Gender Bias in Professional Tennis

Last registered on July 25, 2024

View Trial History

Pre-Trial

Trial Information

General Information

Title

Gender Bias in Professional Tennis

RCT ID

AEARCTR-0014001

Initial registration date

July 12, 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

July 17, 2024, 1:42 PM EDT

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

Last updated

July 25, 2024, 6:44 AM EDT

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

Locations

Country

Switzerland

Region

Primary Investigator

Name

Yu Pan

Affiliation

University of Zurich

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Carlos Gomez-Gonzalez

PI Affiliation

Department of Business Administration, University of Zurich

Contact Investigator

PI Name

Helmut Dietl

PI Affiliation

Department of Business Administration, University of Zurich

Contact Investigator

Additional Trial Information

Status

In development

Start date

2024-07-26

End date

2024-08-08

Keywords

Gender

Additional Keywords

Tennis, Gender Bias, Regulatory Focus Theory

JEL code(s)

Secondary IDs

Prior work

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

Abstract

We employ a novel experimental design to investigate gender biases in performance evaluations, specifically examining whether women receive less recognition for their successes and face harsher penalties for their mistakes compared to men. Utilizing advanced artificial intelligence-generated content (AIGC), we manipulate the perceived gender of players, allowing participants to evaluate identical performances attributed to different genders. This methodology isolates and measures the causal effects of gender bias. Our study involves Prolific participants assessing tennis highlights and unforced errors, ensuring evaluations are based solely on performance while varying perceived gender. Grounded in Regulatory Focus Theory, we explore how promotion focus (associated with ambition and risk-taking, typically linked to men) and prevention focus (associated with caution and responsibility, typically linked to women) influence these evaluations. Study 1 examines if men are more generously rewarded for successes, represented by highlights, while Study 2 investigates if women are more severely penalized for failures, represented by unforced errors. We provide novel experimental evidence on the mechanisms of gender bias in performance assessments.

External Link(s)

Registration Citation

Citation

Dietl, Helmut, Carlos Gomez-Gonzalez and Yu Pan. 2024. "Gender Bias in Professional Tennis." AEA RCT Registry. July 25. https://doi.org/10.1257/rct.14001-1.2

Sponsors & Partners

Interventions

Intervention(s)

Our intervention consists of presenting participants with anonymized and gender-reversed video clips of professional tennis matches. The videos are manipulated using advanced artificial intelligence-generated content (AIGC) to create gender-neutral and gender-specific animations. Participants are randomly assigned to one of three treatment groups: (1) watching videos with players represented as unisex robots, (2) watching videos with players animated with distinctly male characteristics, and (3) watching videos with players animated with distinctly female characteristics. This setup allows us to isolate and measure the impact of perceived gender on performance evaluations.

Intervention (Hidden)

Intervention Start Date

2024-07-26

Intervention End Date

2024-08-08

Primary Outcomes

Primary Outcomes (end points)

The key outcome variables of interest in this experiment are:
1. Highlight Rating: The rating given to video highlights by participants, measured on a scale from 1 to 7. This assesses perceptions of high performance.
2. Mistake Rating: The severity rating given to video highlights of mistakes by participants, measured on a scale from 1 to 7. This assesses perceptions of errors.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

This study utilizes a randomized controlled trial design to investigate gender bias in professional tennis performance evaluations. Participants are recruited through the Prolific platform and are randomly assigned to one of four groups: a control group watching standard tennis videos, or one of three treatment groups watching videos where players are depicted as unisex robots, or with distinctly male or female characteristics. The study examines two core questions: whether people reward men and women differently for high performance (Study A), and whether they penalize men and women differently for mistakes (Study B). This design ensures that the same video content is evaluated under different perceived gender conditions, allowing us to isolate the causal effects of gender bias.

Experimental Design Details

Randomization Method

Randomization will be conducted by survey platform automatically.

Randomization Unit

The unit of randomization is the individual participant. Each participant is independently assigned to one of the treatment groups or the control group.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Not applicable, as the randomization unit is the individual participant, not clusters.

Sample size: planned number of observations

We plan to recruit approximately 4,000 participants in total.

Sample size (or number of clusters) by treatment arms

Study 1 (High Performance Evaluation)

Control Group: 400 participants
Manipulation Check Group: 400 participants
Treatment Group 1A (Gender-Neutral Robots): 400 participants
Treatment Group 1B (All-Men Animation): 400 participants
Treatment Group 1C (All-Women Animation): 400 participants

Study 2 (Mistake Evaluation)

Control Group: 400 participants
Manipulation Check Group: 400 participants
Treatment Group 2A (Gender-Neutral Robots): 400 participants
Treatment Group 2B (All-Men Animation): 400 participants
Treatment Group 2C (All-Women Animation): 400 participants

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

Each group in each study will consist of approximately 400 participants, for a total of about 4,000 participants across both studies. This sample size allows for the detection of an effect size of f² = 0.032 with 90% power at an alpha level of 0.01 in a linear regression with 8 predictors.

Supporting Documents and Materials

IRB