Towards understanding Intolerance: An Experimental Approach

Last registered on January 13, 2026

Pre-Trial

Trial Information

General Information

Title
Towards understanding Intolerance: An Experimental Approach
RCT ID
AEARCTR-0013848
Initial registration date
October 28, 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 28, 2024, 1:43 PM EDT

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

Last updated
January 13, 2026, 11:53 PM EST

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

Locations

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Primary Investigator

Affiliation
Indian Institute of Management Bangalore

Other Primary Investigator(s)

PI Affiliation
CNRS, GATE
PI Affiliation
Monash University

Additional Trial Information

Status
In development
Start date
2025-11-01
End date
2026-04-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Intolerance, in its various forms, undermines the fabric of a cohesive society by breeding division and animosity among individuals or groups based on differences in beliefs, identities, or ideologies. In this experiment, we propose to study whether people are willing to pay to block the views of others that they do not concur with. We design an experiment where participants rate a series of vignette-based decisions and decide whether a certain decision is personally appropriate and socially appropriate. These appropriateness measures subsequently allow us to measure whether participants are willing to pay to prevent the spread of a view that they consider personally and socially inappropriate.
External Link(s)

Registration Citation

Citation
BANERJEE, RITWIK, Lata Gangadharan and Marie Claire Villeval. 2026. "Towards understanding Intolerance: An Experimental Approach." AEA RCT Registry. January 13. https://doi.org/10.1257/rct.13848-2.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Our experiment does not have an intervention. There are two experiments. In Experiment 1, we employ a randomized treatment variation that examines whether an individual is presented with conservative or liberal views for the vignettes described below. Experiment 1 was already pre-registered and conducted. The preregistration given below only refers to that of Experiment 2.
In Experiment 2, we use a two by two randomized treatment design. One treatment variation is, as in Experiment 1, about whether an individual is shown conservative views or liberal views for the vignettes; the other treatment variation is about the default number of people who will receive the vignettes if they are spread out.
Intervention Start Date
2025-11-02
Intervention End Date
2026-04-30

Primary Outcomes

Primary Outcomes (end points)
1. Willingness to pay to prevent the spread of a view to either 1 or 100 people.
2. Allocation of points between different reasons for preventing the spread of an incongruent view
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We have three sets of secondary outcome variables.
The first set of secondary outcome variables relate to survey-based measures of intolerance.
-Self-reported levels of intolerance based on survey questions
-Staircase-based method of measuring intolerance
The second outcome is the decision to cooperate or defect in a Prisoner's Dilemma game.
The third set of outcome variables are related to:
- Personal Norms
- Decision to cooperate in a prisoner's dilemma game
- Measure of pro-social behavior
- Other survey-based measures of intolerance
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will describe a series of four vignettes in which a decision-maker makes a decision and we will frame these vignettes in the form of social media posts expressing a view associated with each decision. We will evaluate the personal norms associated with each decision. We will ask the participants if they are willing to block the spread of the view expressed in the post, and how much they are willing to pay to block the spread of this view. Importantly, we will recruit individuals who have a conservative or a liberal view (defined in the PAP). We will investigate the reasons why individuals choose to pay to prevent the spread of a view when the treatment is incongruent with one's orientation (conservative vs. liberal) and to what extent this willingness to pay depends on the default number of posts' recipients. One randomized treatment variation comes from whether an individual is exposed to liberal views or conservative views. The other randomized treatment variation comes from whether the post is, by default, spread to a small (1) or a large (100) number of individuals.
Experimental Design Details
Not available
Randomization Method
Qualtrics-based individual-level randomization
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
NA
Sample size: planned number of observations
We will use a representative sample from the US, excluding participants who already participated in Experiment 1. This sample will consist of 1000 participants recruited through Academic Prolific. We will categorize a participant as Liberal or Conservative, based on their self-reported measure of how they identify themselves on an 11-point liberal-conservative scale. In this sample, we will not include anyone who reports 5 (i.e., they are at the center) on this scale, or anyone who reports they would vote for neither the Republicans nor the Democrats, or anyone who would express an inconsistent ideological position and voting preference (e.g., a liberal who votes for the Republicans). Such participants will not be allowed to proceed after the initial screening questions.
Sample size (or number of clusters) by treatment arms
500 in each treatment variation.
We will pool data from the treatment where the views are being spread to 1 person or 100 people when we compare liberal and conservative treatments.
Likewise, we will pool data from the liberal treatment and the conservative treatment when comparing the outcomes of treatments that spread views to either one person or 100 people.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Monash University Human Ethics Review Board
IRB Approval Date
2024-08-07
IRB Approval Number
41462
Analysis Plan

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