Power analyses
##
## Two-sample t test power calculation
##
## n = 200.4848
## d = 0.3
## sig.level = 0.05
## power = 0.85
## alternative = two.sided
##
## NOTE: n is number in *each* group
Percent that can recall by condition
## [1] "Can Recall : Sexism - 0.307692307692308"
## [1] "Can't Recall : Sexism - 0.692307692307692"
## [1] "Can Recall : Traditional - 0.88"
## [1] "Can't Recall : Traditional - 0.12"
Count who can recall specific types of behaviors
## [1] "asked you personally to tell them what you think would be helpful for...reducing sexism in your workplace/improving your workplace: Sexism - Cannot Recall: 0.865%"
## [1] "asked you personally to tell them what you think would be helpful for...reducing sexism in your workplace/improving your workplace: Traditional - Cannot Recall: 0.365%"
## [1] "asked you personally to tell them what you think would be helpful for...reducing sexism in your workplace/improving your workplace: Sexism - Can Recall: 0.14%"
## [1] "asked you personally to tell them what you think would be helpful for...reducing sexism in your workplace/improving your workplace: Traditional - Can Recall: 0.62%"
## [1] "asked you personally to tell them about how... you have addressed sexism in the past/things have been done in your workplace: Sexism - Cannot Recall: 0.846%"
## [1] "asked you personally to tell them about how... you have addressed sexism in the past/things have been done in your workplace: Traditional - Cannot Recall: 0.654%"
## [1] "asked you personally to tell them about how... you have addressed sexism in the past/things have been done in your workplace: Sexism - Can Recall: 0.16%"
## [1] "asked you personally to tell them about how... you have addressed sexism in the past/things have been done in your workplace: Traditional - Can Recall: 0.32%"
## [1] "sought out your knowledge about... sexism/knowledge about your area of expertise: Sexism - Cannot Recall: 0.885%"
## [1] "sought out your knowledge about... sexism/knowledge about your area of expertise: Traditional - Cannot Recall: 0.462%"
## [1] "sought out your knowledge about... sexism/knowledge about your area of expertise: Sexism - Can Recall: 0.12%"
## [1] "sought out your knowledge about... sexism/knowledge about your area of expertise: Traditional - Can Recall: 0.52%"
## [1] "Asked you personally what skills you have that they may not know about that might contribute to... reducing sexism/improving your workplace: Sexism - Cannot Recall: 1%"
## [1] "Asked you personally what skills you have that they may not know about that might contribute to... reducing sexism/improving your workplace: Traditional - Cannot Recall: 0.808%"
## [1] "Asked you personally what skills you have that they may not know about that might contribute to... reducing sexism/improving your workplace: Sexism - Can Recall: 0%"
## [1] "Asked you personally what skills you have that they may not know about that might contribute to... reducing sexism/improving your workplace: Traditional - Can Recall: 0.16%"
Measures
Main Effects
Tokenism (token)
1 = not at all, 7 = very much so.
Manager’s behavior made me….
- worry that I stand out because I am a woman.
- feel like my skills and knowledge as a woman were made salient
- feel like a “token” representative of women
Belonging (belong/inauth)
Manager’s behavior made me….
- Feel like I didn’t belong.
- feel like I was in a position where I could NOT be the real me.
- feel like I was NOT in a position to be completely myself.
- feel like I was NOT in a position to be authentic.
Self Awareness (selfaw)
Manager’s behavior made me…
- feel concerned about the way I present myself.
- feel self-conscious about the way I look.
- concerned about what my supervisor thinks of me.
Implicit Voice Theory - Negative career consequences of voice (ivt_neg)
In terms of (sexism at work/your job).
- If you want advancement opportunities in today’s world, you have to be
careful about pointing out needs for [reducing sexism in your
workplace/improving your workplace].
- You are more likely to be rewarded in organizational life by “going
along quietly” than by speaking up about [reducing sexism in your
workplace/improving your workplace].
- Pointing out problems, errors, or inefficiencies about [reducing
sexism/improving your workplace] might very well result in lowered job
evaluations.
- Speaking up about [reducing sexism in your workplace/improving your
workplace] sets you up for retribution by those above you who felt
threatened by your comments.
Implicit Voice Theory - Presumed target identification (ivt_pt)
In terms of speaking up about (sexism at work/your job)….
- It’s risky to challenge existing processes because it may be seen as
questioning the status quo.
- Speaking up to suggest a better way is likely to offend them
- It is not good to question the way things are done because they are
likely to take it personally.
Organizational Commitment (orgcomm)
After [manager] asked you to speak up about [your work/prejudice], to
what extent would you agree with the following statements? - I was
willing to put in a great deal of effort beyond that normally expected
in order to help this organization be successful.
- I want to talk up this organization to other women as a great
organization to work for.
- I wondered if my values and the organization’s values are
similar.
- I was extremely glad that I chose this organization to work for, over
others I was considering at the time I joined.
- I felt that working for this organization was a definite mistake on my
part.
Procedural fairness (proc_fair)
Manager’s behavior made me feel….
- like I can express my views and feelings about my treatment to
them.
- like I have influence over the outcomes I receive from them.
- that they apply personnel procedures consistently across all
employees.
- that they value diverse opinions.
- that they treat racial minorities with respect.
Control variables
Voice Solicitation
- Asks me personally to tell them about things that I think would be
helpful for improving this organization.
- Asks me personally to tell them about how things have been done in
my previous job(s).
- Seeks out task-related knowledge from me.
- Asks me personally what skills I have that they may not know about that might contribute to our performance.
Voice about work
- I give [manager] suggestions about how to make this work unit
better, even if others disagree.
- I challenge [manager] to deal with problems around here
- I speak up to [manager] with ideas to address employees’ needs and concerns
Voice about sexism
- I give [manager] suggestions about how to address sexism, even if
others disagree.
- I challenge [manager] to deal with sexism-related problems around
here
- I speak up to [manager] with ideas to address employees’ needs and concerns around sexism
Main Effects
Graphs
Control Analyses
We controlled for:
- Recall (Yes/No).
- Formal Training (Job).
- Formal Training (Sexism).
- Amount manager solicits voice (generally).
- Amount manager solicits voice (about work).
- Amount manager solicits voice (about sexism).
- Sentiment towards supervisor.
- Supervisor’s gender.
- Part-/Full-time employment.
- Participant’s age.
- Dummy-coded (1/0):
+ asked you personally to tell them what you think would be helpful for
(reducing sexism in your workplace/improving your workplace).
+ asked you personally to tell them about how (you have addressed sexism
in the past/things have been done in your workplace).
+ sought out your (knowledge about sexism/knowledge about your area of
expertise).
+ Asked you personally what skills you have that they may not know about
that might contribute to (reducing sexism/improving your workplace).
Baseline condition is “Sexism condition”
Additional Questions from Drew:
We should also test the main effects on the DVs for participants who didn’t recall (i.e., only those in the “imagine” framing).
Among those who just imagined, we did not find significant effects (there are only 40 people in this sample)
Among those who were able to recall, we did not find significant effects (there are only 40 people in this sample)
Reliability
## [1] "Tokenism Reliability: 0.757584856023562"
## [1] "Belonging Reliability: 0.96115709997271"
## [1] "Inauthenticity Reliability: 0.954287557849769"
## [1] "SelfAware Reliability: 0.883051346576002"
## [1] "Fear of Social Retaliation Reliability: 0.944439499469652"
## [1] "Implicit Voice Theory - Negative Career Concerns Reliability: 0.885215986830355"
## [1] "Implicit Voice Theory - Presumed Target Identification Reliability: 0.855605014534883"
## [1] "Organizational Commitment Reliability: 0.723046543545237"
## [1] "Procedural Fairness Reliability: 0.925395071278594"
Factor Analyses + Correlations
Correlation
Table
## [1] "Condition: 1 = Traditional, 0 = Sexism"
## [2] "ivt_negcareer_1 - If you want advancement opportunities in todays world, you have to be careful about pointing out needs for [reducing sexism in your workplace/improving your workplace]."
## [3] "ivt_negcareer_2 - You are more likely to be rewarded in organizational life by going along quietly than by speaking up about [reducing sexism in your workplace/improving your workplace]."
## [4] "ivt_negcareer_3 - Pointing out problems, errors, or inefficiencies about [reducing sexism/improving your workplace] might very well result in lowered job evaluations."
## [5] "ivt_negcareer_4 - Speaking up about [reducing sexism in your workplace/improving your workplace] sets you up for retribution by those above you who felt threatened by your comments."
## [6] "ivt_pt_1 - Its risky to challenge existing processes because it may be seen as questioning the status quo."
## [7] "ivt_pt_2 - Speaking up to suggest a better way is likely to offend them"
## [8] "ivt_pt_3 - It is not good to question the way things are done because they are likely to take it personally."
## [9] "proc_fair_1 - I feel like I can express my views and feelings about my treatment to them."
## [10] "proc_fair_2 - like I have influence over the outcomes I receive from them."
## [11] "proc_fair_3 - that they apply personnel procedures consistently across all employees."
## [12] "proc_fair_4 - that they value diverse opinions."
## [13] "proc_fair_5 - that they treat racial minorities with respect"
## [14] "orgcomm_1 - I was willing to put in a great deal of effort beyond that normally expected in order to help this organization be successful."
## [15] "orgcomm_2 - I want to talk up this organization to other women as a great organization to work for."
## [16] "orcomm_3_r - I wondered if my values and the organization’s values are similar."
## [17] "orcomm_4 - I was extremely glad that I chose this organization to work for, over others I was considering at the time I joined."
## [18] "orgcomm_5 - I felt that working for this organization was a definite mistake on my part."
## [19] "belonging_1 - Feel like I didn’t belong."
Factor Analyses
measures_nocon <- measures %>% dplyr::select(-condition_num)
psych::fa.parallel(measures_nocon, fa = "fa")
## Parallel analysis suggests that the number of factors = 3 and the number of components = NA
## Loading required namespace: GPArotation
## Factor Analysis using method = minres
## Call: psych::fa(r = measures_nocon, nfactors = 3)
## Standardized loadings (pattern matrix) based upon correlation matrix
## MR1 MR2 MR3 h2 u2 com
## ivt_negcareer_1 0.86 0.03 0.13 0.67 0.33 1.0
## ivt_negcareer_2 0.75 -0.09 0.03 0.60 0.40 1.0
## ivt_negcareer_3 0.62 -0.02 -0.28 0.60 0.40 1.4
## ivt_negcareer_4 0.72 -0.07 -0.09 0.62 0.38 1.1
## ivt_pt_1 0.80 0.09 -0.11 0.66 0.34 1.1
## ivt_pt_2 0.62 0.08 -0.34 0.62 0.38 1.6
## ivt_pt_3 0.76 0.04 -0.08 0.60 0.40 1.0
## proc_fair_1 -0.42 0.54 0.14 0.73 0.27 2.0
## proc_fair_2 -0.33 0.55 0.05 0.57 0.43 1.7
## proc_fair_3 -0.48 0.53 -0.18 0.60 0.40 2.2
## proc_fair_4 -0.47 0.60 -0.08 0.72 0.28 1.9
## proc_fair_5 -0.31 0.64 0.19 0.78 0.22 1.7
## orgcomm_1 0.03 0.68 -0.11 0.43 0.57 1.1
## orgcomm_2 0.22 0.83 0.03 0.63 0.37 1.1
## orgcomm_3_r -0.16 -0.03 0.52 0.34 0.66 1.2
## orgcomm_4 0.18 0.85 0.15 0.72 0.28 1.1
## orgcomm_5_r 0.01 0.17 0.72 0.60 0.40 1.1
## belonging_1 0.23 -0.02 -0.50 0.39 0.61 1.4
##
## MR1 MR2 MR3
## SS loadings 5.28 3.90 1.70
## Proportion Var 0.29 0.22 0.09
## Cumulative Var 0.29 0.51 0.60
## Proportion Explained 0.49 0.36 0.16
## Cumulative Proportion 0.49 0.84 1.00
##
## With factor correlations of
## MR1 MR2 MR3
## MR1 1.00 -0.34 -0.35
## MR2 -0.34 1.00 0.25
## MR3 -0.35 0.25 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 3 factors are sufficient.
##
## df null model = 153 with the objective function = 13.32 with Chi Square = 1254.69
## df of the model are 102 and the objective function was 2.27
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.06
##
## The harmonic n.obs is 101 with the empirical chi square 72.17 with prob < 0.99
## The total n.obs was 102 with Likelihood Chi Square = 209.12 with prob < 2.2e-09
##
## Tucker Lewis Index of factoring reliability = 0.851
## RMSEA index = 0.101 and the 90 % confidence intervals are 0.082 0.122
## BIC = -262.63
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## MR1 MR2 MR3
## Correlation of (regression) scores with factors 0.96 0.96 0.88
## Multiple R square of scores with factors 0.93 0.92 0.77
## Minimum correlation of possible factor scores 0.86 0.83 0.54
Moderation analyses
Interactions that stood out to me
## SIMPLE SLOPES ANALYSIS
##
## Slope of ivt_pt when condition = sexism:
##
## Est. S.E. t val. p
## ------ ------ -------- ------
## 0.56 0.12 4.74 0.00
##
## Slope of ivt_pt when condition = traditional:
##
## Est. S.E. t val. p
## ------ ------ -------- ------
## 0.18 0.12 1.45 0.15
## SIMPLE SLOPES ANALYSIS
##
## Slope of proc_fair when condition = sexism:
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.47 0.13 -3.49 0.00
##
## Slope of proc_fair when condition = traditional:
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.09 0.13 -0.69 0.49
## SIMPLE SLOPES ANALYSIS
##
## Slope of sentiment_1 when condition = sexism:
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.38 0.12 -3.15 0.00
##
## Slope of sentiment_1 when condition = traditional:
##
## Est. S.E. t val. p
## ------- ------ -------- ------
## -0.03 0.13 -0.25 0.80
Supervisor Gender
Mediation
##
## Mediation/Moderation Analysis
## Call: psych::mediate(y = orgcomm ~ condition_num + (token), data = dei_vs_outcomes1_clean)
##
## The DV (Y) was orgcomm . The IV (X) was condition_num . The mediating variable(s) = token .
##
## Total effect(c) of condition_num on orgcomm = 0.3 S.E. = 0.23 t = 1.28 df= 100 with p = 0.2
## Direct effect (c') of condition_num on orgcomm removing token = 0.05 S.E. = 0.27 t = 0.19 df= 99 with p = 0.85
## Indirect effect (ab) of condition_num on orgcomm through token = 0.25
## Mean bootstrapped indirect effect = 0.24 with standard error = 0.15 Lower CI = -0.03 Upper CI = 0.55
## R = 0.21 R2 = 0.04 F = 2.28 on 2 and 99 DF p-value: 0.0845
##
## To see the longer output, specify short = FALSE in the print statement or ask for the summary
##
## Mediation/Moderation Analysis
## Call: psych::mediate(y = orgcomm ~ condition_num + (fsr), data = dei_vs_outcomes1_clean)
##
## The DV (Y) was orgcomm . The IV (X) was condition_num . The mediating variable(s) = fsr .
##
## Total effect(c) of condition_num on orgcomm = 0.3 S.E. = 0.23 t = 1.28 df= 100 with p = 0.2
## Direct effect (c') of condition_num on orgcomm removing fsr = -0.01 S.E. = 0.22 t = -0.06 df= 99 with p = 0.96
## Indirect effect (ab) of condition_num on orgcomm through fsr = 0.31
## Mean bootstrapped indirect effect = 0.31 with standard error = 0.13 Lower CI = 0.09 Upper CI = 0.58
## R = 0.42 R2 = 0.18 F = 10.89 on 2 and 99 DF p-value: 3.02e-06
##
## To see the longer output, specify short = FALSE in the print statement or ask for the summary
##
## Mediation/Moderation Analysis
## Call: psych::mediate(y = orgcomm ~ condition_num + (proc_fair), data = dei_vs_outcomes1_clean)
##
## The DV (Y) was orgcomm . The IV (X) was condition_num . The mediating variable(s) = proc_fair .
##
## Total effect(c) of condition_num on orgcomm = 0.3 S.E. = 0.23 t = 1.28 df= 100 with p = 0.2
## Direct effect (c') of condition_num on orgcomm removing proc_fair = 0.1 S.E. = 0.19 t = 0.51 df= 99 with p = 0.61
## Indirect effect (ab) of condition_num on orgcomm through proc_fair = 0.2
## Mean bootstrapped indirect effect = 0.2 with standard error = 0.15 Lower CI = -0.08 Upper CI = 0.52
## R = 0.62 R2 = 0.38 F = 30.48 on 2 and 99 DF p-value: 4.82e-14
##
## To see the longer output, specify short = FALSE in the print statement or ask for the summary