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Resumes were sent out to 316 top law firms in the United States, and there were two randomized characteristics of each resume. First, the gender associated with the resume was randomized by assigning a first name of either James or Julia. Second, the socioeconomic class of the candidate was randomly assigned and represented through five minor changes associated with personal interests and other other minor details (e.g. an extracurricular activity of sailing team vs track and field). The outcome variable was whether the candidate was received an interview.

Usage

law_resume

Format

A data frame with 316 observations on the following 3 variables. Each row represents a resume sent a top law firm for this experiment.

gender

The resume implied the candidate was either "male" or "female".

outcome

If the candidate received an invitation for an "interview" or "not".

Source

For a casual overview, see https://hbr.org/2016/12/research-how-subtle-class-cues-can-backfire-on-your-resume.

For the academic paper, see Tilcsik A, Rivera LA. 2016. Class Advantage, Commitment Penalty. The Gendered Effect of Social Class Signals in an Elite Labor Market. American Sociological Review 81:6 p1097-1131. doi: 10.1177/0003122416668154 .

Examples



tapply(law_resume$outcome == "interview", law_resume[, c("class", "gender")], mean)
#>       gender
#> class      female       male
#>   high 0.03797468 0.16250000
#>   low  0.06329114 0.01282051
m <- glm(I(outcome == "interview") ~ gender * class, data = law_resume, family = binomial)
summary(m)
#> 
#> Call:
#> glm(formula = I(outcome == "interview") ~ gender * class, family = binomial, 
#>     data = law_resume)
#> 
#> Deviance Residuals: 
#>     Min       1Q   Median       3Q      Max  
#> -0.5955  -0.3616  -0.2783  -0.1606   2.9518  
#> 
#> Coefficients:
#>                     Estimate Std. Error z value   Pr(>|z|)    
#> (Intercept)          -3.2321     0.5886  -5.491 0.00000004 ***
#> gendermale            1.5924     0.6621   2.405     0.0162 *  
#> classlow              0.5375     0.7483   0.718     0.4726    
#> gendermale:classlow  -3.2416     1.2903  -2.512     0.0120 *  
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> (Dispersion parameter for binomial family taken to be 1)
#> 
#>     Null deviance: 159.68  on 315  degrees of freedom
#> Residual deviance: 144.49  on 312  degrees of freedom
#> AIC: 152.49
#> 
#> Number of Fisher Scoring iterations: 7
#> 
predict(m, type = "response")
#>         84        118        180        285         63        280        293 
#> 0.16250000 0.03797468 0.01282051 0.06329114 0.16250000 0.06329114 0.06329114 
#>        205        194         19         64         54        209        117 
#> 0.01282051 0.01282051 0.06329114 0.16250000 0.16250000 0.01282051 0.03797468 
#>        233        150        216        297        114        231        277 
#> 0.01282051 0.03797468 0.01282051 0.06329114 0.03797468 0.01282051 0.06329114 
#>        312        192         37         79        113          4        111 
#> 0.06329114 0.01282051 0.16250000 0.16250000 0.03797468 0.16250000 0.03797468 
#>        251         98        138        171        141         53        234 
#> 0.06329114 0.03797468 0.03797468 0.01282051 0.03797468 0.16250000 0.01282051 
#>        188        223         31        202        298        227        178 
#> 0.01282051 0.01282051 0.16250000 0.01282051 0.06329114 0.01282051 0.01282051 
#>        215        151        145        214          7        129        197 
#> 0.01282051 0.03797468 0.03797468 0.01282051 0.16250000 0.03797468 0.01282051 
#>        185        128        229        116         65        307         26 
#> 0.01282051 0.03797468 0.01282051 0.03797468 0.16250000 0.06329114 0.16250000 
#>         83        135        313        105        282         75        303 
#> 0.16250000 0.03797468 0.06329114 0.03797468 0.06329114 0.16250000 0.06329114 
#>         85        165        263        120        191         21        217 
#> 0.16250000 0.03797468 0.06329114 0.03797468 0.01282051 0.06329114 0.01282051 
#>        316        206        253         82        264        300        208 
#> 0.06329114 0.01282051 0.06329114 0.16250000 0.06329114 0.06329114 0.01282051 
#>         94        186        228        103        168        239         76 
#> 0.03797468 0.01282051 0.01282051 0.03797468 0.01282051 0.01282051 0.16250000 
#>        176         47        164         28         56         33         55 
#> 0.01282051 0.16250000 0.03797468 0.16250000 0.16250000 0.16250000 0.16250000 
#>         14        144        196        173        177        101         90 
#> 0.03797468 0.03797468 0.01282051 0.01282051 0.01282051 0.03797468 0.03797468 
#>        221        132        142        302         58        212        259 
#> 0.01282051 0.03797468 0.03797468 0.06329114 0.16250000 0.01282051 0.06329114 
#>         45        265        100        193        124        278        273 
#> 0.16250000 0.06329114 0.03797468 0.01282051 0.03797468 0.06329114 0.06329114 
#>         73         88         30          3        224        248         89 
#> 0.16250000 0.16250000 0.16250000 0.16250000 0.01282051 0.06329114 0.16250000 
#>        127        195         97        256         34        272         87 
#> 0.03797468 0.01282051 0.03797468 0.06329114 0.16250000 0.06329114 0.16250000 
#>        287         40         43        112        107         15        270 
#> 0.06329114 0.16250000 0.16250000 0.03797468 0.03797468 0.03797468 0.06329114 
#>        315        170        109        220         95        232        219 
#> 0.06329114 0.01282051 0.03797468 0.01282051 0.03797468 0.01282051 0.01282051 
#>        121        106         42        211        126         78        245 
#> 0.03797468 0.03797468 0.16250000 0.01282051 0.03797468 0.16250000 0.06329114 
#>        268         18        294        236         92        305         74 
#> 0.06329114 0.06329114 0.06329114 0.01282051 0.03797468 0.06329114 0.16250000 
#>        243        182        244         12         44        240        222 
#> 0.06329114 0.01282051 0.06329114 0.16250000 0.16250000 0.01282051 0.01282051 
#>        139         69        250        134        295         10         50 
#> 0.03797468 0.16250000 0.06329114 0.03797468 0.06329114 0.16250000 0.16250000 
#>        108        149         93        122        207        237        226 
#> 0.03797468 0.03797468 0.03797468 0.03797468 0.01282051 0.01282051 0.01282051 
#>        169         91        104        246        200        189        261 
#> 0.01282051 0.03797468 0.03797468 0.06329114 0.01282051 0.01282051 0.06329114 
#>        119         67        242         25         99        308        275 
#> 0.03797468 0.16250000 0.01282051 0.16250000 0.03797468 0.06329114 0.06329114 
#>         70        218         49         13        115         35         72 
#> 0.16250000 0.01282051 0.16250000 0.16250000 0.03797468 0.16250000 0.16250000 
#>        225        314         38        252         32        213         59 
#> 0.01282051 0.06329114 0.16250000 0.06329114 0.16250000 0.01282051 0.16250000 
#>        279        199        271         62        267        210         77 
#> 0.06329114 0.01282051 0.06329114 0.16250000 0.06329114 0.01282051 0.16250000 
#>        102         11         80        190        286        247        288 
#> 0.03797468 0.16250000 0.16250000 0.01282051 0.06329114 0.06329114 0.06329114 
#>        179        269        276        123         16        291         48 
#> 0.01282051 0.06329114 0.06329114 0.03797468 0.03797468 0.06329114 0.16250000 
#>         86        299         24          5        310        255        161 
#> 0.16250000 0.06329114 0.16250000 0.16250000 0.06329114 0.06329114 0.03797468 
#>        159        152        283        175        143         81        158 
#> 0.03797468 0.03797468 0.06329114 0.01282051 0.03797468 0.16250000 0.03797468 
#>        157        167        172        292         68        257        254 
#> 0.03797468 0.01282051 0.01282051 0.06329114 0.16250000 0.06329114 0.06329114 
#>        181        166        301        162        306         51         61 
#> 0.01282051 0.01282051 0.06329114 0.03797468 0.06329114 0.16250000 0.16250000 
#>        284         39        133        184         71        266         22 
#> 0.06329114 0.16250000 0.03797468 0.01282051 0.16250000 0.06329114 0.06329114 
#>        230        296        235        130        174        203          9 
#> 0.01282051 0.06329114 0.01282051 0.03797468 0.01282051 0.01282051 0.16250000 
#>        290         52        155          8        201        198         17 
#> 0.06329114 0.16250000 0.03797468 0.16250000 0.01282051 0.01282051 0.01282051 
#>        140        137        281        204         41        262         29 
#> 0.03797468 0.03797468 0.06329114 0.01282051 0.16250000 0.06329114 0.16250000 
#>          2        183        146        260         36        156        154 
#> 0.16250000 0.01282051 0.03797468 0.06329114 0.16250000 0.03797468 0.03797468 
#>        110        147          6         27        148        274        309 
#> 0.03797468 0.03797468 0.16250000 0.16250000 0.03797468 0.06329114 0.06329114 
#>        160         60        163         46          1         57        136 
#> 0.03797468 0.16250000 0.03797468 0.16250000 0.16250000 0.16250000 0.03797468 
#>         20        304        153        125        249        187         23 
#> 0.06329114 0.06329114 0.03797468 0.03797468 0.06329114 0.01282051 0.16250000 
#>        241        238         66         96        131        311        289 
#> 0.01282051 0.01282051 0.16250000 0.03797468 0.03797468 0.06329114 0.06329114 
#>        258 
#> 0.06329114