Participant Information

## 
## Non-White     White 
## 0.3354839 0.6645161

Main Effects

Tokenism

{Supervisor}’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

##            [,1]       [,2]      
## condition  "sexism"   "trad"    
## mean_token "3.395699" "2.537634"
## sd_token   "1.705093" "1.575144"

Fear of social retaliation

In this situation, I was concerned about being… - shunned or excluded by others at work - slighted or ignored by others at work - gossiped about in an unkind way - threatened - criticized for complaining - blamed - considered a “troublemaker”

##           [,1]       [,2]      
## condition "sexism"   "trad"    
## mean_fsr  "2.174603" "1.829314"
## sd_fsr    "1.468906" "1.257346"

Belonging

{supervisor’s} behavior made me… - feel like I didn’t belong.
- feel like I didn’t fit in.

##             [,1]       [,2]      
## condition   "sexism"   "trad"    
## mean_belong "2.003247" "1.661290"
## sd_belong   "1.574404" "1.359115"

Implicit Voice Theories - Negative Career Outcomes

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.

##             [,1]       [,2]      
## condition   "sexism"   "trad"    
## mean_ivtneg "3.312903" "3.193182"
## sd_ivtneg   "1.846063" "1.696672"

Implicit Voice Theories - Presumed Target Identification

In terms of {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.

##            [,1]       [,2]      
## condition  "sexism"   "trad"    
## mean_ivtpt "3.270968" "2.926407"
## sd_ivtpt   "1.826843" "1.707026"

Organizational Commitment

I was willing to put in a great deal of effort beyond that normally expected in order to help this organization be successful.
I wanted 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.

##           [,1]       [,2]      
## condition "sexism"   "trad"    
## mean_comm "4.490323" "4.774510"
## sd_comm   "1.430161" "1.337947"

Controls

Tokenism - Still significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition + formaltrain_job + formaltrain_sexism + voicesol +  
##     voice_work + voice_sexm + sentiment_1 + sup_gend + ethn_bin +  
##     age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "token", ]
## 
## REML criterion at convergence: 1128.4
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.02505 -0.62252 -0.07515  0.55407  2.68553 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.240    1.114   
##  Residual                  1.285    1.133   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                      Estimate Std. Error         df t value Pr(>|t|)    
## (Intercept)          2.461585   0.832511 142.730090   2.957  0.00364 ** 
## conditiontrad       -0.855263   0.130006 151.000000  -6.579 7.33e-10 ***
## formaltrain_job      0.034774   0.100405 141.000003   0.346  0.72961    
## formaltrain_sexism   0.123594   0.077658 141.000000   1.592  0.11373    
## voicesol            -0.075588   0.125964 140.999999  -0.600  0.54942    
## voice_work           0.036741   0.130928 140.999999   0.281  0.77942    
## voice_sexm           0.050602   0.112843 141.000000   0.448  0.65453    
## sentiment_1         -0.130512   0.085473 141.000000  -1.527  0.12902    
## sup_gendFemale      -0.358556   0.236351 141.000000  -1.517  0.13149    
## ethn_binWhite       -0.399882   0.248919 141.000000  -1.606  0.11041    
## age                  0.021221   0.011195 141.000000   1.896  0.06005 .  
## tenure               0.005246   0.017844 141.000000   0.294  0.76919    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) cndtnt frmltrn_j frmltrn_s voicsl vc_wrk vc_sxm sntm_1
## conditintrd -0.078                                                       
## formltrn_jb -0.415  0.000                                                
## frmltrn_sxs -0.024  0.000 -0.162                                         
## voicesol    -0.313  0.000 -0.136    -0.005                               
## voice_work  -0.366  0.000 -0.050     0.002    -0.227                     
## voice_sexm   0.201  0.000 -0.035    -0.261    -0.210 -0.579              
## sentiment_1  0.153  0.000  0.027    -0.133    -0.280  0.034 -0.103       
## sup_gendFml -0.138  0.000 -0.098    -0.017    -0.176  0.184  0.075 -0.098
## ethn_binWht -0.130  0.000 -0.168     0.263     0.114 -0.098  0.009 -0.134
## age         -0.567  0.000  0.040    -0.145    -0.034  0.294 -0.133  0.029
## tenure       0.306  0.000 -0.145    -0.015    -0.002 -0.216  0.138 -0.022
##             sp_gnF ethn_W age   
## conditintrd                     
## formltrn_jb                     
## frmltrn_sxs                     
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## sup_gendFml                     
## ethn_binWht  0.009              
## age          0.045 -0.070       
## tenure      -0.027 -0.011 -0.495

Fear of Social Retaliation - Still significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition + formaltrain_job + formaltrain_sexism + voicesol +  
##     voice_work + voice_sexm + sentiment_1 + sup_gend + ethn_bin +  
##     age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "fsr", ]
## 
## REML criterion at convergence: 972.5
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.8420 -0.4986 -0.1541  0.2867  3.3811 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.5617   0.7494  
##  Residual                  0.8400   0.9165  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                      Estimate Std. Error         df t value Pr(>|t|)    
## (Intercept)          3.058821   0.601679 143.169465   5.084 1.14e-06 ***
## conditiontrad       -0.370301   0.105133 151.000001  -3.522 0.000566 ***
## formaltrain_job     -0.043728   0.072510 140.999999  -0.603 0.547439    
## formaltrain_sexism   0.073424   0.056082 140.999999   1.309 0.192588    
## voicesol            -0.135335   0.090967 140.999998  -1.488 0.139054    
## voice_work          -0.116687   0.094552 140.999999  -1.234 0.219221    
## voice_sexm           0.141777   0.081492 140.999999   1.740 0.084081 .  
## sentiment_1         -0.357647   0.061726 140.999999  -5.794 4.30e-08 ***
## sup_gendFemale       0.031709   0.170685 140.999999   0.186 0.852887    
## ethn_binWhite       -0.365387   0.179762 140.999999  -2.033 0.043969 *  
## age                  0.012376   0.008085 140.999998   1.531 0.128055    
## tenure              -0.005166   0.012886 140.999998  -0.401 0.689100    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) cndtnt frmltrn_j frmltrn_s voicsl vc_wrk vc_sxm sntm_1
## conditintrd -0.087                                                       
## formltrn_jb -0.415  0.000                                                
## frmltrn_sxs -0.024  0.000 -0.162                                         
## voicesol    -0.312  0.000 -0.136    -0.005                               
## voice_work  -0.365  0.000 -0.050     0.002    -0.227                     
## voice_sexm   0.201  0.000 -0.035    -0.261    -0.210 -0.579              
## sentiment_1  0.153  0.000  0.027    -0.133    -0.280  0.034 -0.103       
## sup_gendFml -0.138  0.000 -0.098    -0.017    -0.176  0.184  0.075 -0.098
## ethn_binWht -0.130  0.000 -0.168     0.263     0.114 -0.098  0.009 -0.134
## age         -0.566  0.000  0.040    -0.145    -0.034  0.294 -0.133  0.029
## tenure       0.306  0.000 -0.145    -0.015    -0.002 -0.216  0.138 -0.022
##             sp_gnF ethn_W age   
## conditintrd                     
## formltrn_jb                     
## frmltrn_sxs                     
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## sup_gendFml                     
## ethn_binWht  0.009              
## age          0.045 -0.070       
## tenure      -0.027 -0.011 -0.495

Belonging - Still significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition + formaltrain_job + formaltrain_sexism + voicesol +  
##     voice_work + voice_sexm + sentiment_1 + sup_gend + ethn_bin +  
##     age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "belong", ]
## 
## REML criterion at convergence: 1016.1
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.6531 -0.4660 -0.1738  0.2395  4.1281 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.4316   0.657   
##  Residual                  1.1297   1.063   
## Number of obs: 303, groups:  participantid, 152
## 
## Fixed effects:
##                      Estimate Std. Error         df t value Pr(>|t|)    
## (Intercept)         3.523e+00  6.070e-01  1.433e+02   5.804 3.99e-08 ***
## conditiontrad      -3.748e-01  1.222e-01  1.506e+02  -3.067  0.00256 ** 
## formaltrain_job    -7.195e-02  7.308e-02  1.405e+02  -0.985  0.32649    
## formaltrain_sexism  1.255e-01  5.662e-02  1.411e+02   2.217  0.02825 *  
## voicesol           -2.200e-01  9.170e-02  1.406e+02  -2.399  0.01777 *  
## voice_work         -1.376e-01  9.528e-02  1.405e+02  -1.444  0.15106    
## voice_sexm          7.298e-02  8.211e-02  1.404e+02   0.889  0.37559    
## sentiment_1        -2.966e-01  6.220e-02  1.404e+02  -4.769 4.58e-06 ***
## sup_gendFemale     -2.672e-01  1.722e-01  1.409e+02  -1.552  0.12294    
## ethn_binWhite      -2.191e-02  1.813e-01  1.408e+02  -0.121  0.90400    
## age                 1.062e-02  8.155e-03  1.408e+02   1.302  0.19488    
## tenure              5.668e-04  1.299e-02  1.406e+02   0.044  0.96526    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) cndtnt frmltrn_j frmltrn_s voicsl vc_wrk vc_sxm sntm_1
## conditintrd -0.101                                                       
## formltrn_jb -0.415  0.002                                                
## frmltrn_sxs -0.023 -0.004 -0.163                                         
## voicesol    -0.312  0.002 -0.135    -0.007                               
## voice_work  -0.365 -0.001 -0.051     0.004    -0.228                     
## voice_sexm   0.201  0.001 -0.035    -0.261    -0.210 -0.579              
## sentiment_1  0.153  0.001  0.027    -0.134    -0.279  0.034 -0.103       
## sup_gendFml -0.137 -0.003 -0.099    -0.014    -0.178  0.185  0.074 -0.099
## ethn_binWht -0.130  0.003 -0.167     0.259     0.116 -0.099  0.009 -0.133
## age         -0.564 -0.003  0.038    -0.141    -0.036  0.294 -0.133  0.029
## tenure       0.305  0.002 -0.145    -0.017    -0.001 -0.217  0.138 -0.022
##             sp_gnF ethn_W age   
## conditintrd                     
## formltrn_jb                     
## frmltrn_sxs                     
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## sup_gendFml                     
## ethn_binWht  0.007              
## age          0.047 -0.073       
## tenure      -0.029 -0.010 -0.495

Implicit Voice Theory - Presumed Target Identification - Still significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition + formaltrain_job + formaltrain_sexism + voicesol +  
##     voice_work + voice_sexm + sentiment_1 + sup_gend + ethn_bin +  
##     age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtpt", ]
## 
## REML criterion at convergence: 1113.3
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.21998 -0.45711 -0.06542  0.41539  3.09742 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.335    1.155   
##  Residual                  1.147    1.071   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                      Estimate Std. Error         df t value Pr(>|t|)    
## (Intercept)          4.113589   0.837977 142.524188   4.909 2.47e-06 ***
## conditiontrad       -0.348684   0.122872 151.000000  -2.838  0.00517 ** 
## formaltrain_job      0.059976   0.101101 141.000000   0.593  0.55398    
## formaltrain_sexism  -0.039747   0.078196 141.000000  -0.508  0.61204    
## voicesol            -0.194773   0.126837 141.000000  -1.536  0.12687    
## voice_work          -0.003331   0.131836 140.999998  -0.025  0.97988    
## voice_sexm          -0.031020   0.113625 140.999999  -0.273  0.78525    
## sentiment_1         -0.367615   0.086066 140.999999  -4.271 3.55e-05 ***
## sup_gendFemale       0.059744   0.237989 140.999999   0.251  0.80215    
## ethn_binWhite       -0.709029   0.250645 140.999999  -2.829  0.00535 ** 
## age                  0.027130   0.011272 140.999999   2.407  0.01739 *  
## tenure              -0.013533   0.017968 140.999999  -0.753  0.45261    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) cndtnt frmltrn_j frmltrn_s voicsl vc_wrk vc_sxm sntm_1
## conditintrd -0.073                                                       
## formltrn_jb -0.415  0.000                                                
## frmltrn_sxs -0.024  0.000 -0.162                                         
## voicesol    -0.313  0.000 -0.136    -0.005                               
## voice_work  -0.366  0.000 -0.050     0.002    -0.227                     
## voice_sexm   0.201  0.000 -0.035    -0.261    -0.210 -0.579              
## sentiment_1  0.153  0.000  0.027    -0.133    -0.280  0.034 -0.103       
## sup_gendFml -0.138  0.000 -0.098    -0.017    -0.176  0.184  0.075 -0.098
## ethn_binWht -0.130  0.000 -0.168     0.263     0.114 -0.098  0.009 -0.134
## age         -0.567  0.000  0.040    -0.145    -0.034  0.294 -0.133  0.029
## tenure       0.306  0.000 -0.145    -0.015    -0.002 -0.216  0.138 -0.022
##             sp_gnF ethn_W age   
## conditintrd                     
## formltrn_jb                     
## frmltrn_sxs                     
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## sup_gendFml                     
## ethn_binWht  0.009              
## age          0.045 -0.070       
## tenure      -0.027 -0.011 -0.495

Implicit Voice Theory - Negative Career Outcomes - Still NOT significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition + formaltrain_job + formaltrain_sexism + voicesol +  
##     voice_work + voice_sexm + sentiment_1 + sup_gend + ethn_bin +  
##     age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtneg", ]
## 
## REML criterion at convergence: 1102.1
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.07119 -0.49551  0.00264  0.43613  2.69245 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.354    1.164   
##  Residual                  1.074    1.037   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                     Estimate Std. Error        df t value Pr(>|t|)    
## (Intercept)          3.40503    0.83403 142.44039   4.083 7.39e-05 ***
## conditiontrad       -0.09539    0.11890 151.00000  -0.802 0.423645    
## formaltrain_job      0.12519    0.10064 141.00000   1.244 0.215589    
## formaltrain_sexism   0.02818    0.07784 141.00000   0.362 0.717872    
## voicesol            -0.24041    0.12626 141.00000  -1.904 0.058935 .  
## voice_work           0.04968    0.13123 141.00000   0.379 0.705602    
## voice_sexm          -0.06917    0.11311 141.00000  -0.612 0.541817    
## sentiment_1         -0.33437    0.08567 141.00000  -3.903 0.000147 ***
## sup_gendFemale      -0.15339    0.23690 141.00000  -0.647 0.518381    
## ethn_binWhite       -0.73801    0.24950 141.00000  -2.958 0.003633 ** 
## age                  0.03847    0.01122 141.00000   3.428 0.000797 ***
## tenure              -0.02961    0.01789 141.00000  -1.655 0.100075    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) cndtnt frmltrn_j frmltrn_s voicsl vc_wrk vc_sxm sntm_1
## conditintrd -0.071                                                       
## formltrn_jb -0.416  0.000                                                
## frmltrn_sxs -0.024  0.000 -0.162                                         
## voicesol    -0.313  0.000 -0.136    -0.005                               
## voice_work  -0.366  0.000 -0.050     0.002    -0.227                     
## voice_sexm   0.201  0.000 -0.035    -0.261    -0.210 -0.579              
## sentiment_1  0.153  0.000  0.027    -0.133    -0.280  0.034 -0.103       
## sup_gendFml -0.138  0.000 -0.098    -0.017    -0.176  0.184  0.075 -0.098
## ethn_binWht -0.130  0.000 -0.168     0.263     0.114 -0.098  0.009 -0.134
## age         -0.567  0.000  0.040    -0.145    -0.034  0.294 -0.133  0.029
## tenure       0.307  0.000 -0.145    -0.015    -0.002 -0.216  0.138 -0.022
##             sp_gnF ethn_W age   
## conditintrd                     
## formltrn_jb                     
## frmltrn_sxs                     
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## sup_gendFml                     
## ethn_binWht  0.009              
## age          0.045 -0.070       
## tenure      -0.027 -0.011 -0.495

Organizational Commitment - Still significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition + formaltrain_job + formaltrain_sexism + voicesol +  
##     voice_work + voice_sexm + sentiment_1 + sup_gend + ethn_bin +  
##     age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "orgcomm", ]
## 
## REML criterion at convergence: 894.3
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.7324 -0.4142  0.0482  0.4673  4.0813 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.6393   0.7995  
##  Residual                  0.5381   0.7336  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                      Estimate Std. Error         df t value Pr(>|t|)    
## (Intercept)          2.172679   0.578080 142.501867   3.758 0.000249 ***
## conditiontrad        0.268092   0.084146 151.000032   3.186 0.001753 ** 
## formaltrain_job     -0.052106   0.069748 140.999939  -0.747 0.456270    
## formaltrain_sexism   0.068351   0.053946 140.999942   1.267 0.207230    
## voicesol             0.264241   0.087502 140.999940   3.020 0.003003 ** 
## voice_work           0.078145   0.090951 140.999939   0.859 0.391687    
## voice_sexm           0.065301   0.078388 140.999941   0.833 0.406225    
## sentiment_1          0.347837   0.059375 140.999942   5.858 3.15e-08 ***
## sup_gendFemale      -0.390935   0.164184 140.999942  -2.381 0.018598 *  
## ethn_binWhite        0.417430   0.172915 140.999942   2.414 0.017058 *  
## age                 -0.006897   0.007777 140.999938  -0.887 0.376674    
## tenure               0.016926   0.012396 140.999941   1.366 0.174270    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) cndtnt frmltrn_j frmltrn_s voicsl vc_wrk vc_sxm sntm_1
## conditintrd -0.073                                                       
## formltrn_jb -0.416  0.000                                                
## frmltrn_sxs -0.024  0.000 -0.162                                         
## voicesol    -0.313  0.000 -0.136    -0.005                               
## voice_work  -0.366  0.000 -0.050     0.002    -0.227                     
## voice_sexm   0.201  0.000 -0.035    -0.261    -0.210 -0.579              
## sentiment_1  0.153  0.000  0.027    -0.133    -0.280  0.034 -0.103       
## sup_gendFml -0.138  0.000 -0.098    -0.017    -0.176  0.184  0.075 -0.098
## ethn_binWht -0.130  0.000 -0.168     0.263     0.114 -0.098  0.009 -0.134
## age         -0.567  0.000  0.040    -0.145    -0.034  0.294 -0.133  0.029
## tenure       0.307  0.000 -0.145    -0.015    -0.002 -0.216  0.138 -0.022
##             sp_gnF ethn_W age   
## conditintrd                     
## formltrn_jb                     
## frmltrn_sxs                     
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## sup_gendFml                     
## ethn_binWht  0.009              
## age          0.045 -0.070       
## tenure      -0.027 -0.011 -0.495

Interactions

Summary

Moderator	Significant DV
Supervisor gender	Belonging
Formal Training in sexism	Fear of Social retaliation
Formal Training in sexism	Belonging
Formal Training in sexism	Organizational Commitment
Formal Training at work	Fear of social retaliation
Formal Training in sexism	Belonging
Formal Training in sexism	IVT - Presumed Target Identification
Formal Training in sexism	Negative Career Outcomes

Supervisor Gender

Tokenism

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * sup_gend + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "token", ]
## 
## REML criterion at convergence: 1117.6
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.2077 -0.5678 -0.0625  0.5742  2.5875 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.146    1.071   
##  Residual                  1.271    1.128   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                    2.577829   0.881290 135.171101   2.925  0.00404
## conditiontrad                 -1.082126   0.191970 150.000013  -5.637 8.34e-08
## sup_gendFemale                -0.530926   0.278090 202.100369  -1.909  0.05765
## ordertraditional_sexism       -0.237030   0.230735 131.999979  -1.027  0.30616
## sexism_voiceselect1            0.533999   0.287391 131.999979   1.858  0.06538
## sexism_voiceselect2            0.287310   0.298705 131.999979   0.962  0.33788
## sexism_voiceselect3            0.184151   0.281080 131.999979   0.655  0.51351
## sexism_voiceselect4            0.625815   0.303647 131.999979   2.061  0.04127
## trad_voiceselect1              0.299199   0.319671 131.999979   0.936  0.35100
## trad_voiceselect2             -0.264441   0.277176 131.999979  -0.954  0.34180
## trad_voiceselect3             -0.173098   0.277564 131.999979  -0.624  0.53395
## trad_voiceselect4             -0.194487   0.298791 131.999979  -0.651  0.51623
## formaltrain_job                0.026694   0.100529 131.999979   0.266  0.79101
## formaltrain_sexism             0.073126   0.077521 131.999979   0.943  0.34725
## voicesol                      -0.136872   0.127600 131.999979  -1.073  0.28538
## voice_work                     0.003023   0.136592 131.999979   0.022  0.98238
## voice_sexm                     0.071330   0.116323 131.999978   0.613  0.54079
## sentiment_1                   -0.104686   0.085365 131.999979  -1.226  0.22226
## ethn_binWhite                 -0.282535   0.260036 131.999979  -1.087  0.27923
## age                            0.019531   0.011198 131.999977   1.744  0.08347
## tenure                         0.004482   0.018142 131.999979   0.247  0.80524
## conditiontrad:sup_gendFemale   0.415459   0.259786 150.000013   1.599  0.11187
##                                 
## (Intercept)                  ** 
## conditiontrad                ***
## sup_gendFemale               .  
## ordertraditional_sexism         
## sexism_voiceselect1          .  
## sexism_voiceselect2             
## sexism_voiceselect3             
## sexism_voiceselect4          *  
## trad_voiceselect1               
## trad_voiceselect2               
## trad_voiceselect3               
## trad_voiceselect4               
## formaltrain_job                 
## formaltrain_sexism              
## voicesol                        
## voice_work                      
## voice_sexm                      
## sentiment_1                     
## ethn_binWhite                   
## age                          .  
## tenure                          
## conditiontrad:sup_gendFemale    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Fear of Social Retaliation

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * sup_gend + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "fsr", ]
## 
## REML criterion at convergence: 970.8
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.7496 -0.4977 -0.1706  0.3324  3.4000 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.5180   0.7198  
##  Residual                  0.8405   0.9168  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                    2.746544   0.640451 135.982056   4.288 3.39e-05
## conditiontrad                 -0.480331   0.156087 150.000001  -3.077  0.00248
## sup_gendFemale                 0.050020   0.207338 217.236129   0.241  0.80959
## ordertraditional_sexism       -0.114577   0.167426 131.999999  -0.684  0.49496
## sexism_voiceselect1            0.245272   0.208537 131.999999   1.176  0.24165
## sexism_voiceselect2            0.140441   0.216746 131.999999   0.648  0.51814
## sexism_voiceselect3            0.321278   0.203957 131.999999   1.575  0.11760
## sexism_voiceselect4            0.313567   0.220333 131.999998   1.423  0.15705
## trad_voiceselect1              0.237493   0.231960 131.999999   1.024  0.30778
## trad_voiceselect2             -0.090390   0.201125 131.999998  -0.449  0.65387
## trad_voiceselect3              0.165938   0.201406 131.999999   0.824  0.41149
## trad_voiceselect4             -0.313839   0.216809 131.999999  -1.448  0.15012
## formaltrain_job               -0.064039   0.072946 131.999998  -0.878  0.38159
## formaltrain_sexism             0.041928   0.056251 131.999998   0.745  0.45737
## voicesol                      -0.187527   0.092589 131.999998  -2.025  0.04485
## voice_work                    -0.087252   0.099114 131.999998  -0.880  0.38029
## voice_sexm                     0.156619   0.084406 131.999998   1.856  0.06575
## sentiment_1                   -0.350595   0.061943 131.999998  -5.660 9.02e-08
## ethn_binWhite                 -0.343675   0.188688 131.999999  -1.821  0.07081
## age                            0.014407   0.008126 131.999997   1.773  0.07853
## tenure                        -0.009601   0.013164 131.999998  -0.729  0.46709
## conditiontrad:sup_gendFemale   0.201502   0.211227 150.000001   0.954  0.34164
##                                 
## (Intercept)                  ***
## conditiontrad                ** 
## sup_gendFemale                  
## ordertraditional_sexism         
## sexism_voiceselect1             
## sexism_voiceselect2             
## sexism_voiceselect3             
## sexism_voiceselect4             
## trad_voiceselect1               
## trad_voiceselect2               
## trad_voiceselect3               
## trad_voiceselect4               
## formaltrain_job                 
## formaltrain_sexism              
## voicesol                     *  
## voice_work                      
## voice_sexm                   .  
## sentiment_1                  ***
## ethn_binWhite                .  
## age                          .  
## tenure                          
## conditiontrad:sup_gendFemale    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Belonging - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * sup_gend + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "belong", ]
## 
## REML criterion at convergence: 1013.9
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.5327 -0.4862 -0.1285  0.2589  4.0951 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.4174   0.6461  
##  Residual                  1.1091   1.0531  
## Number of obs: 303, groups:  participantid, 152
## 
## Fixed effects:
##                                Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                   3.599e+00  6.532e-01  1.365e+02   5.510 1.73e-07
## conditiontrad                -6.377e-01  1.793e-01  1.491e+02  -3.557 0.000504
## sup_gendFemale               -4.877e-01  2.190e-01  2.348e+02  -2.227 0.026917
## ordertraditional_sexism      -3.050e-01  1.706e-01  1.317e+02  -1.788 0.075998
## sexism_voiceselect1           3.929e-01  2.126e-01  1.320e+02   1.848 0.066824
## sexism_voiceselect2           1.750e-01  2.209e-01  1.318e+02   0.792 0.429667
## sexism_voiceselect3           2.113e-01  2.076e-01  1.315e+02   1.018 0.310560
## sexism_voiceselect4           2.265e-01  2.244e-01  1.317e+02   1.009 0.314649
## trad_voiceselect1            -4.301e-02  2.362e-01  1.316e+02  -0.182 0.855820
## trad_voiceselect2            -3.282e-01  2.047e-01  1.314e+02  -1.604 0.111217
## trad_voiceselect3             4.890e-02  2.050e-01  1.315e+02   0.239 0.811864
## trad_voiceselect4            -1.659e-01  2.207e-01  1.315e+02  -0.752 0.453455
## formaltrain_job              -9.492e-02  7.425e-02  1.314e+02  -1.278 0.203357
## formaltrain_sexism            1.000e-01  5.735e-02  1.320e+02   1.744 0.083479
## voicesol                     -2.268e-01  9.425e-02  1.315e+02  -2.406 0.017502
## voice_work                   -1.094e-01  1.009e-01  1.314e+02  -1.085 0.280034
## voice_sexm                    7.709e-02  8.591e-02  1.314e+02   0.897 0.371163
## sentiment_1                  -3.025e-01  6.305e-02  1.315e+02  -4.798 4.28e-06
## ethn_binWhite                 2.127e-02  1.922e-01  1.317e+02   0.111 0.912033
## age                           1.073e-02  8.276e-03  1.317e+02   1.296 0.197235
## tenure                       -6.304e-04  1.341e-02  1.318e+02  -0.047 0.962589
## conditiontrad:sup_gendFemale  4.839e-01  2.431e-01  1.495e+02   1.991 0.048352
##                                 
## (Intercept)                  ***
## conditiontrad                ***
## sup_gendFemale               *  
## ordertraditional_sexism      .  
## sexism_voiceselect1          .  
## sexism_voiceselect2             
## sexism_voiceselect3             
## sexism_voiceselect4             
## trad_voiceselect1               
## trad_voiceselect2               
## trad_voiceselect3               
## trad_voiceselect4               
## formaltrain_job                 
## formaltrain_sexism           .  
## voicesol                     *  
## voice_work                      
## voice_sexm                      
## sentiment_1                  ***
## ethn_binWhite                   
## age                             
## tenure                          
## conditiontrad:sup_gendFemale *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

### Implicit Voice Theory - Presumed Target Identification

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * sup_gend + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtpt", ]
## 
## REML criterion at convergence: 1114.5
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.20874 -0.44737 -0.09207  0.38196  3.09397 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.365    1.168   
##  Residual                  1.155    1.075   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                    3.812184   0.919087 134.643074   4.148 5.91e-05
## conditiontrad                 -0.367150   0.182964 150.000001  -2.007  0.04658
## sup_gendFemale                 0.167317   0.284984 191.435450   0.587  0.55782
## ordertraditional_sexism       -0.030896   0.240868 131.999997  -0.128  0.89813
## sexism_voiceselect1           -0.038359   0.300014 131.999997  -0.128  0.89846
## sexism_voiceselect2            0.206131   0.311824 131.999997   0.661  0.50973
## sexism_voiceselect3            0.375909   0.293425 131.999997   1.281  0.20240
## sexism_voiceselect4            0.373152   0.316983 131.999998   1.177  0.24124
## trad_voiceselect1              0.170786   0.333711 131.999997   0.512  0.60966
## trad_voiceselect2             -0.135830   0.289349 131.999997  -0.469  0.63954
## trad_voiceselect3              0.017348   0.289754 131.999997   0.060  0.95235
## trad_voiceselect4             -0.132777   0.311913 131.999998  -0.426  0.67103
## formaltrain_job                0.073447   0.104944 131.999995   0.700  0.48524
## formaltrain_sexism            -0.077278   0.080925 131.999997  -0.955  0.34136
## voicesol                      -0.238986   0.133204 131.999998  -1.794  0.07508
## voice_work                     0.013533   0.142591 131.999997   0.095  0.92453
## voice_sexm                    -0.008751   0.121431 131.999998  -0.072  0.94266
## sentiment_1                   -0.366493   0.089115 131.999997  -4.113 6.84e-05
## ethn_binWhite                 -0.712129   0.271457 131.999997  -2.623  0.00973
## age                            0.028383   0.011690 131.999996   2.428  0.01653
## tenure                        -0.019562   0.018938 131.999997  -1.033  0.30353
## conditiontrad:sup_gendFemale   0.033816   0.247599 150.000001   0.137  0.89155
##                                 
## (Intercept)                  ***
## conditiontrad                *  
## sup_gendFemale                  
## ordertraditional_sexism         
## sexism_voiceselect1             
## sexism_voiceselect2             
## sexism_voiceselect3             
## sexism_voiceselect4             
## trad_voiceselect1               
## trad_voiceselect2               
## trad_voiceselect3               
## trad_voiceselect4               
## formaltrain_job                 
## formaltrain_sexism              
## voicesol                     .  
## voice_work                      
## voice_sexm                      
## sentiment_1                  ***
## ethn_binWhite                ** 
## age                          *  
## tenure                          
## conditiontrad:sup_gendFemale    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Implicit Voice Theory - Negative Career Outcomes

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * sup_gend + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtneg", ]
## 
## REML criterion at convergence: 1098.2
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.18819 -0.48497 -0.05303  0.43664  2.69450 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.308    1.144   
##  Residual                  1.082    1.040   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                    3.254512   0.896652 134.600352   3.630 0.000402
## conditiontrad                 -0.097826   0.177064 150.000000  -0.552 0.581436
## sup_gendFemale                 0.008814   0.277625 190.547313   0.032 0.974706
## ordertraditional_sexism       -0.074474   0.235008 131.999999  -0.317 0.751819
## sexism_voiceselect1            0.045940   0.292714 131.999999   0.157 0.875528
## sexism_voiceselect2            0.273284   0.304236 131.999999   0.898 0.370681
## sexism_voiceselect3            0.228258   0.286285 131.999999   0.797 0.426702
## sexism_voiceselect4            0.637585   0.309270 131.999999   2.062 0.041210
## trad_voiceselect1              0.006062   0.325591 131.999999   0.019 0.985174
## trad_voiceselect2              0.047168   0.282309 131.999999   0.167 0.867564
## trad_voiceselect3              0.202100   0.282704 131.999999   0.715 0.475944
## trad_voiceselect4             -0.728211   0.304324 131.999999  -2.393 0.018125
## formaltrain_job                0.116470   0.102391 131.999996   1.138 0.257387
## formaltrain_sexism            -0.013874   0.078956 131.999999  -0.176 0.860784
## voicesol                      -0.283151   0.129963 131.999997  -2.179 0.031129
## voice_work                     0.041228   0.139122 132.000000   0.296 0.767430
## voice_sexm                     0.009753   0.118477 132.000000   0.082 0.934518
## sentiment_1                   -0.334368   0.086946 131.999999  -3.846 0.000186
## ethn_binWhite                 -0.775483   0.264852 131.999999  -2.928 0.004019
## age                            0.038534   0.011405 131.999999   3.379 0.000958
## tenure                        -0.037261   0.018478 131.999999  -2.017 0.045770
## conditiontrad:sup_gendFemale   0.004453   0.239615 150.000000   0.019 0.985199
##                                 
## (Intercept)                  ***
## conditiontrad                   
## sup_gendFemale                  
## ordertraditional_sexism         
## sexism_voiceselect1             
## sexism_voiceselect2             
## sexism_voiceselect3             
## sexism_voiceselect4          *  
## trad_voiceselect1               
## trad_voiceselect2               
## trad_voiceselect3               
## trad_voiceselect4            *  
## formaltrain_job                 
## formaltrain_sexism              
## voicesol                     *  
## voice_work                      
## voice_sexm                      
## sentiment_1                  ***
## ethn_binWhite                ** 
## age                          ***
## tenure                       *  
## conditiontrad:sup_gendFemale    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Org Commitment

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * sup_gend + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "orgcomm", ]
## 
## REML criterion at convergence: 903.6
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.6610 -0.4466  0.0291  0.4544  4.0474 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.6628   0.8141  
##  Residual                  0.5397   0.7347  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                    2.086891   0.636829 134.571976   3.277  0.00133
## conditiontrad                  0.336957   0.125075 150.000001   2.694  0.00786
## sup_gendFemale                -0.334079   0.196988 189.955509  -1.696  0.09154
## ordertraditional_sexism        0.266887   0.166918 131.999999   1.599  0.11223
## sexism_voiceselect1           -0.082315   0.207905 131.999999  -0.396  0.69280
## sexism_voiceselect2           -0.025678   0.216089 131.999999  -0.119  0.90559
## sexism_voiceselect3           -0.014643   0.203339 131.999999  -0.072  0.94270
## sexism_voiceselect4           -0.020136   0.219665 131.999999  -0.092  0.92710
## trad_voiceselect1              0.166252   0.231257 131.999999   0.719  0.47347
## trad_voiceselect2              0.100682   0.200515 131.999999   0.502  0.61642
## trad_voiceselect3             -0.204613   0.200795 131.999999  -1.019  0.31006
## trad_voiceselect4              0.093216   0.216151 131.999999   0.431  0.66699
## formaltrain_job               -0.034550   0.072725 131.999997  -0.475  0.63552
## formaltrain_sexism             0.075550   0.056080 131.999999   1.347  0.18023
## voicesol                       0.252373   0.092308 131.999998   2.734  0.00712
## voice_work                     0.049926   0.098814 132.000000   0.505  0.61422
## voice_sexm                     0.057500   0.084150 131.999999   0.683  0.49561
## sentiment_1                    0.358014   0.061755 131.999999   5.797 4.72e-08
## ethn_binWhite                  0.410666   0.188115 131.999999   2.183  0.03080
## age                           -0.007027   0.008101 131.999999  -0.867  0.38730
## tenure                         0.017441   0.013124 132.000000   1.329  0.18617
## conditiontrad:sup_gendFemale  -0.126113   0.169260 150.000001  -0.745  0.45739
##                                 
## (Intercept)                  ** 
## conditiontrad                ** 
## sup_gendFemale               .  
## ordertraditional_sexism         
## sexism_voiceselect1             
## sexism_voiceselect2             
## sexism_voiceselect3             
## sexism_voiceselect4             
## trad_voiceselect1               
## trad_voiceselect2               
## trad_voiceselect3               
## trad_voiceselect4               
## formaltrain_job                 
## formaltrain_sexism              
## voicesol                     ** 
## voice_work                      
## voice_sexm                      
## sentiment_1                  ***
## ethn_binWhite                *  
## age                             
## tenure                          
## conditiontrad:sup_gendFemale    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Formal training in sexism

Tokenism

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: 
## Value ~ condition * formaltrain_sexism + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "token", ]
## 
## REML criterion at convergence: 1119.6
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.28970 -0.57639 -0.03911  0.53868  2.59843 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.149    1.072   
##  Residual                  1.267    1.126   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                    Estimate Std. Error         df t value
## (Intercept)                        2.701343   0.888741 139.713713   3.040
## conditiontrad                     -1.329155   0.299344 150.000001  -4.440
## formaltrain_sexism                 0.006920   0.086215 192.440479   0.080
## ordertraditional_sexism           -0.237030   0.230735 131.999998  -1.027
## sexism_voiceselect1                0.533999   0.287391 131.999998   1.858
## sexism_voiceselect2                0.287310   0.298705 131.999998   0.962
## sexism_voiceselect3                0.184151   0.281080 131.999998   0.655
## sexism_voiceselect4                0.625815   0.303647 131.999998   2.061
## trad_voiceselect1                  0.299199   0.319671 131.999998   0.936
## trad_voiceselect2                 -0.264441   0.277176 131.999998  -0.954
## trad_voiceselect3                 -0.173098   0.277564 131.999998  -0.624
## trad_voiceselect4                 -0.194487   0.298791 131.999998  -0.651
## formaltrain_job                    0.026694   0.100529 131.999998   0.266
## voicesol                          -0.136872   0.127600 131.999998  -1.073
## voice_work                         0.003023   0.136592 131.999998   0.022
## voice_sexm                         0.071330   0.116323 131.999998   0.613
## sentiment_1                       -0.104686   0.085365 131.999998  -1.226
## sup_gendFemale                    -0.323196   0.245890 131.999998  -1.314
## ethn_binWhite                     -0.282535   0.260036 131.999998  -1.087
## age                                0.019531   0.011198 131.999998   1.744
## tenure                             0.004482   0.018142 131.999998   0.247
## conditiontrad:formaltrain_sexism   0.132411   0.075459 150.000001   1.755
##                                  Pr(>|t|)    
## (Intercept)                       0.00283 ** 
## conditiontrad                    1.73e-05 ***
## formaltrain_sexism                0.93611    
## ordertraditional_sexism           0.30616    
## sexism_voiceselect1               0.06538 .  
## sexism_voiceselect2               0.33788    
## sexism_voiceselect3               0.51351    
## sexism_voiceselect4               0.04127 *  
## trad_voiceselect1                 0.35100    
## trad_voiceselect2                 0.34180    
## trad_voiceselect3                 0.53395    
## trad_voiceselect4                 0.51623    
## formaltrain_job                   0.79101    
## voicesol                          0.28538    
## voice_work                        0.98238    
## voice_sexm                        0.54079    
## sentiment_1                       0.22226    
## sup_gendFemale                    0.19099    
## ethn_binWhite                     0.27923    
## age                               0.08347 .  
## tenure                            0.80524    
## conditiontrad:formaltrain_sexism  0.08135 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Fear of Social Retaliation - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: 
## Value ~ condition * formaltrain_sexism + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "fsr", ]
## 
## REML criterion at convergence: 968
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.7945 -0.4837 -0.1426  0.3669  3.4161 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.5326   0.7298  
##  Residual                  0.8114   0.9008  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                    Estimate Std. Error         df t value
## (Intercept)                        2.963281   0.646863 141.381896   4.581
## conditiontrad                     -0.913806   0.239546 150.000001  -3.815
## formaltrain_sexism                -0.034003   0.063841 204.106811  -0.533
## ordertraditional_sexism           -0.114577   0.167426 131.999998  -0.684
## sexism_voiceselect1                0.245272   0.208537 131.999998   1.176
## sexism_voiceselect2                0.140441   0.216746 131.999998   0.648
## sexism_voiceselect3                0.321278   0.203957 131.999998   1.575
## sexism_voiceselect4                0.313567   0.220333 131.999998   1.423
## trad_voiceselect1                  0.237493   0.231960 131.999998   1.024
## trad_voiceselect2                 -0.090390   0.201125 131.999998  -0.449
## trad_voiceselect3                  0.165938   0.201406 131.999998   0.824
## trad_voiceselect4                 -0.313839   0.216809 131.999998  -1.448
## formaltrain_job                   -0.064039   0.072946 131.999998  -0.878
## voicesol                          -0.187527   0.092589 131.999998  -2.025
## voice_work                        -0.087252   0.099114 131.999999  -0.880
## voice_sexm                         0.156619   0.084406 131.999999   1.856
## sentiment_1                       -0.350595   0.061943 131.999998  -5.660
## sup_gendFemale                     0.150771   0.178423 131.999998   0.845
## ethn_binWhite                     -0.343675   0.188688 131.999998  -1.821
## age                                0.014407   0.008126 131.999998   1.773
## tenure                            -0.009601   0.013164 131.999998  -0.729
## conditiontrad:formaltrain_sexism   0.151862   0.060385 150.000001   2.515
##                                  Pr(>|t|)    
## (Intercept)                      1.01e-05 ***
## conditiontrad                    0.000199 ***
## formaltrain_sexism               0.594882    
## ordertraditional_sexism          0.494956    
## sexism_voiceselect1              0.241649    
## sexism_voiceselect2              0.518142    
## sexism_voiceselect3              0.117599    
## sexism_voiceselect4              0.157051    
## trad_voiceselect1                0.307778    
## trad_voiceselect2                0.653865    
## trad_voiceselect3                0.411485    
## trad_voiceselect4                0.150116    
## formaltrain_job                  0.381593    
## voicesol                         0.044846 *  
## voice_work                       0.380286    
## voice_sexm                       0.065749 .  
## sentiment_1                      9.02e-08 ***
## sup_gendFemale                   0.399629    
## ethn_binWhite                    0.070811 .  
## age                              0.078527 .  
## tenure                           0.467090    
## conditiontrad:formaltrain_sexism 0.012961 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

### Belonging - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: 
## Value ~ condition * formaltrain_sexism + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "belong", ]
## 
## REML criterion at convergence: 1016.1
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.5856 -0.4992 -0.1399  0.2515  4.3100 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.4176   0.6462  
##  Residual                  1.1077   1.0525  
## Number of obs: 303, groups:  participantid, 152
## 
## Fixed effects:
##                                    Estimate Std. Error         df t value
## (Intercept)                       3.727e+00  6.618e-01  1.438e+02   5.631
## conditiontrad                    -8.938e-01  2.803e-01  1.495e+02  -3.188
## formaltrain_sexism                2.700e-02  6.757e-02  2.236e+02   0.400
## ordertraditional_sexism          -3.045e-01  1.705e-01  1.318e+02  -1.786
## sexism_voiceselect1               3.938e-01  2.125e-01  1.320e+02   1.853
## sexism_voiceselect2               1.742e-01  2.208e-01  1.319e+02   0.789
## sexism_voiceselect3               2.116e-01  2.076e-01  1.315e+02   1.019
## sexism_voiceselect4               2.271e-01  2.243e-01  1.317e+02   1.012
## trad_voiceselect1                -4.362e-02  2.362e-01  1.317e+02  -0.185
## trad_voiceselect2                -3.281e-01  2.047e-01  1.315e+02  -1.603
## trad_voiceselect3                 4.928e-02  2.050e-01  1.316e+02   0.240
## trad_voiceselect4                -1.657e-01  2.206e-01  1.315e+02  -0.751
## formaltrain_job                  -9.485e-02  7.423e-02  1.315e+02  -1.278
## voicesol                         -2.267e-01  9.422e-02  1.315e+02  -2.406
## voice_work                       -1.095e-01  1.009e-01  1.315e+02  -1.086
## voice_sexm                        7.714e-02  8.589e-02  1.315e+02   0.898
## sentiment_1                      -3.025e-01  6.304e-02  1.315e+02  -4.798
## sup_gendFemale                   -2.465e-01  1.818e-01  1.319e+02  -1.356
## ethn_binWhite                     2.184e-02  1.921e-01  1.317e+02   0.114
## age                               1.070e-02  8.274e-03  1.317e+02   1.293
## tenure                           -5.827e-04  1.341e-02  1.319e+02  -0.043
## conditiontrad:formaltrain_sexism  1.455e-01  7.086e-02  1.500e+02   2.054
##                                  Pr(>|t|)    
## (Intercept)                      9.09e-08 ***
## conditiontrad                     0.00174 ** 
## formaltrain_sexism                0.68979    
## ordertraditional_sexism           0.07643 .  
## sexism_voiceselect1               0.06616 .  
## sexism_voiceselect2               0.43163    
## sexism_voiceselect3               0.30988    
## sexism_voiceselect4               0.31323    
## trad_voiceselect1                 0.85376    
## trad_voiceselect2                 0.11127    
## trad_voiceselect3                 0.81040    
## trad_voiceselect4                 0.45407    
## formaltrain_job                   0.20359    
## voicesol                          0.01753 *  
## voice_work                        0.27951    
## voice_sexm                        0.37074    
## sentiment_1                      4.28e-06 ***
## sup_gendFemale                    0.17750    
## ethn_binWhite                     0.90968    
## age                               0.19811    
## tenure                            0.96541    
## conditiontrad:formaltrain_sexism  0.04172 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

### Implicit Voice Theory - Presumed Target Identification

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: 
## Value ~ condition * formaltrain_sexism + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtpt", ]
## 
## REML criterion at convergence: 1116.4
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.21803 -0.45078 -0.08912  0.40209  3.07189 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.367    1.169   
##  Residual                  1.151    1.073   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                    Estimate Std. Error         df t value
## (Intercept)                        3.900861   0.925578 138.427353   4.215
## conditiontrad                     -0.544505   0.285256 150.000001  -1.909
## formaltrain_sexism                -0.104635   0.088553 182.979880  -1.182
## ordertraditional_sexism           -0.030896   0.240868 131.999998  -0.128
## sexism_voiceselect1               -0.038359   0.300014 131.999998  -0.128
## sexism_voiceselect2                0.206131   0.311824 131.999998   0.661
## sexism_voiceselect3                0.375909   0.293425 131.999998   1.281
## sexism_voiceselect4                0.373152   0.316983 131.999998   1.177
## trad_voiceselect1                  0.170786   0.333711 131.999998   0.512
## trad_voiceselect2                 -0.135830   0.289349 131.999998  -0.469
## trad_voiceselect3                  0.017348   0.289754 131.999998   0.060
## trad_voiceselect4                 -0.132777   0.311913 131.999998  -0.426
## formaltrain_job                    0.073447   0.104944 131.999997   0.700
## voicesol                          -0.238986   0.133204 131.999998  -1.794
## voice_work                         0.013533   0.142591 131.999998   0.095
## voice_sexm                        -0.008751   0.121431 131.999997  -0.072
## sentiment_1                       -0.366493   0.089115 131.999998  -4.113
## sup_gendFemale                     0.184225   0.256689 131.999997   0.718
## ethn_binWhite                     -0.712129   0.271457 131.999998  -2.623
## age                                0.028383   0.011690 132.000001   2.428
## tenure                            -0.019562   0.018938 131.999999  -1.033
## conditiontrad:formaltrain_sexism   0.054715   0.071908 150.000001   0.761
##                                  Pr(>|t|)    
## (Intercept)                      4.49e-05 ***
## conditiontrad                     0.05819 .  
## formaltrain_sexism                0.23889    
## ordertraditional_sexism           0.89813    
## sexism_voiceselect1               0.89846    
## sexism_voiceselect2               0.50973    
## sexism_voiceselect3               0.20240    
## sexism_voiceselect4               0.24124    
## trad_voiceselect1                 0.60966    
## trad_voiceselect2                 0.63954    
## trad_voiceselect3                 0.95235    
## trad_voiceselect4                 0.67103    
## formaltrain_job                   0.48524    
## voicesol                          0.07508 .  
## voice_work                        0.92453    
## voice_sexm                        0.94266    
## sentiment_1                      6.84e-05 ***
## sup_gendFemale                    0.47421    
## ethn_binWhite                     0.00973 ** 
## age                               0.01653 *  
## tenure                            0.30353    
## conditiontrad:formaltrain_sexism  0.44791    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Implicit Voice Theory - Negative Career Outcomes

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: 
## Value ~ condition * formaltrain_sexism + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtneg", ]
## 
## REML criterion at convergence: 1100.4
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.1473 -0.4930 -0.0687  0.4373  2.6877 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.309    1.144   
##  Residual                  1.080    1.039   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                    Estimate Std. Error         df t value
## (Intercept)                        3.316201   0.902905 138.336322   3.673
## conditiontrad                     -0.221204   0.276338 150.000000  -0.800
## formaltrain_sexism                -0.031450   0.086297 182.296751  -0.364
## ordertraditional_sexism           -0.074474   0.235008 131.999999  -0.317
## sexism_voiceselect1                0.045940   0.292714 131.999999   0.157
## sexism_voiceselect2                0.273284   0.304236 131.999999   0.898
## sexism_voiceselect3                0.228258   0.286285 131.999999   0.797
## sexism_voiceselect4                0.637585   0.309270 131.999999   2.062
## trad_voiceselect1                  0.006062   0.325591 131.999999   0.019
## trad_voiceselect2                  0.047168   0.282309 131.999999   0.167
## trad_voiceselect3                  0.202100   0.282704 131.999999   0.715
## trad_voiceselect4                 -0.728211   0.304324 131.999999  -2.393
## formaltrain_job                    0.116470   0.102391 131.999998   1.138
## voicesol                          -0.283151   0.129963 132.000001  -2.179
## voice_work                         0.041228   0.139122 131.999998   0.296
## voice_sexm                         0.009753   0.118477 131.999999   0.082
## sentiment_1                       -0.334368   0.086946 131.999999  -3.846
## sup_gendFemale                     0.011040   0.250444 131.999999   0.044
## ethn_binWhite                     -0.775483   0.264852 131.999999  -2.928
## age                                0.038534   0.011405 132.000000   3.379
## tenure                            -0.037261   0.018478 131.999999  -2.017
## conditiontrad:formaltrain_sexism   0.035153   0.069660 150.000000   0.505
##                                  Pr(>|t|)    
## (Intercept)                      0.000342 ***
## conditiontrad                    0.424697    
## formaltrain_sexism               0.715950    
## ordertraditional_sexism          0.751819    
## sexism_voiceselect1              0.875528    
## sexism_voiceselect2              0.370681    
## sexism_voiceselect3              0.426702    
## sexism_voiceselect4              0.041210 *  
## trad_voiceselect1                0.985174    
## trad_voiceselect2                0.867564    
## trad_voiceselect3                0.475944    
## trad_voiceselect4                0.018125 *  
## formaltrain_job                  0.257387    
## voicesol                         0.031129 *  
## voice_work                       0.767430    
## voice_sexm                       0.934518    
## sentiment_1                      0.000186 ***
## sup_gendFemale                   0.964904    
## ethn_binWhite                    0.004019 ** 
## age                              0.000958 ***
## tenure                           0.045770 *  
## conditiontrad:formaltrain_sexism 0.614558    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Org Commitment - Marginal

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: 
## Value ~ condition * formaltrain_sexism + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "orgcomm", ]
## 
## REML criterion at convergence: 902.9
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.5832 -0.4443  0.0443  0.4532  3.9655 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.6685   0.8176  
##  Residual                  0.5283   0.7268  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                    Estimate Std. Error         df t value
## (Intercept)                        1.951073   0.641077 138.144801   3.043
## conditiontrad                      0.608592   0.193286 150.000000   3.149
## formaltrain_sexism                 0.123120   0.061143 180.853800   2.014
## ordertraditional_sexism            0.266887   0.166918 132.000000   1.599
## sexism_voiceselect1               -0.082315   0.207905 132.000000  -0.396
## sexism_voiceselect2               -0.025678   0.216089 131.999999  -0.119
## sexism_voiceselect3               -0.014643   0.203339 132.000000  -0.072
## sexism_voiceselect4               -0.020136   0.219665 131.999999  -0.092
## trad_voiceselect1                  0.166252   0.231257 132.000000   0.719
## trad_voiceselect2                  0.100682   0.200515 131.999999   0.502
## trad_voiceselect3                 -0.204613   0.200795 131.999999  -1.019
## trad_voiceselect4                  0.093216   0.216151 131.999999   0.431
## formaltrain_job                   -0.034550   0.072725 132.000001  -0.475
## voicesol                           0.252373   0.092308 132.000000   2.734
## voice_work                         0.049926   0.098814 131.999999   0.505
## voice_sexm                         0.057500   0.084150 131.999999   0.683
## sentiment_1                        0.358014   0.061755 131.999999   5.797
## sup_gendFemale                    -0.397135   0.177882 131.999999  -2.233
## ethn_binWhite                      0.410666   0.188115 131.999999   2.183
## age                               -0.007027   0.008101 132.000003  -0.867
## tenure                             0.017441   0.013124 132.000001   1.329
## conditiontrad:formaltrain_sexism  -0.095140   0.048724 150.000000  -1.953
##                                  Pr(>|t|)    
## (Intercept)                       0.00280 ** 
## conditiontrad                     0.00198 ** 
## formaltrain_sexism                0.04553 *  
## ordertraditional_sexism           0.11223    
## sexism_voiceselect1               0.69280    
## sexism_voiceselect2               0.90559    
## sexism_voiceselect3               0.94270    
## sexism_voiceselect4               0.92710    
## trad_voiceselect1                 0.47347    
## trad_voiceselect2                 0.61642    
## trad_voiceselect3                 0.31006    
## trad_voiceselect4                 0.66699    
## formaltrain_job                   0.63552    
## voicesol                          0.00712 ** 
## voice_work                        0.61422    
## voice_sexm                        0.49561    
## sentiment_1                      4.72e-08 ***
## sup_gendFemale                    0.02726 *  
## ethn_binWhite                     0.03080 *  
## age                               0.38730    
## tenure                            0.18617    
## conditiontrad:formaltrain_sexism  0.05273 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Formal training in work

Tokenism

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * formaltrain_job + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "token", ]
## 
## REML criterion at convergence: 1121.4
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.17821 -0.56735 -0.06066  0.56619  2.62914 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.138    1.067   
##  Residual                  1.289    1.135   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                 Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                     2.251846   0.928145 164.146448   2.426   0.0163
## conditiontrad                  -0.430161   0.613169 150.000002  -0.702   0.4841
## formaltrain_job                 0.064570   0.113825 202.757791   0.567   0.5712
## ordertraditional_sexism        -0.237030   0.230735 131.999996  -1.027   0.3062
## sexism_voiceselect1             0.533999   0.287391 131.999997   1.858   0.0654
## sexism_voiceselect2             0.287310   0.298705 131.999997   0.962   0.3379
## sexism_voiceselect3             0.184151   0.281080 131.999996   0.655   0.5135
## sexism_voiceselect4             0.625815   0.303647 131.999997   2.061   0.0413
## trad_voiceselect1               0.299199   0.319671 131.999997   0.936   0.3510
## trad_voiceselect2              -0.264441   0.277176 131.999997  -0.954   0.3418
## trad_voiceselect3              -0.173098   0.277564 131.999997  -0.624   0.5339
## trad_voiceselect4              -0.194487   0.298791 131.999997  -0.651   0.5162
## formaltrain_sexism              0.073126   0.077521 131.999997   0.943   0.3472
## voicesol                       -0.136872   0.127600 131.999996  -1.073   0.2854
## voice_work                      0.003023   0.136592 131.999996   0.022   0.9824
## voice_sexm                      0.071330   0.116323 131.999996   0.613   0.5408
## sentiment_1                    -0.104686   0.085365 131.999996  -1.226   0.2223
## sup_gendFemale                 -0.323196   0.245890 131.999997  -1.314   0.1910
## ethn_binWhite                  -0.282535   0.260036 131.999997  -1.087   0.2792
## age                             0.019531   0.011198 131.999995   1.744   0.0835
## tenure                          0.004482   0.018142 131.999996   0.247   0.8052
## conditiontrad:formaltrain_job  -0.075751   0.106771 150.000002  -0.709   0.4791
##                                
## (Intercept)                   *
## conditiontrad                  
## formaltrain_job                
## ordertraditional_sexism        
## sexism_voiceselect1           .
## sexism_voiceselect2            
## sexism_voiceselect3            
## sexism_voiceselect4           *
## trad_voiceselect1              
## trad_voiceselect2              
## trad_voiceselect3              
## trad_voiceselect4              
## formaltrain_sexism             
## voicesol                       
## voice_work                     
## voice_sexm                     
## sentiment_1                    
## sup_gendFemale                 
## ethn_binWhite                  
## age                           .
## tenure                         
## conditiontrad:formaltrain_job  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Fear of Social Retaliation - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * formaltrain_job + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "fsr", ]
## 
## REML criterion at convergence: 969.1
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.7834 -0.5052 -0.1339  0.3725  3.2322 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.5277   0.7264  
##  Residual                  0.8212   0.9062  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                 Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                     2.186374   0.681160 170.728754   3.210  0.00159
## conditiontrad                   0.640008   0.489460 150.000000   1.308  0.19302
## formaltrain_job                 0.025976   0.084482 215.396137   0.307  0.75878
## ordertraditional_sexism        -0.114577   0.167426 132.000000  -0.684  0.49496
## sexism_voiceselect1             0.245272   0.208537 132.000000   1.176  0.24165
## sexism_voiceselect2             0.140441   0.216746 132.000000   0.648  0.51814
## sexism_voiceselect3             0.321278   0.203957 132.000000   1.575  0.11760
## sexism_voiceselect4             0.313567   0.220333 132.000000   1.423  0.15705
## trad_voiceselect1               0.237493   0.231960 132.000000   1.024  0.30778
## trad_voiceselect2              -0.090390   0.201125 132.000000  -0.449  0.65387
## trad_voiceselect3               0.165938   0.201406 132.000000   0.824  0.41149
## trad_voiceselect4              -0.313839   0.216809 132.000000  -1.448  0.15012
## formaltrain_sexism              0.041928   0.056251 132.000000   0.745  0.45737
## voicesol                       -0.187527   0.092589 132.000001  -2.025  0.04485
## voice_work                     -0.087252   0.099114 132.000000  -0.880  0.38029
## voice_sexm                      0.156619   0.084406 132.000000   1.856  0.06575
## sentiment_1                    -0.350595   0.061943 132.000000  -5.660 9.02e-08
## sup_gendFemale                  0.150771   0.178423 132.000000   0.845  0.39963
## ethn_binWhite                  -0.343675   0.188688 132.000000  -1.821  0.07081
## age                             0.014407   0.008126 132.000000   1.773  0.07853
## tenure                         -0.009601   0.013164 132.000000  -0.729  0.46709
## conditiontrad:formaltrain_job  -0.180032   0.085230 150.000000  -2.112  0.03632
##                                  
## (Intercept)                   ** 
## conditiontrad                    
## formaltrain_job                  
## ordertraditional_sexism          
## sexism_voiceselect1              
## sexism_voiceselect2              
## sexism_voiceselect3              
## sexism_voiceselect4              
## trad_voiceselect1                
## trad_voiceselect2                
## trad_voiceselect3                
## trad_voiceselect4                
## formaltrain_sexism               
## voicesol                      *  
## voice_work                       
## voice_sexm                    .  
## sentiment_1                   ***
## sup_gendFemale                   
## ethn_binWhite                 .  
## age                           .  
## tenure                           
## conditiontrad:formaltrain_job *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Belonging - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * formaltrain_job + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "belong", ]
## 
## REML criterion at convergence: 1006.7
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.6655 -0.4827 -0.1606  0.3210  3.8063 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.4499   0.6707  
##  Residual                  1.0443   1.0219  
## Number of obs: 303, groups:  participantid, 152
## 
## Fixed effects:
##                                 Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                    2.477e+00  7.036e-01  1.786e+02   3.521 0.000546
## conditiontrad                  1.606e+00  5.526e-01  1.493e+02   2.906 0.004222
## formaltrain_job                8.140e-02  8.848e-02  2.295e+02   0.920 0.358554
## ordertraditional_sexism       -3.053e-01  1.706e-01  1.317e+02  -1.790 0.075788
## sexism_voiceselect1            3.925e-01  2.126e-01  1.320e+02   1.846 0.067082
## sexism_voiceselect2            1.753e-01  2.209e-01  1.318e+02   0.794 0.428776
## sexism_voiceselect3            2.112e-01  2.076e-01  1.315e+02   1.017 0.310826
## sexism_voiceselect4            2.262e-01  2.244e-01  1.317e+02   1.008 0.315226
## trad_voiceselect1             -4.274e-02  2.362e-01  1.316e+02  -0.181 0.856696
## trad_voiceselect2             -3.283e-01  2.047e-01  1.314e+02  -1.604 0.111176
## trad_voiceselect3              4.874e-02  2.051e-01  1.315e+02   0.238 0.812483
## trad_voiceselect4             -1.661e-01  2.207e-01  1.315e+02  -0.752 0.453166
## formaltrain_sexism             1.001e-01  5.735e-02  1.320e+02   1.746 0.083154
## voicesol                      -2.268e-01  9.425e-02  1.315e+02  -2.407 0.017483
## voice_work                    -1.094e-01  1.009e-01  1.314e+02  -1.084 0.280236
## voice_sexm                     7.707e-02  8.591e-02  1.314e+02   0.897 0.371321
## sentiment_1                   -3.026e-01  6.306e-02  1.315e+02  -4.799 4.27e-06
## sup_gendFemale                -2.455e-01  1.818e-01  1.319e+02  -1.350 0.179313
## ethn_binWhite                  2.103e-02  1.922e-01  1.317e+02   0.109 0.913038
## age                            1.074e-02  8.277e-03  1.317e+02   1.297 0.196822
## tenure                        -6.509e-04  1.341e-02  1.318e+02  -0.049 0.961373
## conditiontrad:formaltrain_job -3.527e-01  9.616e-02  1.492e+02  -3.668 0.000340
##                                  
## (Intercept)                   ***
## conditiontrad                 ** 
## formaltrain_job                  
## ordertraditional_sexism       .  
## sexism_voiceselect1           .  
## sexism_voiceselect2              
## sexism_voiceselect3              
## sexism_voiceselect4              
## trad_voiceselect1                
## trad_voiceselect2                
## trad_voiceselect3                
## trad_voiceselect4                
## formaltrain_sexism            .  
## voicesol                      *  
## voice_work                       
## voice_sexm                       
## sentiment_1                   ***
## sup_gendFemale                   
## ethn_binWhite                    
## age                              
## tenure                           
## conditiontrad:formaltrain_job ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Implicit Voice Theory - Presumed Target Identification - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * formaltrain_job + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtpt", ]
## 
## REML criterion at convergence: 1112.4
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -2.3647 -0.4461 -0.0840  0.4225  3.2677 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.380    1.175   
##  Residual                  1.125    1.061   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                 Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                     3.241527   0.958329 157.830854   3.382 0.000906
## conditiontrad                   0.774163   0.572860 150.000001   1.351 0.178602
## formaltrain_job                 0.173490   0.116194 189.841772   1.493 0.137069
## ordertraditional_sexism        -0.030896   0.240868 131.999999  -0.128 0.898131
## sexism_voiceselect1            -0.038359   0.300014 131.999999  -0.128 0.898456
## sexism_voiceselect2             0.206131   0.311824 131.999999   0.661 0.509733
## sexism_voiceselect3             0.375909   0.293425 131.999999   1.281 0.202401
## sexism_voiceselect4             0.373152   0.316983 131.999999   1.177 0.241235
## trad_voiceselect1               0.170786   0.333711 131.999999   0.512 0.609662
## trad_voiceselect2              -0.135830   0.289349 131.999999  -0.469 0.639536
## trad_voiceselect3               0.017348   0.289754 131.999999   0.060 0.952350
## trad_voiceselect4              -0.132777   0.311913 131.999999  -0.426 0.671030
## formaltrain_sexism             -0.077278   0.080925 131.999999  -0.955 0.341359
## voicesol                       -0.238986   0.133204 131.999999  -1.794 0.075080
## voice_work                      0.013533   0.142591 131.999999   0.095 0.924531
## voice_sexm                     -0.008751   0.121431 131.999998  -0.072 0.942660
## sentiment_1                    -0.366493   0.089115 131.999999  -4.113 6.84e-05
## sup_gendFemale                  0.184225   0.256689 131.999999   0.718 0.474213
## ethn_binWhite                  -0.712129   0.271457 131.999999  -2.623 0.009732
## age                             0.028383   0.011690 131.999999   2.428 0.016530
## tenure                         -0.019562   0.018938 131.999999  -1.033 0.303530
## conditiontrad:formaltrain_job  -0.200085   0.099752 150.000001  -2.006 0.046673
##                                  
## (Intercept)                   ***
## conditiontrad                    
## formaltrain_job                  
## ordertraditional_sexism          
## sexism_voiceselect1              
## sexism_voiceselect2              
## sexism_voiceselect3              
## sexism_voiceselect4              
## trad_voiceselect1                
## trad_voiceselect2                
## trad_voiceselect3                
## trad_voiceselect4                
## formaltrain_sexism               
## voicesol                      .  
## voice_work                       
## voice_sexm                       
## sentiment_1                   ***
## sup_gendFemale                   
## ethn_binWhite                 ** 
## age                           *  
## tenure                           
## conditiontrad:formaltrain_job *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

### Implicit Voice Theory - Negative Career Outcomes - Significant

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * formaltrain_job + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "ivtneg", ]
## 
## REML criterion at convergence: 1095.1
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -2.59885 -0.50578 -0.01413  0.42003  2.86786 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 1.325    1.151   
##  Residual                  1.047    1.023   
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                 Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                     2.649812   0.934073 157.257028   2.837 0.005157
## conditiontrad                   1.111575   0.552612 150.000001   2.011 0.046064
## formaltrain_job                 0.224008   0.113132 188.634248   1.980 0.049150
## ordertraditional_sexism        -0.074474   0.235008 131.999999  -0.317 0.751819
## sexism_voiceselect1             0.045940   0.292714 131.999999   0.157 0.875528
## sexism_voiceselect2             0.273284   0.304236 131.999999   0.898 0.370681
## sexism_voiceselect3             0.228258   0.286285 131.999999   0.797 0.426702
## sexism_voiceselect4             0.637585   0.309270 131.999999   2.062 0.041210
## trad_voiceselect1               0.006062   0.325591 131.999999   0.019 0.985174
## trad_voiceselect2               0.047168   0.282309 131.999999   0.167 0.867564
## trad_voiceselect3               0.202100   0.282704 131.999999   0.715 0.475944
## trad_voiceselect4              -0.728211   0.304324 131.999999  -2.393 0.018125
## formaltrain_sexism             -0.013874   0.078956 131.999999  -0.176 0.860784
## voicesol                       -0.283151   0.129963 132.000000  -2.179 0.031129
## voice_work                      0.041228   0.139122 131.999998   0.296 0.767430
## voice_sexm                      0.009753   0.118477 131.999999   0.082 0.934518
## sentiment_1                    -0.334368   0.086946 131.999999  -3.846 0.000186
## sup_gendFemale                  0.011040   0.250444 131.999999   0.044 0.964904
## ethn_binWhite                  -0.775483   0.264852 131.999999  -2.928 0.004019
## age                             0.038534   0.011405 132.000000   3.379 0.000958
## tenure                         -0.037261   0.018478 131.999999  -2.017 0.045770
## conditiontrad:formaltrain_job  -0.215076   0.096226 150.000001  -2.235 0.026888
##                                  
## (Intercept)                   ** 
## conditiontrad                 *  
## formaltrain_job               *  
## ordertraditional_sexism          
## sexism_voiceselect1              
## sexism_voiceselect2              
## sexism_voiceselect3              
## sexism_voiceselect4           *  
## trad_voiceselect1                
## trad_voiceselect2                
## trad_voiceselect3                
## trad_voiceselect4             *  
## formaltrain_sexism               
## voicesol                      *  
## voice_work                       
## voice_sexm                       
## sentiment_1                   ***
## sup_gendFemale                   
## ethn_binWhite                 ** 
## age                           ***
## tenure                        *  
## conditiontrad:formaltrain_job *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

### Org Commitment

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Value ~ condition * formaltrain_job + order + sexism_voiceselect1 +  
##     sexism_voiceselect2 + sexism_voiceselect3 + sexism_voiceselect4 +  
##     trad_voiceselect1 + trad_voiceselect2 + trad_voiceselect3 +  
##     trad_voiceselect4 + formaltrain_job + formaltrain_sexism +  
##     voicesol + voice_work + voice_sexm + sentiment_1 + sup_gend +  
##     ethn_bin + age + tenure + (1 | participantid)
##    Data: study3_clean_long[study3_clean_long$scale == "orgcomm", ]
## 
## REML criterion at convergence: 905.6
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -3.6687 -0.4111  0.0312  0.4603  4.0554 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  participantid (Intercept) 0.6623   0.8138  
##  Residual                  0.5406   0.7353  
## Number of obs: 304, groups:  participantid, 152
## 
## Fixed effects:
##                                 Estimate Std. Error         df t value Pr(>|t|)
## (Intercept)                     2.227646   0.664131 157.850777   3.354 0.000997
## conditiontrad                   0.055446   0.397138 150.000000   0.140 0.889153
## formaltrain_job                -0.053496   0.080526 189.883603  -0.664 0.507284
## ordertraditional_sexism         0.266887   0.166918 131.999999   1.599 0.112232
## sexism_voiceselect1            -0.082315   0.207905 131.999999  -0.396 0.692799
## sexism_voiceselect2            -0.025678   0.216089 131.999999  -0.119 0.905592
## sexism_voiceselect3            -0.014643   0.203339 131.999999  -0.072 0.942699
## sexism_voiceselect4            -0.020136   0.219665 131.999999  -0.092 0.927103
## trad_voiceselect1               0.166252   0.231257 131.999999   0.719 0.473470
## trad_voiceselect2               0.100682   0.200515 131.999999   0.502 0.616423
## trad_voiceselect3              -0.204613   0.200795 131.999999  -1.019 0.310062
## trad_voiceselect4               0.093216   0.216151 131.999999   0.431 0.666987
## formaltrain_sexism              0.075550   0.056080 131.999999   1.347 0.180228
## voicesol                        0.252373   0.092308 131.999997   2.734 0.007116
## voice_work                      0.049926   0.098814 131.999999   0.505 0.614220
## voice_sexm                      0.057500   0.084150 131.999999   0.683 0.495612
## sentiment_1                     0.358014   0.061755 131.999999   5.797 4.72e-08
## sup_gendFemale                 -0.397135   0.177882 131.999999  -2.233 0.027262
## ethn_binWhite                   0.410666   0.188115 131.999999   2.183 0.030800
## age                            -0.007027   0.008101 131.999998  -0.867 0.387304
## tenure                          0.017441   0.013124 131.999999   1.329 0.186165
## conditiontrad:formaltrain_job   0.037892   0.069154 150.000000   0.548 0.584543
##                                  
## (Intercept)                   ***
## conditiontrad                    
## formaltrain_job                  
## ordertraditional_sexism          
## sexism_voiceselect1              
## sexism_voiceselect2              
## sexism_voiceselect3              
## sexism_voiceselect4              
## trad_voiceselect1                
## trad_voiceselect2                
## trad_voiceselect3                
## trad_voiceselect4                
## formaltrain_sexism               
## voicesol                      ** 
## voice_work                       
## voice_sexm                       
## sentiment_1                   ***
## sup_gendFemale                *  
## ethn_binWhite                 *  
## age                              
## tenure                           
## conditiontrad:formaltrain_job    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

DEI VS - Study 3 Summary

Participant Information

Main Effects

Tokenism

Fear of social retaliation

Belonging

Implicit Voice Theories - Negative Career Outcomes

Implicit Voice Theories - Presumed Target Identification

Organizational Commitment

Controls

Tokenism - Still significant

Fear of Social Retaliation - Still significant

Belonging - Still significant

Implicit Voice Theory - Presumed Target Identification - Still significant

Implicit Voice Theory - Negative Career Outcomes - Still NOT significant

Organizational Commitment - Still significant

Interactions

Summary

Supervisor Gender

Tokenism

Fear of Social Retaliation

Belonging - Significant

Implicit Voice Theory - Negative Career Outcomes

Org Commitment

Formal training in sexism

Tokenism

Fear of Social Retaliation - Significant

Implicit Voice Theory - Negative Career Outcomes

Org Commitment - Marginal

Formal training in work

Tokenism

Fear of Social Retaliation - Significant

Belonging - Significant

Implicit Voice Theory - Presumed Target Identification - Significant