Gender Stereotypes and Peers' Recognition

Last registered on October 18, 2023

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Pre-Trial

Trial Information

General Information

Title

Gender Stereotypes and Peers' Recognition

RCT ID

AEARCTR-0008491

Initial registration date

November 08, 2021

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

November 09, 2021, 11:00 AM EST

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

Last updated

October 18, 2023, 10:45 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

Peru

Region

Primary Investigator

Name

Maria Pia Basurto

Affiliation

Universidad del Pacifico

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Other Primary Investigator(s)

PI Name

Manuel Barrón

PI Affiliation

Universidad del Pacífico

Contact Investigator

PI Name

Juan Francisco Castro

PI Affiliation

Universidad del Pacífico

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PI Name

Roman Andres Zarate

PI Affiliation

University of Toronto

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Additional Trial Information

Status

On going

Start date

2021-10-25

End date

2023-12-31

Keywords

Education, Gender

Additional Keywords

STEM, post secondary education, role models, stereotypes

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

We explore the effect of providing students with information on female role models and gender stereotypes on STEM careers on peers' recognition. We use a two-phase randomization design with different degrees of saturation at the classroom level: 20%, 50%, and 80%. We randomly assign students (grades 9-11) from 20 schools in Lima, Peru, to receive two treatments before nominating peers to represent their classroom in a knowledge contest: (i) watching videos about successful women in STEM careers and (ii) receiving feedback on an Implicit Association Test (IAT) about gender and career choices. Classrooms compete in a contest with STEM-related and non-STEM-related questions. Students nominate three peers to represent their classroom in the inter-classroom competition. We will test the effect of reducing gender stereotypes on peer nominations in STEM-related and non-STEM-related subjects. We will also study efficiency gains measured by the performance of students with more nominations in the competition.

External Link(s)

Registration Citation

Citation

Barrón, Manuel et al. 2023. "Gender Stereotypes and Peers' Recognition." AEA RCT Registry. October 18. https://doi.org/10.1257/rct.8491-1.1

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Experimental Details

Interventions

Intervention(s)

Students (grades 9-11) are randomly assigned to 2 groups: a control group, and a treatment group, with different degrees of saturation at the classroom level: 20%, 50%, and 80%.

The treatment group is exposed to the combination of two treatments:
1. Students receive feedback on a previously carried out Implicit Association Test (IAT), which reveals information on their degree of gender bias (high, medium, low, or no degree of bias) in choosing career paths.
2. Students watch videos about successful women in STEM careers.

Intervention Start Date

2021-11-03

Intervention End Date

2021-11-15

Primary Outcomes

Primary Outcomes (end points)

The primary outcomes are:

1. Peer nominations to the student contest. We will consider two types of nominations: STEM-related and non-STEM-related subjects. We will estimate treatment effects at the dyad level.
2. Self-nominations: we will test whether girls in the treatment group are more likely to nominate themselves for the contest.
3. Performance on the contest: we will estimate treatment effects on the performance of the students that receive more peer nominations for the inter-classroom competition.
4. We will also estimate treatment effects on individual performance in the contest. We will run these regressions at the question level.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will also estimate treatment effects on stereotypes by using videos about a (randomly assigned) female/male engineer.

We will test for heterogeneous effects by gender on general and self-nominations.

Secondary Outcomes (explanation)

Experimental Design

This is a two-stage randomization process:

1. Classrooms are randomly assigned to a saturation level: 20%, 50%, 80%.
2. Within each classroom, students are randomly assigned to receive the treatment.

Experimental Design Details

All students fill a survey with information on their career choices, education level, and socioeconomic indicators at baseline. They also receive videos about a (randomly assigned) female/male engineer and answer questions about gender stereotypes and a general understanding of the videos. Further, they carry out an Implicit Association Test (IAT), which approximates their degree of gender bias in choosing a career path, namely, an implicit association between women and arts and humanities careers and between men and STEM careers. Students in the treatment group receive feedback on their IATs and videos about successful women in STEM careers.

A week later, students participate in a knowledge contest on two subjects: Arts and Humanities, and STEM. Students must nominate three participants to form the team that will represent their classroom in this competition. All the students answer the contest's questions, and the classroom score is the performance of the three students with more nominations. The classroom with the highest score wins a prize.

Randomization Method

Randomization done by a computer.

Randomization Unit

Student level with saturation at the classroom level (20%, 50%, 80%)

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

130 classrooms

Sample size: planned number of observations

5000 students

Sample size (or number of clusters) by treatment arms

5000 students

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

We perform power calculations on the likelihood of nominations. We will estimate the treatment effect on the likelihood that student i nominates student j for STEM-related subjects and non-STEM-related subjects. Our parameter of interest is the interaction of the treatment with the gender of student j. We assume 2,200 students in the treatment group and 2,200 students in the control group. The estimation is carried at the dyad level, and the average classroom size is 30. The unit of the cluster is the student. Assuming that students nominate 10 percent of their peers on average, we can identify an effect of 1.9 percentage points on the likelihood that student i nominates student j.

Supporting Documents and Materials

IRB