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Abstract
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Before
Do implicit gender bias affect managers' discriminating behaviors? Does becoming aware of own implicit bias attenuate discrimination?
The project consist of a two-step lab-in-the-field experiment. As a general summary: we will evaluate gender bias of managers through the IAT test, reveal to the respondents of the treatment group their own score in the IAT, deliver a second survey in which we will be asking managers from treatment and control group to evaluate explicitly hypothetical students profiles according to the methods of the Incentivized Resume Rating.
The experiment is done on two different population:
1) the population of Italian managers making part of the largest managers' association in Italy
2) the population of all employees from a High Tech firm in Italy: in this second case, we will be able to identify employees, middle managers and managers. To the bulk of employees, we will provide two different treatments: the one aforementioned and another treatment containing general information about the gender gap in Italy. We will be able to identify the effect of both disclosing own implicit stereotypes or to provide information about the general status of the labor market in terms of gender gap.
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After
Do implicit gender bias affect managers' discriminating behaviors? Does becoming aware of own implicit bias attenuate discrimination?
The project consist of a two-step lab-in-the-field experiment. As a general summary: we will evaluate gender bias of managers through the IAT test, reveal to the respondents of the treatment group their own score in the IAT, deliver a second survey in which we will be asking managers from treatment and control group to evaluate explicitly hypothetical students profiles according to the methods of the Incentivized Resume Rating.
The experiment is done on two different population:
1) the population of Italian managers making part of the largest managers' association in Italy
2) the population of all employees from a High Tech firm in Italy: in this second case, we will be able to identify employees, middle managers and managers. To the bulk of employees, we will provide two different treatments: the one aforementioned and another treatment containing general information about the gender gap in Italy. We will be able to identify the effect of both disclosing own implicit stereotypes or to provide information about the general status of the labor market in terms of gender gap.
We decided to evaluate the effects of our treatment in the long-run as well. At the end of January 2023, after about 8 months from our treatment, we will replicate the Incentivized Resume Rating (the evaluation of Curricula), to study whether the treatment still has an effect on the score given to candidates.
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Last Published
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Before
October 14, 2022 05:48 AM
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After
January 10, 2023 04:29 AM
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Primary Outcomes (End Points)
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Before
The primary outcomes will be the score provided by respondents to the Incentivized Resume Rating. Through the Incentivized Resume Rating we will ask managers to evaluate 10 explicitly fake CVs, that contain a bunch of information such as gender, GPA, previous education, work experience, experience abroad, languages.
Please find attached the second survey containing the IRR. You will see only one CV, as characteristics inside of it are randomized for 10 iterations, while keeping the shape and presentation of the CV fixed. At the end of each CV, a slider will be used to give an evaluation from 1 to 10.
Managers will be asked to provide an evaluation of each profile on a Likert Scale from 1 to 10. We are interested in understanding how the gender of the profile and manager’s own implicit bias affect the score provided to the profile. Other variables included in the profile and manager’s characteristics will be used as control variables. Our preferred specification will be as follows:
〖Profile Score〗_im= α+βX_i+ρ〖Gender〗_i+ γ〖Treatment〗_m×〖Gender〗_i+δ_m+ε_im
Where X_i are profile characteristics, δ_m are manager’s m fixed effects and γ is our coefficient of interest, identifying the effect of IAT score disclosure on on outcome variable 〖Profile Score〗_im.
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After
The primary outcomes will be the score provided by respondents to the Incentivized Resume Rating. Through the Incentivized Resume Rating we will ask managers to evaluate 10 explicitly fake CVs, that contain a bunch of information such as gender, GPA, previous education, work experience, experience abroad, languages.
Please find attached the second survey containing the IRR. You will see only one CV, as characteristics inside of it are randomized for 10 iterations, while keeping the shape and presentation of the CV fixed. At the end of each CV, a slider will be used to give an evaluation from 1 to 10.
Managers will be asked to provide an evaluation of each profile on a Likert Scale from 1 to 10. We are interested in understanding how the gender of the profile and manager’s own implicit bias affect the score provided to the profile. Other variables included in the profile and manager’s characteristics will be used as control variables. Our preferred specification will be as follows:
〖Profile Score〗_im= α+βX_i+ρ〖Gender〗_i+ γ〖Treatment〗_m×〖Gender〗_i+δ_m+ε_im
Where X_i are profile characteristics, δ_m are manager’s m fixed effects and γ is our coefficient of interest, identifying the effect of IAT score disclosure on on outcome variable 〖Profile Score〗_im.
We replicate the study after 8 months, at the end of January 2023, in order to study whether there is persistency of the effect of the treatment. This time, both Treatment and Control group are "treated", in fact Control group received the IAT score at the end of the first survey in which they were asked to evaluate the Curricula through the incentivized Resume Rating. We hence expect no difference between Treatment and Control groups in the long run (as they are both treated now), but still expect better results in terms of diminished gender gap in scoring with respect to the results obtained with the Control group in the short run. We expect the effect of the treatment diminishes over time, so results might not be as clean and clear as in the short run.
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Experimental Design (Public)
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Before
The treated grous receive the treatment before the Incentivized Resume Rating (IRR). Managers in the control group will receive the control straight after the IRR.
Please refer to the "hidden" experimental design for more information: excessive details in these section might alter results.
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After
The treated grous receive the treatment before the Incentivized Resume Rating (IRR). Managers in the control group will receive the control straight after the IRR.
Please refer to the "hidden" experimental design for more information: excessive details in these section might alter results.
To test the long-run effect, we will also replicate the IRR after about 8 months, at the end of January 2023. We want to test whether there is persistency of the results.
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Secondary Outcomes (End Points)
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Before
The other outcomes will be given by the IAT score itself, which will be regressed on manager’s individual characteristics.
We will also use firm’s performance variables and the share of women in the firm and in managerial positions as outcome variables, and study whether manager’s bias affect these figures.
Evetually, we also use explicit attitudes and belilefs of managers on the IAT score, showing whether correlation arises between explicit and implicit attitudes. This is ex ante ambiguous and the prior is that the explanatory power of the IAT score in explaining explicit bias is low. This might be due both to Social Desirability Bias, for which managers provide answers that are more acceptable, but also to the fact that managers are trained in answering these type of questions in a non discriminatory way (thanks for example to diversity training they have undertaken during their career).
An additional secondary outcome is the time spent on CVs. This can be recorded through Qualtrics.
In order to incentivize the participation in the second survey, we would also provide the possibility to win a 200 euros prize for those who would finish the resume rating. At the end of the resume rating, we ask both treatment and control group to state how much of these 200 euros, in case of win, they would donate to an association promoting women empowerment in the labor market. This is an incentivized outcome as well and might be interesting if our treatment has any effect on this.
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After
The other outcomes will be given by the IAT score itself, which will be regressed on manager’s individual characteristics.
We will also use firm’s performance variables and the share of women in the firm and in managerial positions as outcome variables, and study whether manager’s bias affect these figures.
Evetually, we also use explicit attitudes and belilefs of managers on the IAT score, showing whether correlation arises between explicit and implicit attitudes. This is ex ante ambiguous and the prior is that the explanatory power of the IAT score in explaining explicit bias is low. This might be due both to Social Desirability Bias, for which managers provide answers that are more acceptable, but also to the fact that managers are trained in answering these type of questions in a non discriminatory way (thanks for example to diversity training they have undertaken during their career).
An additional secondary outcome is the time spent on CVs. This can be recorded through Qualtrics.
In order to incentivize the participation in the second survey, we would also provide the possibility to win a 200 euros prize for those who would finish the resume rating. At the end of the resume rating, we ask both treatment and control group to state how much of these 200 euros, in case of win, they would donate to an association promoting women empowerment in the labor market. This is an incentivized outcome as well and might be interesting if our treatment has any effect on this.
We also test whether in the long run respondents will remember their IAT association. At the end of january 2023, in the replication of the IRR, we will also ask whether a candidate remembers his own score (and ask which one it was, to see if it matches).
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