Study Summary
I asked participants to evaluate four roles. I used three job role from Heilman et al. (2004) - financial planning analyst (which they found was considered to be masculine), employee assistant analyst (which they found was considered to be feminine), and training analyst (which they found was considered to be neutral: i.e., in between masculine and feminine). I made a “gender diversity training analyst”.
Goal
I predicted that people think a canddiate’s gender is more relevant for the DEI position than other positions. The other items were filler to distract participants from the DEI items.
Study Description
For each role, I asked participants to imagine that they were hiring for that role
Then, I asked participants the following:
1. Nationwide, what percentage of people in each role do you think are
women?
2. To what extent do you think that other people see each role as more
masculine or feminine (1 = Very Masculine, 3 = Slightly Masculine, 4 =
Neither masculine nor feminine, 5 = Slightly feminine, 7 = Very
Feminine; I adapted this from Heilman et al., 2004)?
3. What is the ideal gender that you think others have in mind when
hiring for these positions (1 = Male, 2 = Female, 3 = Non-binary, 4 =
Not listed, 5 = Does Not Matter)?
4. How important do you think it is that the person in this position is
a woman?
Here are the Roles (and their descriptions which I included):
Financial Planning Analyst:.
Providing financial planning information to employees. Informing
employees about within-company benefit options through individual
appointments and in-house workshops.
Locating out-of-company sources that can aid them in mapping out
long-term financial strategies for themselves and their families.
Being good with numbers and knowledgeable about banking, insurance,
accounting, and bond and equity investment.
Staying abreast of programs and practices within the industry concerning
life insurance and mortgage assistance.
Employee Assistance Analyst:.
Providing assistance to employees with personal and family
problems.
Counseling employees about mental health problems through individual
appointments and in-house workshop.
Referring employees to professionals who can aid them in coping with
issues affecting their work performance.
Having good interpersonal skills, sensitivity to the concerns of others,
and the ability to build trusting relationships.
Staying updated of programs and practices within the industry concerning
on-site day care.
Training Analyst:.
Providing skill training to employees who seek to upgrade their roles
within the company.
Informing employees about job advancement opportunities through
individual appointments and in-house workshops.
Referring employees to professionals who can aid them in developing
longterm career goals.
Good communication skills and knowledgeable about job and career
planning.
Is up-to-date with programs and practices within the industry concerning
paid leave for taking courses.
Gender Diversity, Equity, and Inclusion
Analyst:.
Providing training to employees about how to make the workplace better
for women.
Giving information to employees about upcoming company-wide events
intended to honor, or promote, women.
Referring employees to professionals who can offer additional
information about creating a diverse and inclusive environment.
Good communication skills, ability to navigate difficult conversations,
and knowledgeable about the issues that women face in the
workplace.
Stays current on programs and practices within the industry concerning
practices for enhancing gender equity.
Qualifications:
I also asked them to report how important it was that the candidate
possess the following characteristics (scale was 1 = Not at all
important to 7 = Very important):
- Prior Experience.
- Time in similar roles.
- Prior performance in similar roles.
- The candidate’s gender.
- The candidate’s ethnicity.
- The candidate’s ability to connect with other people on the
team.
- The candidate’s ability to connect with other people in the
organization.
- The candidate’s comfort working with numbers.
- The candidate’s creativity.
- The candidate’s interpersonal warmth.
Next step:
Use these findings to justify the following study design:
1. I tell participants that their organization recently decided a new
initiative, and I would like to know who they will solicit voice from.
2. I present three candidates, each with different experiences.
3. I manipulate:
- The focus of the initiative (DEI vs. Financial planning).
4. I measure:
- If participants pick the woman to so solicit voice in the DEI
(vs. finacical planning) condition.
- How interested participants think the woman is in each condition (I
expect people to assume she is more interested in the DEI condition,
relative to the financial planning condition).
Works Cited/Studies Referenced
Heilman, M. E., Wallen, A. S., Fuchs, D., & Tamkins, M. M. (2004). Penalties for success: reactions to women who succeed at male gender-typed tasks. Journal of applied psychology, 89(3), 416.
Participant Summary
I collected data from 102 part-/and full-time workers on Prolific
Nationwide, what percentage of people in each role do you think are women?
Percentage Analyses
## ANOVA Table (type III tests)
##
## $ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 ItemText 3 303 83.2 2.73e-39 * 0.279
##
## $`Mauchly's Test for Sphericity`
## Effect W p p<.05
## 1 ItemText 0.764 6.21e-05 *
##
## $`Sphericity Corrections`
## Effect GGe DF[GG] p[GG] p[GG]<.05 HFe DF[HF] p[HF] p[HF]<.05
## 1 ItemText 0.864 2.59, 261.8 2.58e-34 * 0.889 2.67, 269.3 3.21e-35 *Percentage Graphs
To what extent do you think that other people see each role as more masculine or feminine?
To what extent do you think that other people see each role as more masculine or feminine (1 = Very Masculine, 3 = Slightly Masculine, 4 = Neither masculine nor feminine, 5 = Slightly feminine, 7 = Very Feminine; I adapted this from Heilman et al., 2004)
Masculine Analyses
## ANOVA Table (type III tests)
##
## $ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 ItemText 3 303 143.849 5.83e-58 * 0.496
##
## $`Mauchly's Test for Sphericity`
## Effect W p p<.05
## 1 ItemText 0.786 0.000214 *
##
## $`Sphericity Corrections`
## Effect GGe DF[GG] p[GG] p[GG]<.05 HFe DF[HF] p[HF] p[HF]<.05
## 1 ItemText 0.852 2.56, 258.21 8.31e-50 * 0.876 2.63, 265.48 3.93e-51 *Masculine Graphs
What is the ideal gender that you think others have in mind when hiring for these positions?
As a note: I coded “1” if the participant said that women were the ideal candidates, and “0” if they did not select “woman”.
Selecting a Woman
Ideal Analyses
## ANOVA Table (type III tests)
##
## $ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 ItemText 3 303 65.922 7.72e-33 * 0.278
##
## $`Mauchly's Test for Sphericity`
## Effect W p p<.05
## 1 ItemText 0.606 1.38e-09 *
##
## $`Sphericity Corrections`
## Effect GGe DF[GG] p[GG] p[GG]<.05 HFe DF[HF] p[HF] p[HF]<.05
## 1 ItemText 0.812 2.44, 246.03 3.69e-27 * 0.834 2.5, 252.56 8.25e-28 *Ideal Graphs
Selecting a Man
Ideal Analyses
## ANOVA Table (type III tests)
##
## $ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 ItemText 3 303 59.565 2.69e-30 * 0.242
##
## $`Mauchly's Test for Sphericity`
## Effect W p p<.05
## 1 ItemText 0.287 3.58e-25 *
##
## $`Sphericity Corrections`
## Effect GGe DF[GG] p[GG] p[GG]<.05 HFe DF[HF] p[HF] p[HF]<.05
## 1 ItemText 0.679 2.04, 205.76 2.1e-21 * 0.693 2.08, 210.03 8.52e-22 *Ideal Graphs
How important do you think it is that the person in this position is a woman?
Important Analyses
## ANOVA Table (type III tests)
##
## $ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 ItemText 3 303 52.941 1.53e-27 * 0.139
##
## $`Mauchly's Test for Sphericity`
## Effect W p p<.05
## 1 ItemText 0.202 1.47e-32 *
##
## $`Sphericity Corrections`
## Effect GGe DF[GG] p[GG] p[GG]<.05 HFe DF[HF] p[HF] p[HF]<.05
## 1 ItemText 0.498 1.5, 151.02 5.37e-15 * 0.504 1.51, 152.78 3.84e-15 *Important Graphs
Candidate Qualifications
I asked all participants, for each position, to indicate how much
they think the following qualifications are important for the position:
- Prior Experience.
- Time in similar roles.
- Prior performance in similar roles.
- The candidate’s gender.
- The candidate’s ethnicity.
- The candidate’s ability to connect with other people on the
team.
- The candidate’s ability to connect with other people in the
organization.
- The candidate’s comfort working with numbers.
- The candidate’s creativity.
- The candidate’s interpersonal warmth.
Analyses
## $`Educ. Experience Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 5.01 1.51 0.150
## 2 2. emp_assist (fem) 102 5.18 1.38 0.136
## 3 3. financial (masc) 102 5.78 1.21 0.120
## 4 4. training (neutral) 102 5.35 1.23 0.122
##
## $`Educ. Experience Anova Table`
## $`Educ. Experience Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 10.483 1.4e-06 * 0.045
##
##
## $`Educ. Experience T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) -1.214010 1.00e+00 ns
## 2 Value 1. dei 3. financial (masc) -4.555283 8.82e-05 ****
## 3 Value 1. dei 4. training (neutral) -2.432552 1.01e-01 ns
## 4 Value 2. emp_assist (fem) 3. financial (masc) -4.175532 3.79e-04 ***
## 5 Value 2. emp_assist (fem) 4. training (neutral) -1.386770 1.00e+00 ns
## 6 Value 3. financial (masc) 4. training (neutral) 2.905906 2.70e-02 *
##
## $`Graph of Educ. Experience`
##
## $`Time in Similar Roles Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 5.43 1.29 0.127
## 2 2. emp_assist (fem) 102 5.65 1.10 0.109
## 3 3. financial (masc) 102 5.99 0.97 0.0960
## 4 4. training (neutral) 102 5.76 1.03 0.102
##
## $`Time in Similar Roles Anova Table`
## $`Time in Similar Roles Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 9.354 6.23e-06 * 0.033
##
##
## $`Time in Similar Roles T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) -1.910845 0.353000 ns
## 2 Value 1. dei 3. financial (masc) -4.335615 0.000206 ***
## 3 Value 1. dei 4. training (neutral) -2.982679 0.021000 *
## 4 Value 2. emp_assist (fem) 3. financial (masc) -3.367105 0.006000 **
## 5 Value 2. emp_assist (fem) 4. training (neutral) -1.330167 1.000000 ns
## 6 Value 3. financial (masc) 4. training (neutral) 2.290832 0.145000 ns
##
## $`Graph of Time in Similar Roles`
##
## $`Prior Performance Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 5.72 1.28 0.127
## 2 2. emp_assist (fem) 102 5.92 1.01 0.100
## 3 3. financial (masc) 102 6.12 0.947 0.0938
## 4 4. training (neutral) 102 5.91 1.02 0.101
##
## $`Prior Performance Anova Table`
## $`Prior Performance Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 4.613 0.004 * 0.017
##
##
## $`Prior Performance T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) -1.8798776 0.378 ns
## 2 Value 1. dei 3. financial (masc) -3.1051578 0.015 *
## 3 Value 1. dei 4. training (neutral) -1.6489827 0.612 ns
## 4 Value 2. emp_assist (fem) 3. financial (masc) -2.0518498 0.257 ns
## 5 Value 2. emp_assist (fem) 4. training (neutral) 0.1105718 1.000 ns
## 6 Value 3. financial (masc) 4. training (neutral) 2.0424685 0.262 ns
##
## $`Graph of Prior Performance`
##
## $`Gender Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 3.84 2.22 0.219
## 2 2. emp_assist (fem) 102 2.07 1.54 0.153
## 3 3. financial (masc) 102 1.78 1.30 0.128
## 4 4. training (neutral) 102 1.79 1.37 0.136
##
## $`Gender Anova Table`
## $`Gender Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 74.753 3.25e-36 * 0.215
##
##
## $`Gender T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) 8.3272710 2.53e-12 ****
## 2 Value 1. dei 3. financial (masc) 9.5217207 6.12e-15 ****
## 3 Value 1. dei 4. training (neutral) 9.6888427 2.61e-15 ****
## 4 Value 2. emp_assist (fem) 3. financial (masc) 2.9645430 2.30e-02 *
## 5 Value 2. emp_assist (fem) 4. training (neutral) 3.7806270 2.00e-03 **
## 6 Value 3. financial (masc) 4. training (neutral) -0.1295599 1.00e+00 ns
##
## $`Graph of Gender`
##
## $`Ethnicity Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 2.76 1.97 0.195
## 2 2. emp_assist (fem) 102 1.87 1.48 0.147
## 3 3. financial (masc) 102 1.71 1.32 0.130
## 4 4. training (neutral) 102 1.70 1.26 0.124
##
## $`Ethnicity Anova Table`
## $`Ethnicity Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 33.779 7.32e-19 * 0.076
##
##
## $`Ethnicity T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) 5.6801895 7.80e-07 ****
## 2 Value 1. dei 3. financial (masc) 6.3772453 3.29e-08 ****
## 3 Value 1. dei 4. training (neutral) 6.9422189 2.28e-09 ****
## 4 Value 2. emp_assist (fem) 3. financial (masc) 1.9913207 2.95e-01 ns
## 5 Value 2. emp_assist (fem) 4. training (neutral) 2.6175864 6.10e-02 ns
## 6 Value 3. financial (masc) 4. training (neutral) 0.1451633 1.00e+00 ns
##
## $`Graph of Ethnicity`
##
## $`Ability to connect with others on the team Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 5.97 1.19 0.118
## 2 2. emp_assist (fem) 102 6.14 1.10 0.109
## 3 3. financial (masc) 102 4.95 1.37 0.136
## 4 4. training (neutral) 102 5.96 1.12 0.111
##
## $`Ability to connect with others on the team Anova Table`
## $`Ability to connect with others on the team Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 35.386 1.23e-19 * 0.134
##
##
## $`Ability to connect with others on the team T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) -1.23981978 1.00e+00 ns
## 2 Value 1. dei 3. financial (masc) 7.04216980 1.41e-09 ****
## 3 Value 1. dei 4. training (neutral) 0.08380427 1.00e+00 ns
## 4 Value 2. emp_assist (fem) 3. financial (masc) 8.35945499 2.15e-12 ****
## 5 Value 2. emp_assist (fem) 4. training (neutral) 2.07068487 2.45e-01 ns
## 6 Value 3. financial (masc) 4. training (neutral) -7.22953540 5.70e-10 ****
##
## $`Graph of Ability to connect with others on the team`
##
## $`Ability to connect with others in the org. Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 6.02 1.20 0.119
## 2 2. emp_assist (fem) 102 6.13 1.07 0.106
## 3 3. financial (masc) 102 4.98 1.41 0.140
## 4 4. training (neutral) 102 6.02 1.05 0.104
##
## $`Ability to connect with others in the org. Anova Table`
## $`Ability to connect with others in the org. Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 38.019 7e-21 * 0.134
##
##
## $`Ability to connect with others in the org. T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) -0.9324103 1.00e+00 ns
## 2 Value 1. dei 3. financial (masc) 7.0188024 1.58e-09 ****
## 3 Value 1. dei 4. training (neutral) 0.0000000 1.00e+00 ns
## 4 Value 2. emp_assist (fem) 3. financial (masc) 7.8352474 2.93e-11 ****
## 5 Value 2. emp_assist (fem) 4. training (neutral) 1.3702387 1.00e+00 ns
## 6 Value 3. financial (masc) 4. training (neutral) -7.6554199 7.08e-11 ****
##
## $`Graph of Ability to connect with others in the org.`
##
## $`Comfort with numbers Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 3.57 2.00 0.198
## 2 2. emp_assist (fem) 102 3.54 1.87 0.185
## 3 3. financial (masc) 102 6.24 1.19 0.118
## 4 4. training (neutral) 102 4.05 1.79 0.178
##
## $`Comfort with numbers Anova Table`
## $`Comfort with numbers Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 85.58 3.93e-40 * 0.292
##
##
## $`Comfort with numbers T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) 0.2324642 1.00e+00 ns
## 2 Value 1. dei 3. financial (masc) -10.2653530 1.40e-16 ****
## 3 Value 1. dei 4. training (neutral) -3.6810070 2.00e-03 **
## 4 Value 2. emp_assist (fem) 3. financial (masc) -11.0372902 2.83e-18 ****
## 5 Value 2. emp_assist (fem) 4. training (neutral) -3.8199485 1.00e-03 **
## 6 Value 3. financial (masc) 4. training (neutral) 9.5913602 4.28e-15 ****
##
## $`Graph of Comfort with numbers`
##
## $`Creativity Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 5.18 1.42 0.141
## 2 2. emp_assist (fem) 102 4.88 1.39 0.137
## 3 3. financial (masc) 102 4.28 1.50 0.149
## 4 4. training (neutral) 102 5 1.36 0.134
##
## $`Creativity Anova Table`
## $`Creativity Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 12.65 8.2e-08 * 0.053
##
##
## $`Creativity T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) 1.9384118 3.32e-01 ns
## 2 Value 1. dei 3. financial (masc) 4.8836034 2.35e-05 ****
## 3 Value 1. dei 4. training (neutral) 1.2220590 1.00e+00 ns
## 4 Value 2. emp_assist (fem) 3. financial (masc) 3.9637007 8.28e-04 ***
## 5 Value 2. emp_assist (fem) 4. training (neutral) -0.9666769 1.00e+00 ns
## 6 Value 3. financial (masc) 4. training (neutral) -4.3353063 2.07e-04 ***
##
## $`Graph of Creativity`
##
## $`Interpersonal warmth Means + SDs`
## # A tibble: 4 × 5
## condition n mean sd se
## <fct> <dbl> <dbl> <dbl> <dbl>
## 1 1. dei 102 5.99 1.23 0.122
## 2 2. emp_assist (fem) 102 6.26 1.15 0.114
## 3 3. financial (masc) 102 4.47 1.44 0.143
## 4 4. training (neutral) 102 5.85 1.19 0.118
##
## $`Interpersonal warmth Anova Table`
## $`Interpersonal warmth Anova Table`$ANOVA
## Effect DFn DFd F p p<.05 ges
## 1 condition 3 303 73.473 9.79e-36 * 0.234
##
##
## $`Interpersonal warmth T-test Results`
## .y. group1 group2 statistic p.adj p.adj.signif
## 1 Value 1. dei 2. emp_assist (fem) -2.688710 5.00e-02 ns
## 2 Value 1. dei 3. financial (masc) 9.502422 6.72e-15 ****
## 3 Value 1. dei 4. training (neutral) 1.352618 1.00e+00 ns
## 4 Value 2. emp_assist (fem) 3. financial (masc) 11.119885 1.86e-18 ****
## 5 Value 2. emp_assist (fem) 4. training (neutral) 4.196464 3.50e-04 ***
## 6 Value 3. financial (masc) 4. training (neutral) -8.980619 9.42e-14 ****
##
## $`Graph of Interpersonal warmth`