setwd("~/Google Drive/Research")
ra<-read.csv ("Robots_v_Algorithms_Prejudice_v2.csv", header=T, sep=",")
names(ra)
## [1] "V1" "V2" "V3"
## [4] "V4" "V5" "V6"
## [7] "V7" "V8" "V9"
## [10] "V10" "PROLIFIC_PID" "Prompt"
## [13] "theirs" "ours" "control"
## [16] "pan" "realistic_1" "realistic_3"
## [19] "realistic_4" "realistic_5" "realistic_9"
## [22] "symbolic_1" "symbolic_2" "symbolic_3"
## [25] "symbolic_8" "immpol1R" "immpol2"
## [28] "immpol3" "immpol4" "assoc_1"
## [31] "assoc_2" "assoc_3" "assoc_4"
## [34] "assoc_5" "assoc_6" "blur1"
## [37] "blur2" "blur3" "Gender"
## [40] "Age" "ID" "Politics"
## [43] "Income" "LocationLatitude" "LocationLongitude"
## [46] "LocationAccuracy" "X"
ra$cond[ra$theirs==1]<-"algorithm"
ra$cond[ra$ours==1]<-"robot"
ra$cond[ra$control==1]<-"acontrol"
ra$Rthreat<-(ra$realistic_1+ra$realistic_3+ra$realistic_5+ra$realistic_9)/4
ra$Sthreat<-(ra$symbolic_1+ra$symbolic_2+(8-ra$symbolic_3)+ra$symbolic_8)/4
ra$pol<-((8-ra$immpol1R) + ra$immpol2 + ra$immpol3 + ra$immpol4)/4
ra$blur<-(ra$blur1+ra$blur2+ra$blur3)/3
#support for restrictive immigration policies (bigger numbers = more restrictive)
summary(lm(pol~cond, ra))
##
## Call:
## lm(formula = pol ~ cond, data = ra)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.9549 -1.0095 -0.1146 0.7405 4.2405
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.86458 0.11660 24.567 <2e-16 ***
## condalgorithm 0.09033 0.16422 0.550 0.583
## condrobot -0.10504 0.16140 -0.651 0.516
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.277 on 370 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.003994, Adjusted R-squared: -0.00139
## F-statistic: 0.7419 on 2 and 370 DF, p-value: 0.4769
#panhumanism (overlapping circles)
summary(lm(pan~cond, ra))
##
## Call:
## lm(formula = pan ~ cond, data = ra)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.07500 -1.02963 -0.02963 0.97037 2.22951
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.07500 0.12253 33.258 <2e-16 ***
## condalgorithm -0.30451 0.17257 -1.765 0.0785 .
## condrobot -0.04537 0.16840 -0.269 0.7878
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.342 on 374 degrees of freedom
## Multiple R-squared: 0.009734, Adjusted R-squared: 0.004438
## F-statistic: 1.838 on 2 and 374 DF, p-value: 0.1606
#realistic threats from immigrants
summary(lm(Rthreat~cond, ra))
##
## Call:
## lm(formula = Rthreat ~ cond, data = ra)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.7625 -1.2377 -0.2625 0.9875 4.3796
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.7625 0.1338 20.650 <2e-16 ***
## condalgorithm -0.0248 0.1884 -0.132 0.895
## condrobot -0.1421 0.1839 -0.773 0.440
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.465 on 374 degrees of freedom
## Multiple R-squared: 0.001856, Adjusted R-squared: -0.003482
## F-statistic: 0.3477 on 2 and 374 DF, p-value: 0.7065
#symbolic threats from immigrants
summary(lm(Sthreat~cond, ra))
##
## Call:
## lm(formula = Sthreat ~ cond, data = ra)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.2971 -0.8778 -0.0471 0.7271 3.7271
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.27292 0.11505 28.448 <2e-16 ***
## condalgorithm 0.02421 0.16203 0.149 0.881
## condrobot -0.14514 0.15812 -0.918 0.359
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.26 on 374 degrees of freedom
## Multiple R-squared: 0.003658, Adjusted R-squared: -0.00167
## F-statistic: 0.6866 on 2 and 374 DF, p-value: 0.5039
#perceived blurring between human and machine
summary(lm(blur~cond, ra))
##
## Call:
## lm(formula = blur ~ cond, data = ra)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.25141 -0.89807 -0.03008 0.63659 2.74859
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 19.25141 0.08606 223.694 <2e-16 ***
## condalgorithm -0.02001 0.12095 -0.165 0.869
## condrobot -0.22134 0.11823 -1.872 0.062 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9349 on 369 degrees of freedom
## (5 observations deleted due to missingness)
## Multiple R-squared: 0.01175, Adjusted R-squared: 0.006398
## F-statistic: 2.194 on 2 and 369 DF, p-value: 0.1129