The Social Signal of Jobs
Na'ama Shenhav, Professor
Public Policy
Open. Apprentices needed for the spring semester. Enter your application online beginning January 17th. The deadline to apply is Monday, January 27th, 4 p.m..
Beyond being a source of income, jobs can potentially convey information about a worker’s abilities, personality, or values. For example, individuals may assume that a person who is a teacher is empathetic, or that a lawyer is assertive. In turn, this could imply that a person’s job may affect how she is treated, valued, or respected – even outside of the workplace. Motivated by this idea, this project studies how a person’s job affects one’s social interactions and how they are judged by others. The undergraduate research assistants on this project will help set up a field experiment to test how a person’s job influences the likelihood that they are selected to be a roommate in a shared living situation. In the first stage of the project, we will generate responses to “roommate wanted” advertisements on a classified ads platform and track response rates by renters. In the second stage, we will analyze how the listed occupation in our generated response influences the subsequent response rates by renters.
Students will also have opportunities to engage with the broader research agendas of Professor Na’ama Shenhav and Professor Dmitry Taubinsky. Their work spans topics such as the labor market impacts of public policies, sources of labor market inequality, and the role of behavioral biases in economic decision-making.
Role: The undergraduate research assistant will serve a key role in helping set up the logistical framework for the field experiment. Specifically, we are looking for two RAs who can help create a web scraping program to extract all of the listings from a classified ads website daily, and process the text from the ads. A third RA will help automate the process of sending responses to the scraped listings. This work will provide the RAs hands-on experience with web scraping techniques and automating workflows. They will also learn about experimental design and implementation in social science research.
Qualifications: Required:
-Proficiency in Python or another programming language used for web scraping (e.g., R).
Desirable:
-Experience with web scraping and familiarity with Python libraries such as BeautifulSoup or Scrapy.
-Strong attention to detail and ability to work independently.
Majors in computer science, or data science / social science with strong programming experience preferred.
Day-to-day supervisor for this project: Laila Voss, Graduate Student
Hours: 6-8 hrs
Related website: www.naamashenhav.com
Related website: www.dmitrytaubinsky.com