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Field
Last Published
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Before
September 26, 2022 10:49 PM
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After
September 26, 2022 11:38 PM
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Field
Intervention (Public)
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Before
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After
1) Baseline_colour (Treatment 1): A treatment with randomly assigned colours (red or green) to each candidate, but with neither the soft AA policy nor the information about candidates’ ethnicities.
2) Baseline_minority (Treatment 2): A treatment without a soft AA policy but with revealed information on candidates’ ethnicities (White or East Asian).
3) Soft AA_lucky (Treatment 3): A treatment with a soft AA policy for a randomly selected “lucky” group, namely the candidates assigned to red colour (red or green).
4) Soft AA_minority (Treatment 4): A Treatment with a soft AA policy for the ethnic minority group (White or East Asian).
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Field
Secondary Outcomes (End Points)
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Before
The primary outcome (overall effect) can be decomposed to a Frequency Effect (which is mechanically generated by the SAA policy) and a Token effect (which is potentially confounded by several factors). The Frequency Effect measures how the SAA policy increases the number of candidates of the targeted type in the candidate pool, whereas the Token Effect1 measures how the SAA policy impacts the likelihood that a member of the targeted group is hired given that they are selected by the pre-screening process. Our design aims to further disentangle the confounding factors of the Token Effect.
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After
The primary outcome (overall effect) can be decomposed into a Frequency Effect (which is mechanically generated by the SAA policy) and a Token effect (which is potentially confounded by several factors). The Frequency Effect measures how the SAA policy increases the number of candidates of the targeted type in the candidate pool, whereas the Token Effect1 measures how the SAA policy impacts the likelihood that a member of the targeted group is hired given that they are selected by the pre-screening process. Our design aims to further disentangle the confounding factors of the Token Effect.
1 Tokenism is the practice of doing something purely symbolic to appear inclusive. A (numerically) positive Token Effect is a reduction in the probability that a targeted candidate is hired in the presence of an SAA policy conditional on them being in the candidate pool. In this case, additional representation in the candidate pool does not translate fully into improved hiring outcomes for the targeted candidates.
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