Research partnership proposal · Prepared for IPA · June 2026

Who bears the cost of gender norms?

Three field studies in Latin America on how gender norms shape women's work — in what people express online, allocate at home, and reveal in digital markets.

Ana María Díaz-Escobar  ·  Pontificia Universidad Javeriana
Marie Boltz  ·  coauthor, all three studies
Study 1Online expression · 8 countries

Do people hide their support for gender equality?

Suppressed Voices: Pluralistic Ignorance about Gender Norms
19M
comments
analyzed
Why it matters

Attitudes on gender are shifting faster in private than in public. When support stays silent, outdated norms survive even after most people have abandoned them — slowing progress on women's work.

How

An online field experiment in real comment sections: we post one visible, gender-equal comment on randomly chosen videos and measure whether others then speak up. (Detail next.)

Where

35 Spanish-language channels across 8 countries — Colombia, Mexico, Argentina, Chile, Peru, Spain and more.

Who

Díaz-Escobar & Boltz. Data pipeline already live; one research assistant runs the experiment.

How much
US$15–20K indicative
One research assistant for ~6 months, plus classifier validation, pre-registration and IRB. Data and pipeline already built. Powered at 80% for a 15-point effect — ~180 videos complete in 6–8 weeks.
Who bears the cost of gender norms?Study 1 — Online expression
Study 1 · The intervention

One seeded comment, varied two ways

Within two hours of a new video, we post one norm-challenging comment, assigned at random. The four treatments cross how they challenge the norm with which norm they target.

Seeded message
Women's paid work
Men's caregiving
Express the view injunctive
T1

"Women working outside the home benefits the whole family."

T3

"Men who share housework and childcare are better fathers and partners."

Reveal the majority social proof
T2

"In Colombian surveys, the majority — over 59% — support women working outside the home."

T4

"Surveys show more men than it seems want to share housework and childcare."

Control & measurement
Control (T0) gets no seeded comment. A two-option like-poll runs on every video — an anonymous read on private opinion.
Primary outcome: does one seeded comment trigger organic norm-challenging comments in the week that follows? The poll ratio separates real belief change from imitation.

Tiered deployment: the expression arms (T1/T3) are withheld from male-centered channels to avoid backlash contaminating the outcome; social-proof arms and polls run everywhere.

Who bears the cost of gender norms?Study 1 — The intervention
Study 2Households · online · nationwide Colombia

When flexibility is scarce, whose job gets it?

Why it matters

Flexible work is reshaping careers, but women take it and pay in wages and promotion. If the driver is a norm of maternal availability rather than preference, flexibility policy needs a different fix — and that distinction is what we identify.

How

Couples face one scarce flexibility package they assign to either partner. We randomize the framing and the scarcity — first with hypothetical offers, then with real packages. (Two interventions next.)

Where

Couples across Colombia, recruited and run online — beyond Bogotá, at scale. Optional firm arm later.

Who

Díaz-Escobar & Boltz, with IPA on implementation and firms for the workplace arm.

How much
Online pilot cost to confirm  ·  real packages = main cost lever
Running online nationwide makes the hypothetical stage cheap per couple and large; delivering real packages is where the budget scales.
Who bears the cost of gender norms?Study 2 — Households & firms
Study 2 · Intervention 1Online pilot · nationwide Colombia

The online pilot — a randomized test of framing

~2,500 couples online, across Colombia
Both partners · stratified by child under 6 · each offered ONE scarce package (2 WFH days · childcare backup · transport · protected school-run time) for either partner
↓   randomly assign the justification (frame)   ↓
Control

Neutral

"Either of you can use it."

T1

Care

"…so a parent can be there for the children."

T2

Productivity

"…so the recipient does better at work."

T3

Income

"…so the household protects its earnings."

What we test

Each partner nominates privately, then the couple decides together. Does the frame push the package toward the wife? Cross-cut by scarcity (one package vs. one each); a subset wins its choice for real.

Who bears the cost of gender norms?Study 2 — Online pilot
Study 2 · Intervention 2Real packages · partner firms

The firm experiment — who can the benefit go to?

Workers (and their partners) at partner firms
Each worker is offered a REAL flexibility benefit (flexible & predictable schedule · WFH days · childcare subsidy · transport)
↓   randomly assign WHO can receive it   ↓
Control

Worker only

The benefit stays with the employee.

T1

Transferable

The worker can pass it to the spouse.

T2

Default to partner

Pre-assigned to one partner unless changed.

T3

+ Spouse session

Worker keeps it, after a joint info session.

What we test

Take-up, who actually uses it, job retention, hours, earnings, childcare time and spousal bargaining — does making flexibility transferable change who bears the cost?

Who bears the cost of gender norms?Study 2 — Firm experiment
Study 3Digital labor markets · AR · BR · CO · MX

Does AI close the gender gap — or reveal it was never about style?

A randomized experiment with Latin American freelancers · with OpenAI
+12
search ranks
lower for women
Why it matters

On freelance platforms, women earn less, rank ~12 places lower, and hold far fewer skill certifications than comparable men (0.4% vs 5.2%) — despite slightly higher ratings. Controlling for writing style does not absorb the gap, so it isn't just women presenting themselves modestly.

How

A three-arm RCT giving freelancers access to a generative-AI writing assistant. If AI closes the gap, the constraint is supply-side self-presentation; if it persists, it is demand-side discrimination on signals AI can't change — photo, name, country. (Detail next.)

Where

~1,200 active Workana freelancers in Argentina, Brazil, Colombia, Mexico — on a live panel of 7,712 profiles across 18 countries.

Who

Díaz-Escobar (PI) & Boltz, in partnership with OpenAI (model access + privacy-safe usage data). Panel already built.

How much
≈ US$10K recruitment + RA indicative  ·  AI access & usage data in-kind from OpenAI
Outcomes come from the existing Workana scraper at zero marginal cost — recruitment ads are the main expense.
Who bears the cost of gender norms?Study 3 — Digital labor markets
Study 3 · The intervention

Three arms: does AI equalize or amplify?

Freelancers are randomly assigned (stratified by gender × country) to one of three arms. The design separates access to AI from structured guidance on how to use it.

T1 Coach

A custom "Freelance Coach" GPT

Pre-loaded prompts for rewriting bios, drafting proposals and portfolios, and translation, with a short onboarding.

T2 Access only

ChatGPT Plus, no guidance

Access without onboarding or curated prompts — isolates the effect of access from structured help.

C Control

No access until endline

The baseline of what freelancers achieve on their own; receives access after the study.

The key test
Does the gender × Coach effect on rank and earnings close the gap, or leave it intact?
Outcomes (rank, ratings, certifications, bio style) come from the existing panel. Heterogeneity by country-level gender norms: if AI helps most where norms are most conservative, the supply-side reading is corroborated.
Who bears the cost of gender norms?Study 3 — The intervention
One agenda · three studies

Where IPA comes in.

Study 1 · Online
US$15–20K

Fund one RA for ~6 months to run the seeded-comment experiment on data already built.

Study 2 · Households
Online pilot

Fund the online couples pilot (conjoint + real-package lottery), then scale to real packages nationwide.

Study 3 · Freelancers
With OpenAI

AI access in-kind from OpenAI; IPA could support Latin American recruitment (~US$10K ads).

Ana María Díaz-Escobar  ·  a.diaze@javeriana.edu.co
Marie Boltz  ·  coauthor, all three studies
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