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Field
Experimental Design (Public)
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Before
Our treatment changes the descriptions of the jobs workers are considering, thus changing the stakes and consequences of failure. We have two cross-randomized dimensions of treatment:
1) Demographic Reveal: Under Demographic Reveal, the worker’s demographic information (gender and race) is revealed to employer subjects along with their score and their Prolific work history. Under No Demographic Reveal, only the worker’s anonymized quantitative attributes are revealed.
2) Separation Risk: Under Separation Risk, the worker might get “fired” (i.e. not be invited back to complete the second round of puzzles). Under No Separation Risk, the worker will always be invited back to complete the second round and their performance will be used to train employers in a “practice round” of evaluation.
Our final design consists of four treatment cells. Treatment will be stratified by gender (Men and Women) and race (URM versus non-URM). URM in our context means a reported ethnicity of "Black" or "Other" (as opposed to "White" or "Asian") on the platform where we're recruiting. Note: "Other" predominantly includes those who identify exclusively as Hispanic, Latino, American Indian, or Alaska Native.
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After
Our treatment changes the descriptions of the jobs workers are considering, thus changing the stakes and consequences of failure. We have two cross-randomized dimensions of treatment:
1) Demographic Reveal: Under Demographic Reveal, the worker’s demographic information (gender and race) is revealed to employer subjects along with their score and their Prolific work history. Under No Demographic Reveal, only the worker’s anonymized quantitative attributes are revealed.
2) Separation Risk: Under Separation Risk, the worker might get “fired” (i.e. not be invited back to complete the second round of puzzles). Under No Separation Risk, the worker will always be invited back to complete the second round and their performance will be used to train employers in a “practice round” of evaluation.
Our final design consists of four treatment cells. Treatment will be stratified by gender (Men and Women) and race (URM versus non-URM). URM in our context means a reported ethnicity of "Black" or "Other" (as opposed to "White" or "Asian") on the platform where we're recruiting. Note: "Other" predominantly includes those who identify exclusively as Hispanic, Latino, American Indian, or Alaska Native.
If we encounter difficulty recruiting within particular treatment cells due to low overall sample sizes, we may have to adjust our stratification strategy accordingly.
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