ASC Annual Meeting Workshops
ASC Sponsored Pre-Meeting Workshops
Equipment: No laptops provided. Power strips will be available for all ASC Sponsored workshops.
Enrollment: Limited to 50 participants for all ASC Sponsored workshops.
Fee: $75.00 ($30.00 for students); Payment must be made/processed to be officially registered.
Registration:
- Register for workshops online via the Annual Meeting Registration Form
- To register for a workshop only, use the Printer-Friendly Workshop Form (PDF) or the Printer-Friendly Workshop Form (Word)
Refund Policy: Advance registration fees will be refunded for cancellations received up to October 31st. No refunds will be made on cancellations received after this date.
*** Please note registration for a workshop is NOT registration for the ASC Annual Meeting ***
Title: Running the Gauntlet: Succeeding as a Qualitative Scholar in a Field Built upon Quantitative Standards
Instructor: : Jamie J. Fader, Temple University and Danielle Rudes, Sam Houston State University
Date & Time: Tuesday, November 12th | Time 12-4 P.M.
Place: Salon 11, Lower B2 Level
This workshop is targeted primarily for early career scholars and will contain practical/ strategic and methodological strategies for navigating a quant-dominated field. Subtopics might include: how to respond to (or write to prevent) common reviewer critiques, how to build a research and funding pipeline that includes qualitative research, and how to be an advocate for your research in a field that often devalues qualitative work. More senior scholars are also encouraged to attend and share your own strategies for succeeding while using qualitative methods and to strategize for advocacy efforts that may help bridge the quant-qual divide in our field.
Title: Synthetic Control Time Series Experiments: The Case-Study Approach to Causal Inference
Instructor: Bradley J. Bartos, University of Arizona
Date & Time: Tuesday, November 12th | Time 1-5 P.M.
Place: Salon 10, Lower B2 Level
The Synthetic Control Method is an increasingly popular approach to quasi-experimental causal inference and policy evaluation. The method involves the construction of a control time series which optimally mimics the characteristics of the treated series up to the point of the intervention as a weighted combination of less-than-ideal, but uncontaminated “donor pool” units. Because the synthetic control is constructed from a set of uncontaminated controls, the post intervention synthetic series is intended to approximate the treated series “had the intervention never occurred”. After briefly situating the method within causal inference and quasi-experimental literatures, the workshop will walk participants through real-world applications of the method, including replications of peer-reviewed synthetic control studies. The replications and illustrations will familiarize participants with the process and implementation of the synthetic control routine, from data cleaning and setup through postestimation procedures. Examples will also highlight common pitfalls and researcher checks that are essential to valid inference. The examples presented in this workshop are derived from a book project on synthetic control designs currently out for review. All necessary data, .ado, and .do files will be provided by the instructor prior to the workshop. Participants will need to bring laptops with stata installed to follow along with the examples presented.
Title: Using Topic Models to Qualitatively Code Large Amounts of Text
Instructor: Danielle Wallace, Arizona State University and Connor Stewart, Arizona State University
Date & Time: Tuesday, November 12th | Time 12-4 P.M.
Place: Salon 12, Lower B2 Level
Given advances in computing and storage, qualitative researchers are now having to grapple with massive amounts of text data, which may be too difficult or invite too many errors to code by hand. In these circumstances, the data science technique of topic modeling may be useful. Topic modeling is machine learning technique that aids in qualitative coding of different forms of text documents by examining the documents for patterns in words or phrases, then clustering those words and phrases into “topics” or “themes.” Two types of topic models are most commonly used in criminology: structured topic modeling and biterm topic modeling. This workshop will expose attendees to the basics of topic modeling and give attendees hands on practice with real text data available on ICSPR. During the first part of the workshop, attendees will receive an overview of topic modeling generally, with a focus on structured topic modeling and biterm topic modeling. Then using RStudio, during the second part of the workshop, attendees will be directly working with two sets of text data to thematically code the data using both structured topic and biterm topic models. To participate in the hands-on activities, attendees should have some exposure to and knowledge of RStudio and the most recent version of RStudio on their computer to use in the workshop. All code and data will be provided.
This workshop includes an additional supply fee of $20.
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