or instructor approval. |
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| | 01 | M------ | 9:00A-12:00P | TBA | An | Default - none | 24 | 0 | 0 | | |
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| | 01 | TBA | | See Dept / | Han, Barbier | Default - none | 100 | 0 | 0 | | |
| 02 | TBA | | See Dept / | Orahood, Barbier | Default - none | 100 | 0 | 0 | Desc: | **This section is for Global Health Specializers only. |
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| | 01 | TBA | | See Dept / | Han, Barbier | Default - none | 100 | 0 | 0 | | |
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| | 01 | TBA | | See Dept / | Han, Barbier | Default - none | 50 | 0 | 0 | | |
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| | 01 | TBA | | See Dept / | Barbier | Default - none | 10 | 0 | 0 | | |
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| | 01 | TBA | | See Dept / | Stafford, Barbier | Default - none | 100 | 0 | 0 | | |
| 02 | TBA | | See Dept / | Stafford, Barbier | Default - none | 100 | 0 | 0 | | |
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| | 01 | TBA | | See Dept / | Stafford, Barbier | Default - none | 100 | 0 | 0 | | |
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| | 01 | ---R--- | 1:00P-4:00P | TBA | [TBA] | Default - none | 24 | 0 | 0 | | |
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| | 01 | TBA | | TBA | Hobson | Default - none | 100 | 0 | 0 | | |
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| | 01 | M------ | 12:00P-2:00P | Remote / SW | Caburnay | Default - none | 90 | 0 | 0 | Desc: | This section is taught online with a combination of synchronous and asynchronous classes. PLEASE NOTE: 1st class (date TBD) and last class (date TBD) meet 12:15-2pm. A meeting room will be available on campus for students who remain on campus, upon request. Students should bring their laptops to participate in online class from the meeting room. Each week the class format may include a synchronous online lecture, an asynchronous lecture, or a zoom-based student meeting with the coursemaster (students will be assigned to meet with coursemaster at a specific time, TBD between 12-2pm). Course Fee: $250. This is billed to tuition and applied to the CPH exam fee. |
| | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| | 01 | --W---- | 4:15P-5:15P | TBA | Duncan | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| 02 | --W---- | 4:15P-5:15P | TBA | McMurtry | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| 03 | -T----- | 4:15P-5:15P | TBA | McMurtry | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| 04 | TBA | | TBA | [TBA] | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| 05 | TBA | | TBA | [TBA] | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| 06 | TBA | | TBA | [TBA] | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| 07 | TBA | | TBA | [TBA] | Default - none | 14 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| | 01 | M------ | 5:30P-8:30P | TBA | Duncan | Default - none | 16 | 0 | 0 | Desc: | This class will meet 5 times.
Course Dates: 8/26, 9/9, 9/16, 9/23 & 9/30 |
| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M------ | 5:30P-8:30P | TBA | Floros | Default - none | 20 | 0 | 0 | Desc: | Course Dates: 8/26, 9/9, 9/16, 9/23 & 9/30 |
| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | ---R--- | 5:30P-8:30P | TBA | Nelson | Default - none | 20 | 0 | 0 | Desc: | The class will meet every other Thursday for 5 weeks on the following dates: 9/5, 9/19, 10/3, 10/17 & 10/31
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| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 03 | TBA | | TBA | Orahood, Barbier | Default - none | 20 | 0 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | In this five-week skill lab, we will learn about the epidemiology of gun violence in the United States and review the scientific evidence of policies aimed at reducing gun deaths. We will address questions such as: What is the risk of death from a gun in the United States? How does this risk vary by age, gender, race, and ethnicity? And which policies are effective at mitigating these risks? The course will operate as an upper-level graduate seminar (i.e., it will be heavy on readings and required material) and class time will focus on discussion. Additionally, the ICD-10 classification system for firearm deaths will organize course content: accidents, events of undetermined intent, legal intervention (police shootings), intentional self-harm (suicide), and assault (homicide). Students will demonstrate their learning through an article critique at the end of the course. |
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| | 01 | M------ | 1:00P-4:00P | TBA | McMurtry | Default - none | 20 | 0 | 0 | Desc: | Course Dates: 8/26, 9/9, 9/16, 9/23 & 9/30. |
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| Description: | In this five-week skill lab, we will focus on political strategy as it relates to gun laws in the United States, paying special attention to state-level ballot initiatives. We will review the politics of guns in America, the importance of the Second Amendment and recent decisions by the U.S. Supreme Court, the influence of lobbying groups like the National Rifle Association, and political advocacy tactics at the state level. We will also examine case studies to understand these ideas in practice, including Maine's unsuccessful attempt in 2016 to pass a ballot initiative aimed at expanding firearm background checks. The course will operate as an upper-level graduate seminar (i.e., it will be heavy on readings and required material) and class time will focus on discussion. Students will demonstrate their learning by collaboratively designing a ballot initiative campaign to expand or restrict firearm access in a state of their choosing. Prior enrollment in the skill lab, Gun Violence Epidemiology and Policy in the United States, is strongly encouraged, but not required. Familiarity with the basic structure and operation of American government is mandatory. |
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| | 01 | M------ | 1:00P-4:00P | TBA | McMurtry | Default - none | 20 | 0 | 0 | Desc: | Course Dates: 10/14, 10/21, 10/28, 11/4 & 11/11. |
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