Appearance Norms in Academic Settings

Last registered on October 17, 2023

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Pre-Trial

Trial Information

General Information

Title

Appearance Norms in Academic Settings

RCT ID

AEARCTR-0010183

Initial registration date

October 15, 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 17, 2023, 1:51 PM EDT

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

Locations

Country

United States of America

Region

Primary Investigator

Name

Jeffrey Shrader

Affiliation

Columbia University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Tarikua Erda

PI Affiliation

Columbia University

Contact Investigator

Additional Trial Information

Status

On going

Start date

2023-10-15

End date

2024-06-30

Keywords

Behavior, Education, Labor

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

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

Abstract

Appearance is potentially important in academic settings: in-person/virtual job-talks for academic hiring are common across many fields; personal websites and videos summarizing research articles are becoming standard; speeches and seminars are a routine part of publicizing papers. Are there definitive norms of appearance in academia, or are they more like unspoken rules and are there differences across disciplines? How does the public’s understanding of norms compare against the views of academics? We plan to answer these questions by surveying three groups of respondents—faculty, university students, and lay adults—about their perception of academic job candidates they know to be hypothetical. In particular, we will ask them to rate pictured headshots on perceived competence, professionalism, and agreeability. This study will generate novel evidence on norms of appearance in academic settings.

This Pre-Analysis Plan is being filed concurrently with the launch of the lay adult and student sample surveys.

External Link(s)

Registration Citation

Citation

Erda, Tarikua and Jeffrey Shrader. 2023. "Appearance Norms in Academic Settings." AEA RCT Registry. October 17. https://doi.org/10.1257/rct.10183-1.0

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Experimental Details

Interventions

Intervention(s)

Two different information intervention experiments will be conducted on respondents to see whether the interventions will affect how respondents' rating of subsequent headshots.

Intervention Start Date

2023-10-15

Intervention End Date

2024-06-30

Primary Outcomes

Primary Outcomes (end points)

- Ratings of headshots on three main metrics: based on perceived competence, professionalism, and agreeableness.
- The list experiment in our study with a control and treatment group (randomized with even 50% chance) will also produce a set of primary outcomes that will help estimate the share of the population which misreports their opinion on the sensitive statement.

List experiment will also produce measures of the shares of respondents who agree with veiled and/or direct versions of a sensitive statement

Primary Outcomes (explanation)

- The ratings on headshots are direct ratings that each respondent makes based on a 1-10 Likert scale.
- The measurement details for the outcomes from the list experiment follow Aksoy, Carpenter, Sansone (2022) and are explained in more detail in the Analysis Plan.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Not available.

Experimental Design Details

We will use incentivized surveys to examine how three different groups of respondents—lay adults, students, and professors—evaluate headshots of job candidates that they know to be hypothetical along three metrics: professionalism, competence, and agreeableness. We will conduct information intervention experiments to examine and compare the impact of two treatments, one which broadly states that ‘comfort’/‘authenticity’ at work enhances workers’ productivity, and a second one which situates the hair bias in the broader history of structural racial discrimination in the US. All respondents will have a 1/3 chance of ending up in the pure control group, or in either of the two information treatment groups.

To address experimenter demand on the two groups of respondents who received either one of the two information intervention treatments discussed above (these respondents make up two-thirds of the total sample), we will follow de Quidt et al (2018) and conduct an experimenter demand induction treatment. We will randomly divide these two groups of respondents into 3 groups--those who receive no demand (50 percent), weak demand (25 percent), and strong demand (25 percent).

To address social desirability bias, we will conduct a list experiment, in which the sample of respondents will be split into treatment and control arms evenly (50% each).

Randomization Method

Randomization will be done by a computer.

Randomization Unit

Randomization will be done at the individual respondent level.

The visual stimuli shown to each survey respondents will be randomly selected from a set of photos by a computer as well.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Approximately 500 university students

Approximately 2500 lay adults

Sample size: planned number of observations

Each respondent will rate 32 photos. A subset of the photos are 'extras' that do not involve experimental manipulation; these will be excluded from the analysis. On average, 14% of the photos a respondent sees will be these extra photos, and the effective sample size will be the number of experimentally manipulated photos seen by all respondents.

Sample size (or number of clusters) by treatment arms

List experiment: control (50 percent) and treatment (50 percent)
Information intervention: control (1/3), generic treatment (1/3), main treatment (1/3)
Experimenter demand induction: no demand (50 percent), weak demand (25 percent), and strong demand (25 percent)

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

Supporting Documents and Materials

IRB