Gender Competition and Norms around Women’s Work

Last registered on November 18, 2024

Pre-Trial

Trial Information

General Information

Title
Gender Competition and Norms around Women’s Work
RCT ID
AEARCTR-0014557
Initial registration date
October 10, 2024

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
October 18, 2024, 4:49 PM EDT

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

Last updated
November 18, 2024, 3:17 PM EST

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

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Primary Investigator

Affiliation
Paris School of Economics

Other Primary Investigator(s)

PI Affiliation
Ohio State University
PI Affiliation
Yale University
PI Affiliation
University of Southern California

Additional Trial Information

Status
On going
Start date
2024-09-27
End date
2025-06-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Our study is designed to understand whether men strategically enforce restrictive norms in response to gendered intra-household competition for work. We aim to distinguish between several hypotheses for how reserving jobs for specific gender (compared to letting men and women compete for job opportunities) affect gender norms and attitudes. Our study offers mobile app-based gig work, addressing many issues that typically hinder women from working—e.g., concerns about privacy and mobility—but are also attractive to men due to high remuneration. We cross-randomize gender reservations for jobs (male, female, or open to both genders) and high and low-wage opportunities across community clusters.

We will evaluate how gender norms are expressed when men have to compete with women from their own households for the jobs, and whether there is an interaction between the gender reservation and wage treatments. We will also measure any changes in norms surrounding women’s work after the gig jobs are completed and -- in a separate experiment with workers recruited during the first experiment -- whether embedded gender messaging in work tasks affects gender attitudes and worker productivity. We examine whether these effects vary by gender.
External Link(s)

Registration Citation

Citation
Oh, Suanna et al. 2024. "Gender Competition and Norms around Women’s Work." AEA RCT Registry. November 18. https://doi.org/10.1257/rct.14557-2.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-09-27
Intervention End Date
2025-06-30

Primary Outcomes

Primary Outcomes (end points)
The main outcome variable is gender norm indices related to the following themes:
Norms and attitudes related to women’s work,
Reported consequences of violating work-related norms,
Norms and attitudes related to women’s phone use,
Reported consequences of violating phone-related norms,
Norms related to digital work for women,
Reported suitability of digital work for women.

Subsets of questions that are part of the above indices also relate to the following sub-themes:
- Breadwinner norms
- Domesticity norms
- Purity norms
- Second-order beliefs about community attitudes

We also collect the following outcomes during/after the gig jobs are completed:
- Interest in information about women’s work
- Preference over job reservation policy for future work
- Gender attitudes
- Women’s bargaining power and welfare
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
For those who are not in the control group, we also examine job-related outcomes, including attendance at the job information session, job sign-up and productivity (here, differences across treatment arms will include selection effects).

Within the gender messaging experiment, we will study treatment effects on worker productivity and reported norms (including the outcomes listed under primary outcomes and several self-administered questions delivered via the app) for app-based workers across treatment arms.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
[ Work task ]

We are working with Karya—a digital work platform committed to ethical AI practices. Unlike many lower-paying , exploitative jobs in the sector, Karya offers attractive wages (starting at $5 per hour, 20 times the Indian minimum wage,) with the potential to earn up to $1,500 per person. Karya gig workers use smartphones to perform simple microtasks, the outputs of which are often used to build training datasets for AI and machine learning algorithms.

Our study tasks are accessible to workers with only basic smartphone literacy and educational attainment: they require workers to read and record simple sentences displayed on the app, earning piece-rate wages for accurate recordings. These tasks are conducted in local languages (Hindi) and the app itself is in Hindi, to ensure it is accessible to lower-education populations. Before the job, workers are given in-depth training on setup, job execution, payment, and troubleshooting.

[ Sample and Recruitment ]

Our proposed work is in Bihar, one of the lowest-income states in India, with a female labor force participation (FLFP) rate of around 10% (Periodic Labour Force Survey, 2023). We conduct our study across 175 Gram Panchayats (GP) in Bihar. The study population are low-income married women and male decision makers from the same households. To identify eligible households, we will first conduct a mapping exercise of the sample communities using a random walk method. Based on the mapping exercise, we will identify eligible households and enroll a random subset (up to 20 households) from each community.

Eligible households must have a married female and male decision maker in the household that meet the following eligibility criteria:
- Access to a smartphone and a bank account,
- Can perform basic functions on smartphones
- Able to read in Hindi
- Be of prime working age (18-60)
- Available in the community during the study period.
- In addition, the eligible female participant should not have a regular paid job.

[ Randomization ]

Prior to beginning fieldwork, we will randomize sample communities into one of the following conditions:
- Control: No jobs offered
- Treatment 1: Female Reservation—one job offer is made to the selected female respondent in the household
- Treatment 2: Male Reservation—one job offer is made to the selected male respondent in the household
- Treatment 3: Open—one job offer is made to the household, and either the selected male or female respondent can take the job

Communities in the three treatment arms will be cross-randomized into either a high or low wage condition (thus creating 7 experimental cells in total). In all treatment communities, enrolled households will be offered 4-week-long digital jobs using the Karya mobile app; the work is part time, and should take up to 1-2 hours if workers complete all assigned tasks. While one woman and one man are surveyed from each household, only one member of the household will be allowed to sign up for the job. In communities assigned to the high wage condition, experimental job offers will have daily pay slightly above the market unskilled daily wage for men; in low wage communities, job offers will have daily pay below the market daily wage for unskilled female labor.

[ Study Procedures ]

Once households are enrolled into the study, we will conduct three surveys. In the first survey (baseline), we ask men and women to answer questions related to the following topics: basic demographics, baseline attitudes towards women’s work and phone use, household income and expenditures, female decision-making power, and women’s work status.

At the end of the baseline survey, the respondents in the treatment groups are presented with the information about the Karya job and told they will have the opportunity to sign up for the job when we return and conduct a follow-up survey with the respondent approximately five days later. We elicit initial interest in the job and predictions about household take-up decisions. After baselines are completed in the community, we hold a job information session at a central location in the village to provide more detailed information about the job.

The second survey (pre-work endline) is conducted after the job information session. During the pre-work endline survey, the participants in the treatment groups are first asked to indicate the household’s final decision about the job sign-up. Following this, the survey asks a battery of norms questions and questions about suitability of Karya work for women.

The pre-work endline survey is followed by a community-level job-offer lottery and an onboarding procedure: If fewer than 10 households sign up for the job in a given community, all of them are onboarded to the job. If more than 10 sign up, we will conduct a lottery to select 10 to onboard.

The final (post-work endline) survey will be conducted over the phone with all study participants to capture additional changes in attitudes after actual work is completed (note that these outcomes confound treatment effects of job reservation with access to work, and therefore have a different interpretation; we may exploit the job offer lottery to assist in unbundling these effects). Here we will also measure attitudes using two real-stakes situations. First, respondents can vote to influence the future reservation policy in their community; (we will implement future work and the chosen reservation policy in a randomly chosen community). Respondents are allowed to cast a vote for their preferred reservation policy—open, reserved for men only or reserved for female only—or receive a small compensation instead of voting. The second measure involves taking a costly action (i.e., filling out a digital form) to access information related to women’s work opportunities. We also ask questions about household spending, decision-making, and mental health.

[ Main Hypotheses ]

The main outcomes of interest include personal views surrounding women’s work and smartphone use, as well as beliefs about the suitability of Karya work for women (collected at the pre-work endline). Questions are designed to capture three prominent norms dissuading female work: work as a threat to women’s purity, work interfering with women’s household responsibilities (domesticity), and the norm that the man should be the breadwinner. Some questions are designed to capture second-order beliefs about the community norms for these same dimensions.

We test the hypothesis that men will express more conservative norms under the open treatment, especially in the high wage arm (we discuss alternative hypotheses for how gender reservations could affect norms in our PAP). If this is due to the desire to reserve jobs for men, we would expect the effects to be larger if men lack access to other good job opportunities. We also explore whether the effects may differ depending on how constrained women are in terms of bargaining power and access to work at baseline. More details on these dimensions of heterogeneity are provided in the PAP.

[ Supplementary Experiment ]

As an add-on intervention with the Karya workers, we include some stories in the sentences that the workers have to read as part of their work. A random set of workers see treatment stories that are related to female empowerment, e.g., a female protagonist who is able to work and contribute to her household. Another set sees placebo stories, which are the same stories with a male protagonist. The remaining workers belong to the pure control group which only sees disjoint sentences. This allows us to assess whether reading the treatment stories also affects the post-job survey outcomes. A set of questions checking for story comprehension and measuring gender attitudes will be directly administered through the app.
Experimental Design Details
Not available
Randomization Method
We randomize GPs into different treatments using computer randomization.
Randomization Unit
GP-level randomization
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
175 clusters
Sample size: planned number of observations
7,000 individuals (= 3,500 households * 2 respondents per household) with baseline, pre-work endline, and post-work endline surveys
Sample size (or number of clusters) by treatment arms
25 clusters per treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We use the formula for clustered designs in Glennerster and Takavarasha (2014), assuming power of 80% and size of 5%, 20 observations per cluster and 25 clusters per arm (hence, these calculations are relevant for comparison of one gender reservation wage-level cell to another, or to the control group). We calculate the minimum detectable effect in standard deviation units (SMDEs) for different assumed intra-cluster correlations (ICCs). According to our pilot data, the intra-cluster correlation for our norm measures are quite low, around 0.02-0.04. We have also observed small ICCs (almost always less than 0.05) for gender attitude and norms questions in other data we have collected in similar settings. Per our calculations, the SMDE for cell-to-cell comparisons ranges from 0.18-0.25 as the ICC ranges from 0-0.05 (here a cell refers to one of our 7 equally-sized treatment conditions). For concreteness, if we assume that at baseline half of individuals agree Karya work is appropriate to women, these SMDEs would translate to 80 percent power to detect a change of 9-13 percentage points across any pairwise treatment comparison. We are better powered to detect differences across the three reservation treatments; here SMDEs range from 0.13-0.17 as the ICC ranges from 0-0.05.
IRB

Institutional Review Boards (IRBs)

IRB Name
Yale Human Research Protection Program
IRB Approval Date
2024-08-16
IRB Approval Number
2000034039
Analysis Plan

Analysis Plan Documents