Baseline Regression - Increase MTurk Detail
We repeat our baseline regressions with the increased MTurk detail as seen below. We split these by gender.
Multihead(ResNet50)
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Dependent variable:
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Release Outcome
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(1)
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(2)
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(3)
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(4)
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(5)
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risk_pred_prob
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-1.105***
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-1.107***
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-1.106***
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-0.778***
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-0.713***
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(-1.211, -0.998)
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(-1.215, -1.000)
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(-1.214, -0.999)
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(-0.883, -0.673)
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(-0.818, -0.608)
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skin_tonenumber_f7ddc4
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0.002
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0.002
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-0.027
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-0.041**
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(-0.033, 0.037)
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(-0.033, 0.038)
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(-0.061, 0.007)
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(-0.075, -0.007)
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age
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-0.0003
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0.0003
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0.001*
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(-0.001, 0.001)
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(-0.001, 0.001)
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(0.00004, 0.002)
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attractiveness
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-0.002
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0.001
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0.002
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(-0.012, 0.008)
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(-0.009, 0.010)
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(-0.008, 0.012)
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competence
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0.003
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-0.001
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-0.003
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(-0.009, 0.015)
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(-0.013, 0.010)
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(-0.014, 0.008)
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dominance
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0.001
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0.005
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0.006
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(-0.008, 0.009)
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(-0.003, 0.012)
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(-0.001, 0.014)
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trustworthiness
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0.001
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0.001
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-0.002
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(-0.010, 0.011)
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(-0.009, 0.011)
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(-0.012, 0.008)
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p_hat_covariates
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1.083***
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1.005***
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(1.018, 1.148)
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(0.939, 1.071)
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p_hat_cnn
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0.403***
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(0.336, 0.470)
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Constant
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1.102***
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1.088***
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1.088***
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0.114**
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-0.161***
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(1.069, 1.136)
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(1.045, 1.131)
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(1.017, 1.158)
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(0.024, 0.203)
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(-0.261, -0.061)
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Observations
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8,479
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8,479
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8,479
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8,479
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8,479
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Adjusted R2
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0.033
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0.033
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0.033
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0.112
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0.122
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F Statistic
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291.841*** (df = 1; 8477)
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17.216*** (df = 18; 8460)
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13.490*** (df = 23; 8455)
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45.641*** (df = 24; 8454)
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48.180*** (df = 25; 8453)
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Note:
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p<0.1; p<0.05; p<0.01
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Gender Split
Female Subsample:
Multihead(ResNet50)
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Dependent variable:
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Release Outcome
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(1)
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(2)
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(3)
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(4)
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(5)
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risk_pred_prob
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-0.966***
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-0.946***
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-0.916***
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-0.679***
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-0.618***
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(-1.232, -0.700)
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(-1.214, -0.678)
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(-1.185, -0.647)
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(-0.942, -0.416)
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(-0.879, -0.357)
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skin_tonenumber_f7ddc4
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-0.071
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-0.077*
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-0.085*
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-0.050
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(-0.144, 0.003)
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(-0.150, -0.003)
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(-0.157, -0.013)
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(-0.122, 0.021)
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age
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-0.002
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-0.001
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-0.0003
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(-0.004, 0.0002)
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(-0.003, 0.001)
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(-0.002, 0.002)
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attractiveness
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0.012
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0.012
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0.011
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(-0.006, 0.031)
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(-0.006, 0.030)
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(-0.007, 0.029)
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competence
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-0.012
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-0.014
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-0.017
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(-0.034, 0.009)
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(-0.035, 0.007)
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(-0.038, 0.004)
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dominance
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0.019**
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0.016*
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0.016*
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(0.003, 0.034)
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(0.001, 0.031)
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(0.001, 0.031)
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trustworthiness
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0.004
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0.005
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0.002
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(-0.015, 0.024)
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(-0.014, 0.024)
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(-0.017, 0.020)
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p_hat_covariates
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1.140***
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1.124***
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(0.969, 1.311)
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(0.954, 1.293)
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p_hat_cnn
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0.582***
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(0.417, 0.747)
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Constant
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1.118***
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1.145***
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1.095***
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0.043
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-0.450***
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(1.041, 1.195)
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(1.046, 1.244)
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(0.951, 1.239)
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(-0.168, 0.254)
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(-0.701, -0.198)
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Observations
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1,833
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1,833
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1,833
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1,833
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1,833
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Adjusted R2
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0.019
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0.022
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0.026
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0.086
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0.102
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F Statistic
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35.610*** (df = 1; 1831)
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3.239*** (df = 18; 1814)
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3.113*** (df = 23; 1809)
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8.192*** (df = 24; 1808)
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9.355*** (df = 25; 1807)
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Note:
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p<0.1; p<0.05; p<0.01
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Male Subsample:
Multihead(ResNet50)
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Dependent variable:
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Release Outcome
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(1)
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(2)
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(3)
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(4)
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(5)
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risk_pred_prob
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-1.039***
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-1.043***
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-1.048***
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-0.791***
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-0.749***
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(-1.158, -0.920)
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(-1.163, -0.923)
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(-1.168, -0.928)
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(-0.908, -0.674)
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(-0.865, -0.633)
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skin_tonenumber_f7ddc4
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0.001
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0.003
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-0.013
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-0.033
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(-0.040, 0.043)
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(-0.039, 0.045)
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(-0.053, 0.027)
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(-0.073, 0.007)
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age
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0.001
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0.001
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0.001*
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(-0.001, 0.002)
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(-0.001, 0.002)
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(0.0001, 0.002)
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attractiveness
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-0.006
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-0.002
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-0.0001
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(-0.018, 0.005)
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(-0.013, 0.010)
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(-0.011, 0.011)
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competence
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0.005
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0.001
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0.001
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(-0.008, 0.019)
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(-0.012, 0.015)
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(-0.012, 0.014)
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dominance
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0.002
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0.0004
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-0.001
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(-0.008, 0.012)
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(-0.009, 0.010)
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(-0.010, 0.009)
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trustworthiness
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-0.003
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-0.0005
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-0.002
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(-0.015, 0.010)
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(-0.012, 0.011)
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(-0.014, 0.010)
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p_hat_covariates
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1.086***
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1.043***
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(1.011, 1.160)
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(0.968, 1.117)
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p_hat_cnn
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0.467***
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(0.385, 0.549)
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Constant
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1.066***
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1.053***
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1.041***
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0.130**
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-0.197***
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(1.028, 1.105)
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(1.005, 1.101)
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(0.959, 1.124)
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(0.029, 0.231)
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(-0.313, -0.082)
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Observations
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6,646
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6,646
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6,646
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6,646
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6,646
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Adjusted R2
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0.030
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0.030
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0.029
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0.107
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0.118
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F Statistic
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206.526*** (df = 1; 6644)
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12.312*** (df = 18; 6627)
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9.751*** (df = 23; 6622)
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34.077*** (df = 24; 6621)
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36.641*** (df = 25; 6620)
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Note:
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p<0.1; p<0.05; p<0.01
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Label regressions
We now regress the individual, and combined, MTurk label on the release outcome. These are;
- Attractiveness
- Competence
- Dominance
- Trustworthiness
We split these regressions by: gender and race.
Combined Male-Female
Multihead(ResNet50)
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Dependent variable:
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Release Outcome
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(1)
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(2)
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(3)
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(4)
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(5)
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attractiveness
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0.005
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0.003
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(-0.001, 0.012)
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(-0.006, 0.013)
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competence
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0.005
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0.003
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(-0.002, 0.013)
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(-0.009, 0.015)
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dominance
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-0.002
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-0.006
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(-0.009, 0.006)
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(-0.014, 0.003)
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trustworthiness
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0.006
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0.003
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(-0.001, 0.012)
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(-0.008, 0.013)
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Constant
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0.737***
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0.735***
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0.770***
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0.735***
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0.745***
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(0.706, 0.769)
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(0.697, 0.773)
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(0.732, 0.808)
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(0.702, 0.768)
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(0.700, 0.790)
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Observations
|
8,479
|
8,479
|
8,479
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8,479
|
8,479
|
|
Adjusted R2
|
0.0001
|
0.00004
|
-0.0001
|
0.0001
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-0.0001
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F Statistic
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1.654 (df = 1; 8477)
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1.351 (df = 1; 8477)
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0.141 (df = 1; 8477)
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1.893 (df = 1; 8477)
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0.838 (df = 4; 8474)
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Note:
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p<0.1; p<0.05; p<0.01
|
Subsample Female
Multihead(ResNet50)
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Dependent variable:
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Release Outcome
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(1)
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(2)
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(3)
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(4)
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(5)
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(6)
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attractiveness
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0.019***
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0.016
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0.013*
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(0.007, 0.030)
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(-0.001, 0.033)
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(0.0005, 0.026)
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competence
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|
0.014*
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-0.010
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(0.001, 0.027)
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(-0.032, 0.011)
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dominance
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0.021***
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|
0.016*
|
0.014
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(0.008, 0.034)
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(0.001, 0.032)
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(-0.0004, 0.028)
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trustworthiness
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|
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0.015**
|
0.004
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(0.003, 0.027)
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(-0.016, 0.023)
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|
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Constant
|
0.753***
|
0.772***
|
0.741***
|
0.770***
|
0.720***
|
0.710***
|
|
|
(0.696, 0.809)
|
(0.704, 0.839)
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(0.676, 0.806)
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(0.710, 0.831)
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(0.643, 0.796)
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(0.639, 0.782)
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|
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|
|
|
|
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|
Observations
|
1,833
|
1,833
|
1,833
|
1,833
|
1,833
|
1,833
|
|
Adjusted R2
|
0.003
|
0.001
|
0.003
|
0.002
|
0.004
|
0.004
|
|
F Statistic
|
7.370*** (df = 1; 1831)
|
3.162* (df = 1; 1831)
|
7.024*** (df = 1; 1831)
|
4.116** (df = 1; 1831)
|
2.639** (df = 4; 1828)
|
4.969*** (df = 2; 1830)
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Note:
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p<0.1; p<0.05; p<0.01
|
Subsample Male
Multihead(ResNet50)
|
|
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|
Dependent variable:
|
|
|
|
|
|
Release Outcome
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
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|
attractiveness
|
-0.001
|
|
|
|
-0.004
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|
|
(-0.009, 0.007)
|
|
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|
(-0.015, 0.007)
|
|
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|
|
|
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|
competence
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|
0.002
|
|
|
0.005
|
|
|
|
(-0.007, 0.011)
|
|
|
(-0.008, 0.019)
|
|
|
|
|
|
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dominance
|
|
|
-0.001
|
|
-0.001
|
|
|
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(-0.009, 0.008)
|
|
(-0.011, 0.008)
|
|
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|
|
|
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|
trustworthiness
|
|
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|
0.001
|
0.0003
|
|
|
|
|
|
(-0.007, 0.008)
|
(-0.012, 0.013)
|
|
|
|
|
|
|
|
|
Constant
|
0.745***
|
0.729***
|
0.743***
|
0.737***
|
0.737***
|
|
|
(0.708, 0.782)
|
(0.684, 0.774)
|
(0.697, 0.789)
|
(0.698, 0.775)
|
(0.683, 0.791)
|
|
|
|
|
|
|
|
|
|
|
Observations
|
6,646
|
6,646
|
6,646
|
6,646
|
6,646
|
|
Adjusted R2
|
-0.0001
|
-0.0001
|
-0.0001
|
-0.0001
|
-0.001
|
|
F Statistic
|
0.072 (df = 1; 6644)
|
0.138 (df = 1; 6644)
|
0.019 (df = 1; 6644)
|
0.013 (df = 1; 6644)
|
0.162 (df = 4; 6641)
|
|
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
Subsample Black
Multihead(ResNet50)
|
|
|
|
Dependent variable:
|
|
|
|
|
|
Release Outcome
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
attractiveness
|
0.001
|
|
|
|
0.001
|
|
|
(-0.008, 0.010)
|
|
|
|
(-0.012, 0.015)
|
|
|
|
|
|
|
|
|
competence
|
|
0.003
|
|
|
0.007
|
|
|
|
(-0.007, 0.013)
|
|
|
(-0.008, 0.023)
|
|
|
|
|
|
|
|
|
dominance
|
|
|
-0.004
|
|
-0.007
|
|
|
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|
(-0.014, 0.006)
|
|
(-0.018, 0.004)
|
|
|
|
|
|
|
|
|
trustworthiness
|
|
|
|
0.001
|
-0.003
|
|
|
|
|
|
(-0.008, 0.010)
|
(-0.017, 0.011)
|
|
|
|
|
|
|
|
|
Constant
|
0.755***
|
0.746***
|
0.781***
|
0.756***
|
0.767***
|
|
|
(0.712, 0.797)
|
(0.695, 0.797)
|
(0.729, 0.833)
|
(0.712, 0.799)
|
(0.705, 0.828)
|
|
|
|
|
|
|
|
|
|
|
Observations
|
4,768
|
4,768
|
4,768
|
4,768
|
4,768
|
|
Adjusted R2
|
-0.0002
|
-0.0002
|
-0.0001
|
-0.0002
|
-0.001
|
|
F Statistic
|
0.044 (df = 1; 4766)
|
0.222 (df = 1; 4766)
|
0.450 (df = 1; 4766)
|
0.025 (df = 1; 4766)
|
0.327 (df = 4; 4763)
|
|
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
Subsample Not-Black
Multihead(ResNet50)
|
|
|
|
Dependent variable:
|
|
|
|
|
|
Release Outcome
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
|
|
|
attractiveness
|
0.010
|
|
|
|
0.006
|
|
|
(-0.0002, 0.019)
|
|
|
|
(-0.009, 0.021)
|
|
|
|
|
|
|
|
|
competence
|
|
0.008
|
|
|
-0.002
|
|
|
|
(-0.003, 0.019)
|
|
|
(-0.020, 0.016)
|
|
|
|
|
|
|
|
|
dominance
|
|
|
0.001
|
|
-0.005
|
|
|
|
|
(-0.009, 0.012)
|
|
(-0.017, 0.008)
|
|
|
|
|
|
|
|
|
trustworthiness
|
|
|
|
0.011*
|
0.010
|
|
|
|
|
|
(0.001, 0.022)
|
(-0.006, 0.026)
|
|
|
|
|
|
|
|
|
Constant
|
0.716***
|
0.723***
|
0.756***
|
0.708***
|
0.719***
|
|
|
(0.667, 0.766)
|
(0.666, 0.781)
|
(0.700, 0.813)
|
(0.657, 0.759)
|
(0.653, 0.786)
|
|
|
|
|
|
|
|
|
|
|
Observations
|
3,711
|
3,711
|
3,711
|
3,711
|
3,711
|
|
Adjusted R2
|
0.0004
|
0.0001
|
-0.0003
|
0.001
|
0.00004
|
|
F Statistic
|
2.602 (df = 1; 3709)
|
1.377 (df = 1; 3709)
|
0.046 (df = 1; 3709)
|
3.398* (df = 1; 3709)
|
1.033 (df = 4; 3706)
|
|
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|