Gathering Information about careers: the role of gender

Last registered on February 18, 2020


Trial Information

General Information

Gathering Information about careers: the role of gender
Initial registration date
February 16, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
February 18, 2020, 2:15 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.


Primary Investigator

University of Chicago

Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Recent evidence suggests that occupations and firms are key determinants of earnings differentials among men and women (Blau and Kahn, 2017; Card, Cardoso, and Kline, 2016). Research is scant, however, on what drives gender differences in these labor market outcomes. In this project, we investigate why men and women sort into different occupations, firms, and jobs, by studying whether the access to and provision of information regarding career paths differs systematically by gender.

How and from whom do new labor market entrants seek advice regarding their career path decisions? Do the mentor-mentee relationships formed exacerbate or attenuate gender differences in information and expectations about potential jobs? We seek to study the supply of and demand for advice regarding career choices among college students. Specifically, we will explore whether advice seekers’ demographic characteristics alter their access to and the informational content of advice received.
External Link(s)

Registration Citation

Gallen, Yana and Melanie Wasserman. 2020. "Gathering Information about careers: the role of gender." AEA RCT Registry. February 18.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
We will analyze gender differences in rates of response, length of response, content of response, offers of help, and whether the professional validates or mitigates concerns. To construct these outcomes, we will ask the students their perceptions, use third-party evaluators, and use natural language processing tools such as sentiment analysis.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Professionals will be randomly assigned to receive a message from a male or a female student. Each professional-student communication will use one of four message templates. Each professional will receive at most one message. Each student participant will be invited to an in-person session during which they will be instructed on how to set-up a profile on the professional platform, asked to rank professionals, and asked to send pre-formulated messages to their list of 100 professionals. Students will also be instructed on how to submit information concerning professional replies to the research team. One month after students have attended the in-person session, they will fill out an endline survey in which they detail their subsequent interactions with professionals and describe their attitudes concerning various career path choices.
Experimental Design Details
Randomization Method
The randomization of students to professionals is done using STATA's random number generator.
Randomization Unit
The level of randomization is the professional
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
10,000 professionals
Sample size: planned number of observations
10,000 professionals
Sample size (or number of clusters) by treatment arms
5,000 professionals per student gender.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We expect to send 10,000 messages, half from female and half from male students. Our main outcomes of interest are (1) response rates and (2) the quality and content of responses. We expect response rates of 0.15, which is in between response rates in studies of cold emails to politicians (Kalla et al. (2018)) and cold emails to venture capitalists (Gornall and Strebulaev (2018)). Based on informal testing of the first message to 96 graduate students with industry experience, we observe the mean/sd number of words per message of 93/71 and the rate of discussing work/life concerns of 0.13. With 80 percent power and 5 percent statistical significance, the minimum detectable gender differences are 2 percentage points in response rates, 10.28 words per message, and .048 in the rate of discussing work/life concerns.

Institutional Review Boards (IRBs)

IRB Name
University of Chicago IRB
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

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Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials