IPS 270: The Geopolitics of Energy
The global energy landscape is undergoing seismic shifts with game-changing economic, political and environmental ramifications. Technological breakthroughs are expanding the realms of production, reshuffling the competition among different sources of energy and altering the relative balance of power between energy exporters and importers. The US shale oil and gas bonanza is replacing worries about foreign oil dependence with an exuberance about the domestic resurgence of energy-intensive sectors. China¿s roaring appetite for energy imports propels its national oil companies to global prominence. Middle Eastern nations that used to reap power from oil wealth are bracing for a struggle for political relevance. Many African energy exporters are adopting promising strategies to break with a history dominated by the ¿resource curse¿.nThis course provides students with the knowledge, skill set and professional network to analyze how the present and past upheavals in oil and gas markets affect energy exporters and importers, their policymaking, and their relative power. Students will gain a truly global perspective thanks to a series of exciting international guest speakers and the opportunity to have an impact by working on a burning issue for a real world client.
Terms: Win
| Units: 3-5
Instructors:
Jojarth, C. (PI)
IPS 271A: U.S. Human Rights NGOs and International Human Rights (ETHICSOC 15R, MED 225, POLISCI 203)
(Same as
LAW 782) Many US human rights non-government organizations, including the US philanthropic sector, work on international human rights. The US government also engages with the private sector in "partnerships" that twins US foreign aid human rights action with corporate expertise. This weekly series will feature speakers who lead these human rights NGOs, philanthropic enterprises, and corporate partnerships, and also policy experts and scholars, to explore the pro's and con's of this scenario.
Instructors:
Stacy, H. (PI)
IPS 290: Practical Approaches to Global Health Research (HRP 237, MED 226)
Enrollment limited to graduate students; undergraduates in their junior or senior year may enroll with consent of instructor only. Introduces research methods for conducting studies involving health in low-income context. Focuses on developing a concept note to support a funding proposal. addressing research question of student's interest. Skills developed include developing a compelling research question; synthesizing a focused literature review; selecting and adapting appropriate study design, target population, sampling methods, data collection and analysis; addressing human subject issues; developing productive cross-collaboration.
Terms: Win
| Units: 3
Instructors:
Luby, S. (PI)
IPS 299: Directed Reading
IPS students only. May be repeated for credit.
Terms: Aut, Win, Spr, Sum
| Units: 1-5
| Repeatable
for credit
Instructors:
Abel, A. (PI)
;
Armacost, M. (PI)
;
Arnold, S. (PI)
;
Aturupane, C. (PI)
;
Blacker, C. (PI)
;
Brest, P. (PI)
;
Bundorf, M. (PI)
;
Crenshaw, M. (PI)
;
Diamond, L. (PI)
;
Fukuyama, F. (PI)
;
Goldman, S. (PI)
;
Gould, E. (PI)
;
Greif, A. (PI)
;
Hilton, S. (PI)
;
Holberton, R. (PI)
;
Holloway, D. (PI)
;
Jojarth, C. (PI)
;
Jolluck, K. (PI)
;
Kieschnick, M. (PI)
;
Kumar, A. (PI)
;
Magaloni-Kerpel, B. (PI)
;
Meyersson Milgrom, E. (PI)
;
Milani, A. (PI)
;
Morris, E. (PI)
;
Orr, R. (PI)
;
Ross, L. (PI)
;
Sagan, S. (PI)
;
Shin, G. (PI)
;
Sorcar, P. (PI)
;
Stedman, S. (PI)
;
Stoner, K. (PI)
;
Straub, W. (PI)
;
Thurber, M. (PI)
;
Van Schaack, B. (PI)
;
Weiner, A. (PI)
IPS 802: TGR Dissertation
| Repeatable
for credit
IPS 206: Applied Statistics for Policy
Introduction to the use of statistical models, as relevant for decision making and data interpretation in policy contexts. Emphasis on regression analysis, as the most frequently used tool in quantitative policy analysis. The purpose of the course is to enable students to become intelligent consumers of regression analysis. Applied experience in both consuming and producing regression analyses, as well as knowledge of the underlying statistical theory.
Instructors:
Gulotty, R. (PI)
;
Bullock, J. (TA)
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