Gender-Fair Framing of Job Titles

Last registered on February 22, 2023
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Pre-Trial

Trial Information

General Information

Title
Gender-Fair Framing of Job Titles
RCT ID
AEARCTR-0008060
Initial registration date
September 02, 2021

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
September 03, 2021, 5:25 PM EDT

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

Last updated
February 22, 2023, 8:20 AM EST

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

Locations

Country
Germany
Region

Primary Investigator

Name
Paul M. Gorny
Affiliation
Karlsruhe Institute of Technology
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Other Primary Investigator(s)

PI Name
Petra Nieken
PI Affiliation
Karlsruhe Institute of Technology
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2021-09-06
End date
2022-11-15
Keywords
Gender, Labor
Additional Keywords
Recruitment, Bias, Discrimination, Gender-Fair Language
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study the effects of gender-fair framing of job titles in online job ads in cooperation with a large online job platform in Germany. We use a randomized controlled trial (RCT) design. We are particularly interested in how the usage of the gender-fair variant affects the female to male applicant ratio as well as the overall number of applications. The goals of our study are (i) to investigate whether the female applicant ratio can be increased by deviating from the “generic masculinum” which is typically used in German, (ii) study whether any changes in overall applicant numbers are due to a specific sex of the applicants, and (iii) investigate whether and how these effects differ across industries and jobs.

We focus on three broad categories of jobs as used by the online job platform: “IT & Development”, “Business and Management” and “Marketing and Sales”. For the jobs contained within these categories, we can use secondary data to see whether these jobs empirically more often are occupied by men or women. We only use full-time positions for jobs not already advertised using gender-fair titles by the hiring company within each of the above-mentioned categories.

Our study encompasses two treatments per each of the three broad industry categories: In the baseline, we record the number of female applications for job titles using the generic masculinum. In the gender-fair treatment, we record the female applicant ratio when jobs are advertised using a gender-fair frame. The RCT will be conducted in cooperation with a German online job platform and all applications towards the eligible jobs, as described earlier, can be part of the study and will, upon checking eligibility, enter the RCT and thus be randomly assigned to one of the two treatments with equal probability.
External Link(s)

Registration Citation

Citation
Gorny, Paul M. and Petra Nieken. 2023. "Gender-Fair Framing of Job Titles." AEA RCT Registry. February 22. https://doi.org/10.1257/rct.8060-4.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Our study encompasses two treatments per each of the three broad industry categories: In the baseline, we record the number of female applications for job titles using the generic masculinum. In the gender-fair treatment, we record the female applicant ratio when jobs are advertised using agender-fair frame. Target group: The RCT will be conducted in cooperation with a German online job platform and all applications towards the eligible jobs, i.e., full-time jobs not already advertised using gender-fair titles by the hiring company within the categories “IT & Development”, “Business and Management” and “Marketing and Sales”, can be part of the study and will, upon checking eligibility, enter the RCT and thus be randomly assigned to one of the two treatments with equal probability.

Intended purpose: We study the effects of gender-fair framing of job titles in online job platforms in cooperation with a large German online job platform using a randomized controlled trial (RCT) design. We are particularly interested in how the usage of the gender-fair variant affects the female and male applicant ratio as well as the overall number of applications. The goals of our study are (i) to investigate whether the female applicant ratio can be increased by deviating from the “generic masculinum” which is typically used in German, (ii) study whether any changes in overall applicant numbers are due to a specific sex of the applicant, and (iii) investigate whether and how these effects differ across industries and jobs.
Intervention Start Date
2021-09-08
Intervention End Date
2022-11-15

Primary Outcomes

Primary Outcomes (end points)
female_ratio
treatment
indcat
Primary Outcomes (explanation)
female_ratio: Number of female applicants to a job divided by the total number of applicants to a job
treatment: Dummy variable that is 0 for the baseline and 1 for the treatment (gender-fair titles)
indcat: Indicator variable for 1 "IT & Development", 2 "Management and Business" and 3 "Marketing and Sales"

Secondary Outcomes

Secondary Outcomes (end points)
Jobtitle
views_spreading_count
views_native_duration
requirements_appl
size_comp
jobad_postdate
jobad_closedate
alt_titles
Secondary Outcomes (explanation)
Jobtitle: title of advertised job as string
views_spreading_count: Views of Job Ad through Spreading
views_native_duration: Duration of Native Views on the platform (Total, not including views on external platforms)
requirements_appl: number of documents required for application
size_comp: Company Size Categories
jobad_postdate: Postdate of JobAd
jobad_closedate: Closedate of JobAd
alt_titles: Number of alt. Titles

All alternative titles and job descriptions are available as text data.

Experimental Design

Experimental Design
We have two treatment groups (baseline, gender-fair) and job ads will be randomly allocated to one. We only use full-time positions for jobs not already advertised using gender-neutral titles by the hiring company within each of the above-mentioned industry categories.
Experimental Design Details
Randomization Method
The server of the platform assigns each new incoming job ad with the letter A or B with probability 50%. After that, each ad is checked for being in one of the above-mentioned industries and the following criteria: Fulltime job or fulltime traineeship. If the letter A was assigned, the job ad will be displayed using generic male titles (baseline), if the letter B was assigned, gender-fair titles will be used (gender-fair) throughout for the respective ad.
Randomization Unit
Data is organized at the job-ad-level, that is, each job ad that passed through the procedure described in the randomization method is one observation with the number of applications, views and clicks as variable expressions.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
n.a.
Sample size: planned number of observations
Data collection will seize once the last treatment-industry combination has 300 observations. (Total: 2x3x300=1800 observations)
Sample size (or number of clusters) by treatment arms
Data collection will seize once the last treatment-industry combination has 300 observations. (Total: 2x3x300=1800 observations) We will allocate job ads randomly to each treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
A power calculation for a two-sample proportions test (Pearson's chi-squared) yields the following minimal detectable effect size (MDES) for the three categories (alpha=0.5, beta=0.8 and the above numbers for subjects for all of the following): IT & Development: 0.0998 Management and Business: 0.1132 Marketing and Sales: 0.11428
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
November 15, 2022, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
November 15, 2022, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
2051 job ads
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
2051 jobads
Final Sample Size (or Number of Clusters) by Treatment Arms
1,080 jobads with masculine title (369 IT & Development, 410 Business & Management, 301 Marketing & Sales) 971 jobads with gender-fair title (322 IT & Development, 356 Business & Management, 293 Marketing & Sales)
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials