Summary plots:

Regressing on ML-Face detention prediction:

Does fat-faced explain the CNN detention prediction?

Table 4.1 - Fat Faced & Well-groomed:
Correlation between human-labeled novel feature and algorithms prediction
Dependent variable:
Algorithmic Prediction
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Fat-faced -0.016*** -0.015*** -0.015*** -0.014*** -0.015*** -0.014*** -0.015*** -0.015*** -0.015*** -0.015***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Well-groomed -0.017*** -0.016*** -0.018*** -0.017*** -0.018*** -0.017*** -0.016*** -0.014*** -0.015*** -0.014***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Male 0.117*** 0.120*** 0.118*** 0.113*** 0.117*** 0.114*** 0.111*** 0.115*** 0.112*** 0.111*** 0.116*** 0.113***
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.003) (0.002) (0.002) (0.003) (0.002)
Age 0.051 0.044 0.040 0.055 0.048 0.045 0.058 0.048 0.048 0.058 0.048 0.048
(0.098) (0.097) (0.096) (0.097) (0.097) (0.096) (0.096) (0.097) (0.096) (0.096) (0.097) (0.096)
Black 0.001*** 0.0003*** 0.0004*** 0.001*** 0.0003*** 0.0004*** 0.0004*** 0.0003*** 0.0004*** 0.0004*** 0.0003*** 0.0004***
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Unknown Race -0.027*** -0.018*** -0.023*** -0.023*** -0.017*** -0.022*** -0.023*** -0.018*** -0.023***
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Asian 0.011 0.016** 0.019*** 0.016** 0.017** 0.020*** 0.016** 0.017** 0.019***
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Indian -0.021* -0.015 -0.014 -0.019* -0.014 -0.013 -0.019* -0.014 -0.014
(0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011)
Steryotypicall black -0.007 0.016 0.004 0.001 0.018 0.006 0.001 0.017 0.005
(0.024) (0.024) (0.023) (0.023) (0.024) (0.023) (0.023) (0.024) (0.023)
Skin-tone 0.005*** 0.004*** 0.005*** 0.005*** 0.004*** 0.005*** 0.005*** 0.004*** 0.005***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Attractiveness -0.213*** -0.199*** -0.207*** -0.185*** -0.188*** -0.198*** -0.187*** -0.189*** -0.199***
(0.054) (0.054) (0.053) (0.054) (0.054) (0.053) (0.053) (0.054) (0.053)
Competence -0.007*** 0.001 -0.002 -0.007*** 0.001 -0.002
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Dominance -0.009*** -0.006*** -0.006*** -0.009*** -0.006*** -0.006***
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Trustworthiness 0.005*** 0.004*** 0.005*** 0.005*** 0.003*** 0.005***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Human Guess -0.003* -0.003* -0.001 -0.002 -0.003 -0.001
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
detention_likely 0.031*** 0.030*** 0.027***
(0.007) (0.007) (0.007)
Constant 0.334*** 0.334*** 0.409*** 0.215*** 0.237*** 0.301*** 0.214*** 0.235*** 0.299*** 0.274*** 0.240*** 0.303*** 0.257*** 0.223*** 0.287***
(0.005) (0.005) (0.007) (0.005) (0.006) (0.007) (0.006) (0.007) (0.008) (0.009) (0.008) (0.009) (0.010) (0.009) (0.010)
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.028 0.025 0.050 0.223 0.225 0.246 0.228 0.229 0.251 0.243 0.231 0.254 0.244 0.233 0.255
Note: p<0.1; p<0.05; p<0.01

Does facial-hair explain the CNN detention prediction ?

Table 4.2 - Facial hair & Well-Groomed:
Correlation between human-labeled novel feature and algorithms prediction
Dependent variable:
Algorithmic Prediction
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Facial-hair 0.015*** 0.014*** -0.001 -0.004*** -0.001 -0.004*** -0.001* -0.004*** -0.001* -0.004***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Well-groomed -0.017*** -0.012*** -0.018*** -0.020*** -0.018*** -0.020*** -0.016*** -0.017*** -0.015*** -0.017***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Male 0.120*** 0.120*** 0.131*** 0.118*** 0.117*** 0.128*** 0.117*** 0.115*** 0.126*** 0.117*** 0.116*** 0.126***
(0.003) (0.002) (0.003) (0.003) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Age 0.057 0.044 0.048 0.061 0.048 0.054 0.062 0.048 0.054 0.062 0.048 0.054
(0.099) (0.097) (0.097) (0.099) (0.097) (0.097) (0.098) (0.097) (0.097) (0.098) (0.097) (0.097)
Black 0.001*** 0.0003*** 0.0003*** 0.001*** 0.0003*** 0.0004*** 0.0003*** 0.0003*** 0.0003*** 0.0004*** 0.0003*** 0.0004***
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Unknown Race -0.021*** -0.018*** -0.017*** -0.018*** -0.017*** -0.017*** -0.018*** -0.018*** -0.017***
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Asian 0.007 0.016** 0.016** 0.013* 0.017** 0.016** 0.012* 0.017** 0.016**
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Indian -0.023* -0.015 -0.018 -0.021* -0.014 -0.017 -0.021* -0.014 -0.017
(0.012) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011)
Steryotypicall black 0.005 0.016 0.016 0.013 0.018 0.017 0.012 0.017 0.017
(0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024)
Skin-tone 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Attractiveness -0.204*** -0.199*** -0.194*** -0.172*** -0.188*** -0.186*** -0.174*** -0.189*** -0.187***
(0.055) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054)
Competence -0.005*** 0.001 0.001 -0.005*** 0.001 0.001
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Dominance -0.009*** -0.006*** -0.006*** -0.009*** -0.006*** -0.006***
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Trustworthiness 0.004*** 0.004*** 0.004*** 0.003*** 0.003*** 0.003***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Human Guess -0.005*** -0.003* -0.003* -0.005*** -0.003 -0.003*
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
detention_likely 0.034*** 0.030*** 0.029***
(0.007) (0.007) (0.007)
Constant 0.185*** 0.334*** 0.247*** 0.142*** 0.237*** 0.249*** 0.141*** 0.235*** 0.247*** 0.206*** 0.240*** 0.247*** 0.187*** 0.223*** 0.231***
(0.003) (0.005) (0.006) (0.004) (0.006) (0.007) (0.005) (0.007) (0.007) (0.008) (0.008) (0.008) (0.009) (0.009) (0.009)
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.076 0.025 0.087 0.199 0.225 0.227 0.202 0.229 0.231 0.218 0.231 0.234 0.220 0.233 0.235
Note: p<0.1; p<0.05; p<0.01

Does eye-bags explain the CNN detention prediction ?

Table 4.3 - Eye bags & Well-Groomed:
Correlation between human-labeled novel feature and algorithms prediction
Dependent variable:
Algorithmic Prediction
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Eye-bags -0.003*** -0.005*** -0.002** -0.003*** -0.002** -0.003*** -0.003*** -0.003*** -0.003*** -0.003***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Well-groomed -0.017*** -0.018*** -0.018*** -0.018*** -0.018*** -0.018*** -0.016*** -0.016*** -0.015*** -0.015***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Male 0.118*** 0.120*** 0.119*** 0.115*** 0.117*** 0.116*** 0.113*** 0.115*** 0.115*** 0.114*** 0.116*** 0.115***
(0.002) (0.002) (0.002) (0.003) (0.002) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Age 0.051 0.044 0.036 0.054 0.048 0.040 0.054 0.048 0.041 0.053 0.048 0.041
(0.099) (0.097) (0.097) (0.099) (0.097) (0.097) (0.098) (0.097) (0.097) (0.098) (0.097) (0.097)
Black 0.001*** 0.0003*** 0.0003*** 0.001*** 0.0003*** 0.0003*** 0.0004*** 0.0003*** 0.0003*** 0.0004*** 0.0003*** 0.0003***
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Unknown Race -0.022*** -0.018*** -0.018*** -0.018*** -0.017*** -0.017*** -0.019*** -0.018*** -0.018***
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Asian 0.008 0.016** 0.016** 0.013* 0.017** 0.017** 0.013* 0.017** 0.017**
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Indian -0.022* -0.015 -0.015 -0.020* -0.014 -0.014 -0.020* -0.014 -0.015
(0.012) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011)
Steryotypicall black 0.004 0.016 0.014 0.011 0.018 0.016 0.011 0.017 0.015
(0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024)
Skin-tone 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Attractiveness -0.205*** -0.199*** -0.199*** -0.173*** -0.188*** -0.188*** -0.175*** -0.189*** -0.190***
(0.055) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054)
Competence -0.006*** 0.001 0.0005 -0.005*** 0.001 0.001
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Dominance -0.009*** -0.006*** -0.006*** -0.009*** -0.006*** -0.006***
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Trustworthiness 0.004*** 0.004*** 0.004*** 0.003*** 0.003*** 0.003***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Human Guess -0.005*** -0.003* -0.003* -0.004*** -0.003 -0.003
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
detention_likely 0.034*** 0.030*** 0.030***
(0.007) (0.007) (0.007)
Constant 0.268*** 0.334*** 0.362*** 0.150*** 0.237*** 0.252*** 0.149*** 0.235*** 0.250*** 0.218*** 0.240*** 0.255*** 0.199*** 0.223*** 0.238***
(0.005) (0.005) (0.008) (0.006) (0.006) (0.008) (0.007) (0.007) (0.009) (0.009) (0.008) (0.010) (0.010) (0.009) (0.010)
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.001 0.025 0.027 0.199 0.225 0.226 0.202 0.229 0.229 0.218 0.231 0.232 0.220 0.233 0.234
Note: p<0.1; p<0.05; p<0.01

Regressing on the detention outcome:

Does fat-faced explain the actual detention outcome?

Table 5.1 - Fat Faced & Well-Groomed:
Testing the algorithmically-generated hypothesis: Does fat-faced predict judge decisions?
Dependent variable:
Judge Detain Decision
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Fat-faced -0.021*** -0.020*** -0.019*** -0.018*** -0.020*** -0.019*** -0.019*** -0.019*** -0.010*** -0.010***
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Well-groomed -0.020*** -0.019*** -0.024*** -0.023*** -0.024*** -0.022*** -0.013** -0.011** -0.003 -0.003
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) (0.005) (0.005) (0.005)
Male 0.100*** 0.105*** 0.103*** 0.095*** 0.100*** 0.096*** 0.091*** 0.096*** 0.092*** 0.025** 0.025** 0.025**
(0.010) (0.010) (0.010) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.012) (0.012) (0.012)
Age Arrest -0.152 -0.162 -0.167 -0.156 -0.165 -0.169 -0.155 -0.163 -0.164 -0.190 -0.193 -0.192
(0.420) (0.420) (0.420) (0.420) (0.420) (0.420) (0.419) (0.419) (0.419) (0.415) (0.415) (0.415)
Black -0.001 -0.001*** -0.001*** -0.001 -0.001*** -0.001** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001***
(0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004)
Unknown Race -0.083*** -0.072*** -0.079*** -0.077*** -0.070*** -0.077*** -0.063*** -0.060*** -0.063***
(0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.021) (0.021) (0.021)
Asian 0.002 0.009 0.013 0.011 0.010 0.014 0.001 -0.0002 0.002
(0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031)
Indian -0.080 -0.072 -0.072 -0.075 -0.071 -0.071 -0.063 -0.062 -0.062
(0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.048) (0.049) (0.048)
Stereotypical Black 0.033 0.064 0.048 0.048 0.067 0.051 0.047 0.056 0.048
(0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.101) (0.101) (0.101)
Skin-tone 0.013*** 0.011*** 0.013*** 0.012*** 0.011*** 0.012*** 0.009** 0.009** 0.009**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Attractiveness -0.340 -0.321 -0.332 -0.288 -0.285 -0.298 -0.176 -0.168 -0.179
(0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.231) (0.231) (0.231)
Competence -0.007 0.001 -0.002 -0.002 0.0003 -0.001
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Dominance -0.020*** -0.018** -0.018** -0.015** -0.014* -0.014**
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Trustworthiness 0.010* 0.008 0.010* 0.007 0.006 0.007
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Human Guess -0.009 -0.011 -0.008 -0.008 -0.009 -0.008
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
ML-Face 0.118*** 0.118*** 0.115*** 0.099*** 0.099*** 0.098***
(0.029) (0.029) (0.029) (0.029) (0.029) (0.029)
p_hat_cnn 0.599*** 0.617*** 0.596***
(0.044) (0.044) (0.044)
Constant 0.342*** 0.329*** 0.429*** 0.273*** 0.303*** 0.386*** 0.277*** 0.303*** 0.387*** 0.321*** 0.262*** 0.345*** 0.167*** 0.124*** 0.174***
(0.020) (0.021) (0.028) (0.024) (0.027) (0.032) (0.028) (0.031) (0.035) (0.042) (0.040) (0.043) (0.043) (0.041) (0.044)
Naive-AUC 0.54 0.531 0.55 0.572 0.571 0.579 0.578 0.576 0.584 0.595 0.59 0.596 0.635 0.633 0.635
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.003 0.002 0.005 0.013 0.013 0.015 0.014 0.014 0.017 0.020 0.018 0.020 0.038 0.037 0.038
Note: p<0.1; p<0.05; p<0.01

Does facial-hair explain the actual detention outcome?

Table 5.2 - Facial hair & Well-Groomed:
Testing the algorithmically-generated hypothesis: Does fat-faced predict judge decisions?
Dependent variable:
Judge Detain Decision
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Facial-hair 0.011*** 0.010*** -0.001 -0.005* -0.001 -0.005* -0.002 -0.004 -0.001 -0.002
(0.002) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Well-groomed -0.020*** -0.016*** -0.024*** -0.026*** -0.024*** -0.026*** -0.013** -0.015*** -0.003 -0.004
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) (0.005) (0.005) (0.005)
Male 0.106*** 0.105*** 0.120*** 0.102*** 0.100*** 0.115*** 0.100*** 0.096*** 0.108*** 0.027* 0.025** 0.030**
(0.013) (0.010) (0.014) (0.013) (0.011) (0.014) (0.014) (0.011) (0.014) (0.014) (0.012) (0.015)
Age Arrest -0.144 -0.162 -0.155 -0.148 -0.165 -0.157 -0.150 -0.163 -0.157 -0.188 -0.193 -0.190
(0.421) (0.420) (0.420) (0.421) (0.420) (0.420) (0.420) (0.419) (0.419) (0.415) (0.415) (0.415)
Black -0.001* -0.001*** -0.001*** -0.001* -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001***
(0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004)
Unknown Race -0.076*** -0.072*** -0.071*** -0.071*** -0.070*** -0.070*** -0.060*** -0.060*** -0.059***
(0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.021) (0.021) (0.021)
Asian -0.003 0.009 0.009 0.006 0.010 0.010 -0.001 -0.0002 -0.0003
(0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031)
Indian -0.082* -0.072 -0.077 -0.078 -0.071 -0.074 -0.065 -0.062 -0.064
(0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049)
Stereotypical Black 0.049 0.064 0.064 0.063 0.067 0.067 0.055 0.056 0.056
(0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.101) (0.101) (0.101)
Skin-tone 0.012*** 0.011*** 0.012*** 0.011*** 0.011*** 0.011*** 0.009** 0.009** 0.009**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Attractiveness -0.328 -0.321 -0.315 -0.271 -0.285 -0.283 -0.163 -0.168 -0.168
(0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.231) (0.231) (0.231)
Competence -0.004 0.001 0.001 -0.001 0.0003 0.001
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Dominance -0.020*** -0.018** -0.017** -0.015** -0.014* -0.014*
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Trustworthiness 0.008 0.008 0.008 0.006 0.006 0.006
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Human Guess -0.012* -0.011 -0.011 -0.009 -0.009 -0.009
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
ML-Face 0.121*** 0.118*** 0.117*** 0.100*** 0.099*** 0.099***
(0.029) (0.029) (0.029) (0.029) (0.029) (0.029)
p_hat_cnn 0.621*** 0.617*** 0.616***
(0.043) (0.044) (0.044)
Constant 0.182*** 0.329*** 0.266*** 0.178*** 0.303*** 0.320*** 0.181*** 0.303*** 0.318*** 0.233*** 0.262*** 0.270*** 0.116*** 0.124*** 0.128***
(0.010) (0.021) (0.025) (0.015) (0.027) (0.029) (0.021) (0.031) (0.032) (0.038) (0.040) (0.040) (0.038) (0.041) (0.041)
Naive-AUC 0.536 0.531 0.542 0.558 0.571 0.573 0.57 0.576 0.578 0.589 0.59 0.591 0.634 0.633 0.634
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.003 0.002 0.004 0.010 0.013 0.013 0.011 0.014 0.014 0.017 0.018 0.018 0.037 0.037 0.037
Note: p<0.1; p<0.05; p<0.01

Does eye-bags explain the actual detention outcome?

Table 5.3 - Eye-bags & Well-Groomed:
Testing the algorithmically-generated hypothesis: Does fat-faced predict judge decisions?
Dependent variable:
Judge Detain Decision
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Eye-bags 0.003 0.001 0.008* 0.007 0.008* 0.006 0.006 0.006 0.008** 0.008**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Well-groomed -0.020*** -0.020*** -0.024*** -0.024*** -0.024*** -0.023*** -0.013** -0.013** -0.003 -0.003
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) (0.005) (0.005) (0.005)
Male 0.104*** 0.105*** 0.106*** 0.099*** 0.100*** 0.101*** 0.096*** 0.096*** 0.097*** 0.025** 0.025** 0.026**
(0.010) (0.010) (0.010) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.012) (0.012) (0.012)
Age Arrest -0.127 -0.162 -0.146 -0.131 -0.165 -0.148 -0.137 -0.163 -0.148 -0.171 -0.193 -0.173
(0.421) (0.420) (0.420) (0.421) (0.420) (0.420) (0.420) (0.419) (0.420) (0.415) (0.415) (0.415)
Black -0.001** -0.001*** -0.001*** -0.001** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.002*** -0.001*** -0.002***
(0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004)
Unknown Race -0.076*** -0.072*** -0.072*** -0.071*** -0.070*** -0.070*** -0.059*** -0.060*** -0.059***
(0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.021) (0.021) (0.021)
Asian -0.002 0.009 0.009 0.007 0.010 0.010 -0.001 -0.0002 -0.0004
(0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031)
Indian -0.080 -0.072 -0.072 -0.075 -0.071 -0.071 -0.063 -0.062 -0.062
(0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.048) (0.049) (0.048)
Stereotypical Black 0.055 0.064 0.068 0.067 0.067 0.070 0.060 0.056 0.061
(0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.101) (0.101) (0.101)
Skin-tone 0.011*** 0.011*** 0.011*** 0.011*** 0.011*** 0.011*** 0.009** 0.009** 0.009**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Attractiveness -0.328 -0.321 -0.320 -0.272 -0.285 -0.284 -0.163 -0.168 -0.167
(0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.231) (0.231) (0.231)
Competence -0.004 0.001 0.001 -0.0004 0.0003 0.001
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Dominance -0.020*** -0.018** -0.018** -0.014** -0.014* -0.014*
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Trustworthiness 0.008 0.008 0.008 0.006 0.006 0.006
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Human Guess -0.012* -0.011 -0.011 -0.009 -0.009 -0.009
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
ML-Face 0.121*** 0.118*** 0.117*** 0.100*** 0.099*** 0.099***
(0.029) (0.029) (0.029) (0.029) (0.029) (0.029)
p_hat_cnn 0.623*** 0.617*** 0.620***
(0.043) (0.044) (0.044)
Constant 0.216*** 0.329*** 0.321*** 0.141*** 0.303*** 0.271*** 0.145*** 0.303*** 0.271*** 0.201*** 0.262*** 0.233*** 0.076* 0.124*** 0.085*
(0.021) (0.021) (0.031) (0.024) (0.027) (0.034) (0.028) (0.031) (0.037) (0.043) (0.040) (0.044) (0.043) (0.041) (0.045)
Naive-AUC 0.504 0.531 0.532 0.563 0.571 0.573 0.573 0.576 0.577 0.59 0.59 0.591 0.634 0.633 0.634
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 -0.00003 0.002 0.002 0.010 0.013 0.013 0.011 0.014 0.014 0.017 0.018 0.018 0.038 0.037 0.038
Note: p<0.1; p<0.05; p<0.01

Checking composite feature of tired and eye-bags

Table 4.3 V2 - Repeating table 4.3 with the mean of eye-bags and tired
Correlation between human-labeled novel feature and algorithms prediction
Dependent variable:
Algorithmic Prediction
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Mean(Eye, Tired) 0.001 -0.004** 0.003* -0.001 0.002* -0.001 -0.001 -0.002 -0.001 -0.002
(0.002) (0.002) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Well-groomed -0.017*** -0.018*** -0.018*** -0.018*** -0.018*** -0.018*** -0.016*** -0.016*** -0.015*** -0.015***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Male 0.119*** 0.120*** 0.120*** 0.116*** 0.117*** 0.117*** 0.114*** 0.115*** 0.115*** 0.114*** 0.116*** 0.115***
(0.002) (0.002) (0.002) (0.003) (0.002) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Age 0.060 0.044 0.042 0.062 0.048 0.046 0.060 0.048 0.045 0.059 0.048 0.045
(0.099) (0.097) (0.098) (0.099) (0.097) (0.097) (0.098) (0.097) (0.097) (0.098) (0.097) (0.097)
Black 0.001*** 0.0003*** 0.0003*** 0.001*** 0.0003*** 0.0003*** 0.0003*** 0.0003*** 0.0003*** 0.0003*** 0.0003*** 0.0003***
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Unknown Race -0.021*** -0.018*** -0.018*** -0.018*** -0.017*** -0.017*** -0.018*** -0.018*** -0.018***
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Asian 0.008 0.016** 0.016** 0.013* 0.017** 0.017** 0.013* 0.017** 0.017**
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Indian -0.021* -0.015 -0.015 -0.020* -0.014 -0.014 -0.020* -0.014 -0.014
(0.012) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011)
Steryotypicall black 0.007 0.016 0.016 0.013 0.018 0.017 0.012 0.017 0.016
(0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024) (0.024)
Skin-tone 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004*** 0.004***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Attractiveness -0.205*** -0.199*** -0.199*** -0.173*** -0.188*** -0.187*** -0.175*** -0.189*** -0.189***
(0.055) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.054)
Competence -0.005*** 0.001 0.001 -0.005*** 0.001 0.001
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Dominance -0.009*** -0.006*** -0.006*** -0.009*** -0.006*** -0.006***
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Trustworthiness 0.004*** 0.004*** 0.004*** 0.003*** 0.003*** 0.003***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Human Guess -0.005*** -0.003* -0.003* -0.004*** -0.003 -0.003
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
detention_likely 0.034*** 0.030*** 0.030***
(0.007) (0.007) (0.007)
Constant 0.248*** 0.334*** 0.356*** 0.130*** 0.237*** 0.243*** 0.130*** 0.235*** 0.242*** 0.207*** 0.240*** 0.250*** 0.190*** 0.223*** 0.234***
(0.008) (0.005) (0.010) (0.007) (0.006) (0.010) (0.008) (0.007) (0.010) (0.011) (0.008) (0.011) (0.011) (0.009) (0.012)
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 -0.0001 0.025 0.025 0.199 0.225 0.225 0.202 0.229 0.229 0.218 0.231 0.232 0.220 0.233 0.233
Note: p<0.1; p<0.05; p<0.01
Table 5.3 V2 - Repeating table 5.3 with the mean of eye-bags and tired
Testing the algorithmically-generated hypothesis: Does fat-faced predict judge decisions?
Dependent variable:
Judge Detain Decision
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15)
Mean(Eye, Tired) 0.005 0.0002 0.013** 0.009 0.013** 0.009 0.007 0.006 0.007 0.007
(0.006) (0.006) (0.006) (0.006) (0.006) (0.006) (0.006) (0.006) (0.006) (0.006)
Well-groomed -0.020*** -0.020*** -0.024*** -0.023*** -0.024*** -0.023*** -0.013** -0.012** -0.003 -0.003
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) (0.005) (0.005) (0.005)
Male 0.104*** 0.105*** 0.106*** 0.100*** 0.100*** 0.101*** 0.096*** 0.096*** 0.097*** 0.025** 0.025** 0.026**
(0.010) (0.010) (0.010) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.012) (0.012) (0.012)
Age Arrest -0.126 -0.162 -0.149 -0.131 -0.165 -0.152 -0.143 -0.163 -0.154 -0.179 -0.193 -0.182
(0.421) (0.420) (0.420) (0.421) (0.420) (0.420) (0.420) (0.419) (0.420) (0.415) (0.415) (0.415)
Black -0.001** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.001*** -0.002*** -0.001*** -0.002***
(0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004)
Unknown Race -0.076*** -0.072*** -0.072*** -0.071*** -0.070*** -0.070*** -0.059*** -0.060*** -0.059***
(0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.021) (0.021) (0.021)
Asian -0.002 0.009 0.009 0.006 0.010 0.010 -0.001 -0.0002 -0.001
(0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031)
Indian -0.080 -0.072 -0.072 -0.075 -0.071 -0.071 -0.063 -0.062 -0.062
(0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.048) (0.049) (0.049)
Stereotypical Black 0.057 0.064 0.068 0.067 0.067 0.070 0.059 0.056 0.060
(0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.101) (0.101) (0.101)
Skin-tone 0.011*** 0.011*** 0.011*** 0.011*** 0.011*** 0.011*** 0.009** 0.009** 0.009**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Attractiveness -0.330 -0.321 -0.322 -0.275 -0.285 -0.286 -0.166 -0.168 -0.170
(0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.231) (0.231) (0.231)
Competence -0.004 0.001 0.001 -0.0004 0.0003 0.001
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Dominance -0.020*** -0.018** -0.018** -0.014** -0.014* -0.014*
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Trustworthiness 0.008 0.008 0.008 0.006 0.006 0.006
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Human Guess -0.012* -0.011 -0.011 -0.009 -0.009 -0.009
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
ML-Face 0.120*** 0.118*** 0.117*** 0.099*** 0.099*** 0.099***
(0.029) (0.029) (0.029) (0.029) (0.029) (0.029)
p_hat_cnn 0.621*** 0.617*** 0.618***
(0.043) (0.044) (0.044)
Constant 0.206*** 0.329*** 0.328*** 0.115*** 0.303*** 0.258*** 0.120*** 0.303*** 0.259*** 0.196*** 0.262*** 0.232*** 0.078 0.124*** 0.087*
(0.030) (0.021) (0.040) (0.031) (0.027) (0.041) (0.035) (0.031) (0.044) (0.049) (0.040) (0.051) (0.049) (0.041) (0.051)
Naive-AUC 0.504 0.531 0.531 0.563 0.571 0.572 0.571 0.576 0.577 0.589 0.59 0.591 0.633 0.633 0.633
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 -0.00001 0.002 0.002 0.010 0.013 0.013 0.012 0.014 0.014 0.017 0.018 0.018 0.038 0.037 0.037
Note: p<0.1; p<0.05; p<0.01

Checking whether height and weight matter for fat-faced

Scatter plot of weight and fat-faced

Fitting smooth-spline of height on weight to produce weight-hat

## integer(0)

Regression of weight, height, weight-hat and other covariates on fat-faced

How much of the fat-faced label can we explain with potential covariates?
Dependent variable:
Fat-faced label
(1) (2) (3) (4) (5) (6) (7)
Well-gromed 0.052***
(0.012)
Weight 0.015***
(0.0003)
Height -0.017**
(0.008)
Weight-hat -0.008*
(0.004)
Attractiveness -0.055*** -0.169***
(0.013) (0.017)
Competence 0.041*** 0.018
(0.013) (0.020)
Dominance 0.083*** 0.099***
(0.013) (0.014)
Trustworthiness 0.070*** 0.156***
(0.014) (0.019)
Constant 4.898*** 6.884*** 5.356*** 4.991*** 4.793*** 4.920*** 4.802***
(0.057) (0.663) (0.051) (0.051) (0.054) (0.047) (0.070)
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.002 0.206 0.002 0.001 0.004 0.002 0.017
Note: p<0.1; p<0.05; p<0.01

Regressing fat-faced, weight, height, weight-hat and well-groomed on ML-Face:

Correlation between human-labeled novel feature and algorithms prediction
Dependent variable:
Algorithmic Prediction
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19)
Fat-faced -0.016*** -0.015*** -0.011*** -0.010*** -0.010*** -0.009*** -0.010*** -0.009*** -0.010*** -0.009*** -0.010*** -0.009***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Well-groomed -0.017*** -0.016*** -0.017*** -0.016*** -0.018*** -0.017*** -0.018*** -0.017*** -0.014*** -0.014*** -0.014*** -0.014***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Weight -0.0005*** -0.0003*** -0.0005*** -0.0003*** -0.0004*** -0.001*** -0.0004*** -0.0004*** -0.001*** -0.0004*** -0.0004*** -0.001*** -0.0004*** -0.0004*** -0.001*** -0.0004***
(0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003) (0.00003)
Height 0.013*** 0.013*** 0.013*** 0.013*** 0.002** 0.002** 0.002** 0.001* 0.001* 0.001* 0.001* 0.001* 0.001* 0.001* 0.001* 0.001*
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Weight-hat -0.005*** -0.005*** -0.005*** -0.005*** -0.001* -0.001 -0.001* -0.001 -0.0005 -0.001 -0.001 -0.0004 -0.001 -0.001 -0.0004 -0.001
(0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004)
Male 0.120*** 0.123*** 0.122*** 0.116*** 0.119*** 0.118*** 0.114*** 0.118*** 0.116*** 0.114*** 0.118*** 0.117***
(0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Age 0.059 0.052 0.050 0.065 0.059 0.057 0.071 0.063 0.062 0.071 0.063 0.062
(0.097) (0.096) (0.095) (0.097) (0.096) (0.095) (0.095) (0.095) (0.095) (0.095) (0.095) (0.095)
Black 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001*** 0.001***
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Unknown Race -0.027*** -0.021*** -0.023*** -0.023*** -0.020*** -0.022*** -0.023*** -0.020*** -0.022***
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Asian 0.010 0.017** 0.018** 0.015** 0.017** 0.018*** 0.015** 0.017** 0.018**
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Indian -0.027** -0.023** -0.021* -0.025** -0.022** -0.020* -0.025** -0.022** -0.021*
(0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) (0.011)
Steryotypicall black -0.008 0.009 0.003 0.0001 0.011 0.005 -0.0003 0.011 0.004
(0.024) (0.023) (0.023) (0.023) (0.023) (0.023) (0.023) (0.023) (0.023)
Skin-tone 0.006*** 0.005*** 0.006*** 0.005*** 0.005*** 0.005*** 0.005*** 0.005*** 0.005***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Attractiveness -0.223*** -0.216*** -0.218*** -0.197*** -0.207*** -0.210*** -0.198*** -0.209*** -0.211***
(0.054) (0.053) (0.053) (0.053) (0.053) (0.053) (0.053) (0.053) (0.053)
Competence -0.009*** -0.003** -0.004** -0.009*** -0.003** -0.004**
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Dominance -0.009*** -0.006*** -0.006*** -0.008*** -0.006*** -0.006***
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Trustworthiness 0.006*** 0.006*** 0.006*** 0.006*** 0.006*** 0.006***
(0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
Human Guess -0.002 -0.001 -0.0002 -0.002 -0.001 -0.00003
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
detention_likely 0.028*** 0.025*** 0.025***
(0.007) (0.007) (0.007)
Constant 0.334*** 0.334*** 0.409*** -1.056*** -0.981*** -0.981*** -0.915*** 0.073 0.124* 0.176*** 0.089 0.136** 0.187*** 0.154** 0.143** 0.194*** 0.143** 0.132* 0.183***
(0.005) (0.005) (0.007) (0.067) (0.067) (0.067) (0.067) (0.068) (0.067) (0.067) (0.068) (0.068) (0.067) (0.068) (0.068) (0.067) (0.068) (0.068) (0.067)
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.028 0.025 0.050 0.097 0.107 0.121 0.129 0.235 0.251 0.258 0.241 0.257 0.264 0.257 0.261 0.268 0.259 0.262 0.269
Note: p<0.1; p<0.05; p<0.01

Regressing fat-faced, weight, height, weight-hat and well-groomed on Detention:

Testing the algorithmically-generated hypothesis: Does fat-faced predict judge decisions?
Dependent variable:
Judge Detain Decision
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22)
Fat-faced -0.021*** -0.020*** -0.016*** -0.015*** -0.015*** -0.014*** -0.015*** -0.014*** -0.015*** -0.014*** -0.014*** -0.014*** -0.009** -0.009**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Well-groomed -0.020*** -0.019*** -0.020*** -0.019*** -0.024*** -0.023*** -0.023*** -0.023*** -0.013** -0.012** -0.012** -0.011** -0.004 -0.003
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Weight -0.001*** -0.0004*** -0.001*** -0.0004*** -0.0004** -0.001*** -0.0004** -0.0004*** -0.001*** -0.0004*** -0.0004*** -0.001*** -0.0004*** -0.0004*** -0.001*** -0.0004*** -0.0002 -0.0003** -0.0002
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Height 0.016*** 0.016*** 0.016*** 0.016*** 0.005 0.005 0.005 0.005 0.005 0.004 0.004 0.004 0.004 0.004 0.004 0.004 0.003 0.003 0.003
(0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) (0.003)
Weight-hat -0.007*** -0.007*** -0.007*** -0.008*** -0.003* -0.003 -0.003* -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.003 -0.002 -0.002 -0.002
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Male 0.115*** 0.120*** 0.119*** 0.110*** 0.115*** 0.113*** 0.107*** 0.111*** 0.109*** 0.108*** 0.111*** 0.109*** 0.040*** 0.041*** 0.041***
(0.013) (0.013) (0.013) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) (0.015) (0.015)
Age Arrest -0.117 -0.127 -0.129 -0.118 -0.127 -0.130 -0.113 -0.119 -0.121 -0.113 -0.119 -0.121 -0.155 -0.156 -0.157
(0.420) (0.420) (0.420) (0.420) (0.420) (0.419) (0.419) (0.419) (0.419) (0.419) (0.419) (0.419) (0.415) (0.415) (0.415)
Black -0.0003 -0.001* -0.001* -0.0003 -0.001* -0.001* -0.001** -0.001** -0.001** -0.001** -0.001** -0.001** -0.001*** -0.001*** -0.001***
(0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004) (0.0004)
Unknown Race -0.080*** -0.072*** -0.076*** -0.073*** -0.069*** -0.072*** -0.074*** -0.070*** -0.073*** -0.060*** -0.058*** -0.060***
(0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022) (0.022)
Asian -0.005 0.004 0.006 0.005 0.006 0.007 0.004 0.005 0.006 -0.005 -0.005 -0.004
(0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031) (0.031)
Indian -0.093* -0.088* -0.086* -0.088* -0.087* -0.084* -0.089* -0.088* -0.085* -0.074 -0.074 -0.073
(0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049) (0.049)
Stereotypical Black 0.026 0.050 0.040 0.042 0.056 0.046 0.041 0.054 0.044 0.041 0.048 0.042
(0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.102) (0.101) (0.101) (0.101)
Skin-tone 0.013*** 0.012*** 0.013*** 0.012*** 0.011*** 0.012*** 0.012*** 0.012*** 0.012*** 0.009** 0.009** 0.009**
(0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004)
Attractiveness -0.355 -0.346 -0.347 -0.298 -0.306 -0.309 -0.305 -0.312 -0.315 -0.188 -0.188 -0.192
(0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.233) (0.231) (0.231) (0.231)
Competence -0.010 -0.004 -0.005 -0.009 -0.004 -0.004 -0.003 -0.002 -0.002
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Dominance -0.020*** -0.018** -0.018** -0.019*** -0.017** -0.017** -0.014** -0.014* -0.014*
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
Trustworthiness 0.013** 0.012** 0.013** 0.012** 0.011** 0.012** 0.008 0.008 0.008
(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Human Guess -0.010 -0.010 -0.009 -0.009 -0.009 -0.008 -0.009 -0.009 -0.008
(0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)
ML-Face 0.115*** 0.113*** 0.112*** 0.098*** 0.098*** 0.097***
(0.029) (0.029) (0.029) (0.029) (0.029) (0.029)
p_hat_cnn 0.588*** 0.594*** 0.584***
(0.044) (0.045) (0.045)
Constant 0.342*** 0.329*** 0.429*** -1.197*** -1.089*** -1.108*** -1.012*** -0.038 0.022 0.100 0.001 0.050 0.129 0.133 0.091 0.168 0.085 0.042 0.118 0.001 -0.037 0.011
(0.020) (0.021) (0.028) (0.270) (0.271) (0.270) (0.271) (0.296) (0.296) (0.296) (0.297) (0.297) (0.298) (0.298) (0.297) (0.298) (0.298) (0.297) (0.298) (0.295) (0.295) (0.295)
Naive-AUC 0.54 0.531 0.55 0.552 0.558 0.56 0.565 0.58 0.584 0.586 0.586 0.589 0.592 0.597 0.596 0.598 0.602 0.6 0.603 0.637 0.636 0.637
Observations 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603 9,603
Adjusted R2 0.003 0.002 0.005 0.005 0.007 0.008 0.009 0.014 0.016 0.017 0.016 0.017 0.018 0.020 0.019 0.020 0.021 0.021 0.022 0.039 0.038 0.039
Note: p<0.1; p<0.05; p<0.01