K12 Labor market for Jewish Americans

Last registered on May 27, 2025

View Trial History

Pre-Trial

Trial Information

General Information

Title

K12 Labor market for Jewish Americans

RCT ID

AEARCTR-0016009

Initial registration date

May 13, 2025

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

May 27, 2025, 6:39 AM 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

Bryan Tomlin

Affiliation

California State University Channel Islands

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

On going

Start date

2025-05-13

End date

2025-12-31

Keywords

Education, Labor

Additional Keywords

Discrimination

JEL code(s)

J10, J15, J71

Secondary IDs

Prior work

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

Abstract

A field-experimental examination of differential treatment of Jewish Americans focusing on the K12 labor market.

External Link(s)

Registration Citation

Citation

Tomlin, Bryan. 2025. "K12 Labor market for Jewish Americans." AEA RCT Registry. May 27. https://doi.org/10.1257/rct.16009-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Identical inquiries differing only in the language of signals indicating membership in the treatment group (Jewish Americans) or the control (Western European Americans).

Intervention (Hidden)

Email inquiries will be sent to elementary, middle, and high-school principals asking for information about potential teaching opportunities at their school. Inquiries are identical except for (a) the teacher's name and (b) the organization for which they mentor youth. Treatment is randomly assigned to principals.

Intervention Start Date

2025-05-13

Intervention End Date

2025-12-31

Primary Outcomes

Primary Outcomes (end points)

Response rates and positive response rates.

Primary Outcomes (explanation)

Response rates are calculated in the usual way (percent of inquiries receiving a response). Positive response rates are also calculated in the usual way (percent of inquiries receiving a "positive response"). A "positive response" is one in which the applicant is not told something discouraging.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Random assignment of treatment and control to the targeted units.

Experimental Design Details

Random assignment of treatment and control to the targeted units (principals of public elementary, middle, and high schools in California, New York, and possibly other states depending on resource availability for gathering observations). Each principal will be sent a single inquiry. We will sample every principal at every school within the targeted school districts (LAUSD, New York City Public Schools, and possibly others) to the best of our ability.

Randomization Method

Targeted unit i is assigned a random number (r_i) using a random number generator (r_i~U[0, 1]). If r_i >= 0.5, the Jewish Treatment is assigned. Otherwise, the Control (Western European) is assigned.

Randomization Unit

The targeted unit (the randomization unit) is disclosed in the hidden portion of the experimental design.

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

At least two school districts.

Sample size: planned number of observations

3,000 targeted units (hidden portion of experimental design defines targeted units).

Sample size (or number of clusters) by treatment arms

Directly proportional to the number of schools within each school district.

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

For alpha = 0.05, assuming a 20% response rate for the control group, power (1 - beta) of 0.80 can be obtained for a difference of 0.06 with approximately N = 1,200, for a difference of 0.05 with approximately N = 1,700, and for a difference of 0.04 with approximately N = 3,000. For N = 3,000, a difference of 0.03 would result in power of a bit under 0.60.

Supporting Documents and Materials

IRB