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Stereotypes in High-Stakes Decisions: Evidence from U.S. Circuit Courts
Last registered on December 09, 2019

Pre-Trial

Trial Information
General Information
Title
Stereotypes in High-Stakes Decisions: Evidence from U.S. Circuit Courts
RCT ID
AEARCTR-0005149
Initial registration date
December 09, 2019
Last updated
December 09, 2019 2:13 PM EST
Location(s)

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Primary Investigator
Affiliation
University of Warwick
Other Primary Investigator(s)
PI Affiliation
Toulouse School of Economics
PI Affiliation
ETH Z├╝rich
Additional Trial Information
Status
In development
Start date
2020-02-01
End date
2021-01-01
Secondary IDs
Abstract
Attitudes towards social groups such as women and racial minorities are important determinants of decision-making, but they are difficult to measure for individuals in policy-making roles. We propose to address this challenge by studying U.S. appellate court judges, for whom we have large corpora of written text (their published opinions). Using published opinions, we construct a judge-specific measure of gender-stereotyped language (gender slant) by looking at the linguistic association of words identifying gender (male versus female) and words identifying gender stereotypes (career versus family). To improve our understanding of how lexical slant can be interpreted, we plan to conduct an online survey experiment aimed at eliciting gender preferences from judges with the objective of correlating them with our measure of lexical slant.
External Link(s)
Registration Citation
Citation
Ash, Elliott, Daniel Chen and Arianna Ornaghi. 2019. "Stereotypes in High-Stakes Decisions: Evidence from U.S. Circuit Courts." AEA RCT Registry. December 09. https://doi.org/10.1257/rct.5149-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2020-02-01
Intervention End Date
2020-07-01
Primary Outcomes
Primary Outcomes (end points)
Response rates; gender preferences.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We will randomize the salience of the name of the email account and researcher name (and gender) from which the survey invitation is addressed. We will randomize across the names of the author as well as whether the first name or first initial is used.
Experimental Design Details
Not available
Randomization Method
Randomization will be done in an office by a computer.
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
We place to contact around 6,000 judges.
Sample size: planned number of observations
We place to contact around 6,000 judges.
Sample size (or number of clusters) by treatment arms
The judges will be equally split across treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Ethics Commission ETH Zurich
IRB Approval Date
2019-11-15
IRB Approval Number
EK 2019-N-55