The Bystander Issue: Why Do We Take The Harassers’ Side?

Last registered on October 04, 2023

Pre-Trial

Trial Information

General Information

Title
The Bystander Issue: Why Do We Take The Harassers’ Side?
RCT ID
AEARCTR-0012128
Initial registration date
October 02, 2023

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 04, 2023, 5:04 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
London School of Economics

Other Primary Investigator(s)

PI Affiliation
University of Barcelona
PI Affiliation
London School of Economics
PI Affiliation
Bocconi University

Additional Trial Information

Status
In development
Start date
2023-10-03
End date
2023-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The issue of sexual harassment in the workplace has been gaining importance in the public debate, especially in recent years and since the #MeToo movement in 2017. Studies have shown that women are willing to give up a significant portion of their salaries to avoid harassment, leading to occupational segregation and macro-level negative consequences. The availability of data and successful experiments have allowed researchers to establish a consensus on the detrimental effects of sexual harassment, primarily focusing on the dynamics between the victim and perpetrator, as well as its broader implications within organizations and society. However, there is a scarcity of evidence regarding the impact of those in the surrounding environment (for instance colleagues), despite anecdotal evidence highlighting an important role in preventing harassment, helping the victim and providing testimony in legal cases. Bystanders have the potential to influence both victims and perpetrators, but they can remain silent, fostering long-term toxic environment where victim will not report, and harassers continue to abuse individuals. In this study, we study the belief of bystanders about sexual harassment, and how these beliefs determine bystanders' choices to provide assistance.
External Link(s)

Registration Citation

Citation
Coly, Caroline et al. 2023. "The Bystander Issue: Why Do We Take The Harassers’ Side?." AEA RCT Registry. October 04. https://doi.org/10.1257/rct.12128-1.0
Experimental Details

Interventions

Intervention(s)
We employ a survey experiment to understand beliefs about sexual harassment and manipulate respondents’ information sets using several treatments regarding harassment in the workplace.
Intervention (Hidden)
We employ a survey experiment to understand beliefs about sexual harassment and manipulate respondents’ information sets using several treatments. These treatments include providing information on the prevalence of sexual harassment, the impacts on victims and alleged perpetrators, and recommended practices for effective bystander intervention.

To provide the necessary information for the treatments, we utilize existing survey data and legal definitions to define what constitutes a sexual harassment case and determine the percentage of female victims among the working population in France, which is presented to the first treatment group. Additionally, we utilize data provided by Ifop to present statistics on cases where victims experienced more adverse consequences than the perpetrator and vice-versa to the second treatment group. Finally, we provide information on the appropriate practices against sexual harassment to the third treatment group.
Intervention Start Date
2023-10-03
Intervention End Date
2023-12-31

Primary Outcomes

Primary Outcomes (end points)
The key outcomes are the willingness to help a victim in sexual harassment cases, and being supportive of the cause against sexual harassment. We will also ask respondents their opinions about sexual harassment as an issue.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
In addition to the main outcomes, we collect initial beliefs around sexual harassment issues. Next, the survey collects secondary data on respondents' individual characteristics, such as age, education, relationship status, and gender, as well as work-related information, including employment type and the nature of their workplace, and personality traits (risk taking behaviours and empathy). These initial variables will enable us to run heterogeneity analyses based on the workers’ characteristics. The survey will also gather data on gender norms, and participants' experiences of sexual harassment and workplace discrimination, which will allow us to look at further heterogeneity along these lines.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Initially, respondents answer questions about their individual characteristics, such as age, education, household composition, gender, employment type, and the nature of their workplace. This "baseline" part of the survey also includes questions about gender norms from the World Value Survey and experiences of harassment and workplace discrimination. Next, respondents are presented with three sets of questions that capture their "prior beliefs" regarding sexual harassment issues. Afterward, respondents are randomly assigned to three treatment groups and two control groups (an active and a passive control group). Finally, all respondents will be asked the same set of questions following randomization regarding willingness to help the victim.
Experimental Design Details
Descriptive Analysis

In our study, we use our survey to collect unique data on bystanders' beliefs and support the effect of information treatments on various outcomes related to individuals' willingness to help victims of sexual harassment. The descriptive methodology involves a simple OLS regression, where the outcome variable for individual i (Yi) is regressed on the various beliefs about sexual harassment prevalence, costs and good practices, using only the control group. Beliefs will be assessed by presenting three sets of questions to the respondent regarding sexual harassment in the workplace. Firstly, they will be shown a definition of sexual harassment and will be asked estimate its prevalence in the workplace: variable “Percentage of Victims”, coded from 1 to 100. We will also construct a variable the deviation from the true share, from -30 to 70 (true share being approx. 30%). Secondly, they will quantify who suffers the most in harassment cases, whether it is the victim or the perpetrator, by indicating the percentage of cases where each party experiences the most significant consequences: variables “Costs”, coded similarly from 1 to 100, and the deviation as well. Finally, respondents will be asked to assess their knowledge about good practices in cases of sexual harassment. This will take the form of a test on the dos and don’ts when faced to a sexual harassment case: variable “Test Score” coded from 1 to 6.

Yi = B1*Percentage of Victims1i + B2* Costs 2i + B3*Test Score3i + µs (1)

The beliefs variables will allow first to draw descriptive conclusion about the type of beliefs that are important to foster to create a supporting environment for victims.

Causal Analysis

In our study, we use a Randomized Control Trial (RCT) to estimate the effect of information treatments on various outcomes related to individuals' willingness to help victims of sexual harassment. The empirical methodology involves a simple OLS regression, where the outcome variable for individual i (Yi) is regressed on the treatment dummies (Treatment1i, Treatment2i, Treatment3i) and other control variables (Xi), with the omission of the control groups as the reference group.

Yi = B1*𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡1 i + B2*𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡2 i + B3*𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡3 i + µs (1)

The treatment dummies (Treatment1i, Treatment2i, Treatment3i) take a value of 1 if the respondent receives a specific information treatment and 0 otherwise. Treatment 1 is giving the right information about the prevalence of sexual harassment will change their perception of the pervasiveness of sexual harassment, influencing individuals' willingness to help victims of sexual harassment.

With Treatment 2, we can challenge the belief that the cost ration between victims and perpetrator favour the victims with quantitative information about the percent of victim who felt that they suffered more consequences will affect individual behaviour when faced with a situation of harassment. Finally, providing a set of simple and easily applicable actions in case they are confronted with a harassment situation can strengthen bystanders’ knowledge and give them the confidence to support victims.

Finally, treatment 3 incentives individual to act regardless of others’ behaviour and to be aware of pluralistic ignorance, and to acknowledge that

We expect certain characteristics, such as gender, age, gender norms, and previous experience of sexual harassment, to play a significant role in influencing individuals' responses to the treatments and their willingness to support victims. By examining these heterogeneity factors, we can gain valuable insights into how different subgroups react to the information treatments, contributing to a comprehensive understanding of the study's findings.

Experiment Design

The survey methodology consists of several steps, as depicted in Figure 1. Initially, respondents answer questions about their individual characteristics, such as age, education, household composition, gender, employment type, and the nature of their workplace. This "Baseline" part of the survey also includes questions about gender norms from the World Value Survey and experiences of harassment and workplace discrimination.

Next, respondents are presented with three sets of questions that capture their "prior beliefs" regarding the extent of sexual harassment, the costs for victims and abusers, and good practices for addressing such situations.

Afterward, respondents are randomly assigned to three treatment groups and two control groups. The control groups will initially be pooled together for the analysis, and later separated for robustness checks, ensuring that any effects observed are not solely due to information provision itself (Haarland et al., 2022). This step helps to verify that the results are not influenced by respondents spending more time on the survey due to information exposure.

Finally, all respondents will be asked the same set of questions following randomization. First, they will be asked about working conditions broadly, ensuring that their responses to the primary outcomes are not direct reactions to the treatment and helping to address potential sociability desirability bias. Lastly, they will be presented with the questions described in the "primary outcome" section, which are focused on their willingness to allocate personal resources to support causes related to workplace violence.

By following this comprehensive survey paired with an RCT methodology, we aim to obtain valuable insights into how information treatments impact individuals' beliefs and behaviours regarding sexual harassment in the workplace and their willingness to help potential victims.
Randomization Method
The randomization will be computerized using Qualtrics.
Randomization Unit
The randomization unit is the individuals.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
The sample size has a planned number of observations of about 3000 workers, but we will collect as much as possible. We plan to deliver the survey to 30000 workers with a response rate of 10%, which is an estimation for the literature using social media ads ((Hakimov et al., 2022; Allcott et al., 2020, 2022; Beknazar-Yuzbashev and Stalinski, 2022; Levy, 2021; Tromholt, 2016; Arenas-Arroyo et al., 2021).
Sample size (or number of clusters) by treatment arms
Each of the five treatment groups and control group is estimated to contain at least 500 workers.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee - Department of Social Policy - London School of Economics
IRB Approval Date
2023-08-24
IRB Approval Number
254175

Post-Trial

Post Trial Information

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials