Rachael Garrett: Catalogue data in Autumn Semester 2022
|Name||Dr. Rachael Garrett|
|Department||Humanities, Social and Political Sciences|
|Relationship||Assistant Professor (Tenure Track)|
|701-0658-00L||Seminar for Bachelor Students: Human Environment Systems||3 credits||2S||J. W. McCaughey, A. Berthold, D. N. Bresch, R. Garrett|
|Abstract||Analysis and presentation of research papers from the involved chairs, relating to topics from human-environment systems.|
|Objective||The students learn to read, understand, summarize and present current research papers related to human-environment systems. Furthermore, students train the critical discussion of these papers. The students alse get to know a number of innovative approaches for such presentations.|
|Content||Research in human-environment systems is characterised by a broad range of topics and methods. This is illustrated by the research papers that are discussed in this seminar. Students choose a paper from a list and present it to the seminar participants. Furthermore, they lead the discussion and train questions and answers related to such presentations. In the first three lessons, inputs to presentation techniques and innovative approaches to presentations are provided and discussed.|
|Lecture notes||Will be provided in the seminar.|
|Literature||Will be provided in the seminar.|
|Prerequisites / Notice||none|
|860-0100-00L||Doctoral Colloquium in Public Policy|
Only PhD students. Permission from lecturers is required.
|1 credit||1K||M. Krauser, T. Bernauer, R. Garrett, T. Schmidt, B. Steffen|
|Abstract||In this colloquium, doctoral students present their research plan within the first year of their doctorate, which is reviewed by three professors affiliated with the ISTP and commented on by the peer students registered in the colloquium. We recommend attending the colloquium for two semesters and present the research plan in the second semester.|
|Objective||Obtain feedback on research ideas the doctoral research plan and have the research plan approved by three faculty, as required by ETH Zurich.|
|Content||Doctoral students (typically affiliated with the ISTP or groups of ISTP members) attend this colloquium for one to two semesters. During the first (voluntary) semester they present their preliminary research ideas. During the second (obligatory) semester, they present their research plan, which is reviewed by three professors affiliated with the ISTP. The research plan should not be longer than 20 pages (references excluded). The second semester will be credited with 1 ECTS. All students are supposed to read and comment on their peers’ research ideas and plans throughout both semesters. The results of the review are submitted to the doctoral committee of D-GESS or other ETH departments where ISTP-affiliated doctoral students intend to graduate.|
|876-0201-00L||Technology and Policy Analysis||8 credits||5G||T. Schmidt, E. Ash, F. M. Egli, R. Garrett, M. Leese, A. Rom, B. Steffen|
|Abstract||Technologies substantially affect the way we live and how our societies function. Technological change, i.e. the innovation and diffusion of new technologies, is a fundamental driver of economic growth but can also have detrimental side effects. This module introduces methods to assess technology-related policy alternatives and to analyse how policies affect technological changes and society.|
Participants understand (1) what ex ante and ex post policy impact analysis is, (2) in what forms and with what methods they can be undertaken, (3) why they are important for evidence-based policy-making.
Analysis of Policy and Technology Options:
Participants understand (1) how to perform policy analyses related to technology; (2) a policy problem and the rationale for policy intervention; (3) how to select appropriate impact categories and methods to address a policy problem through policy analysis; (4) how to assess policy alternatives, using various ex ante policy analysis methods; (5) and how to communicate the results of the analysis.
Evaluation of Policy Outcomes:
Participants understand (1) when and why policy outcomes can be evaluated based on observational or experimental methods, (2) basic methods for evaluating policy outcomes (e.g. causal inference methods and field experiments), (3) how to apply concepts and methods of policy outcome evaluation to specific cases of interest.
Big Data Approaches to Policy Analysis:
Participants understand (1) why "big data" techniques for making policy-relevant assessments and predictions are useful, and under what conditions, (2) key techniques in this area, such as procuring big datasets; pre-processing and dimension reduction of massive datasets for tractable computation; machine learning for predicting outcomes; interpreting machine learning model predictions to understand what is going on inside the black box; data visualization including interactive web apps.
|Literature||Course materials can be found on Moodle.|