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Young Evangelicals and the Environment
## Environment Issue Positions ####
env_fun <- function(df, ques, q2){
ques <- enquo(ques)
df %>%
filter(race ==1) %>%
filter(evangelical ==1) %>%
mutate(age = 2016 - birthyr) %>%
mutate(groups = recode(age, "18:29 = '18-29'; 30:44 = '30-44'; 45:54 = '45-54'; 55:64 = '55-64'; 65:74 = '65-74'; 75:100 = '75 and Older'")) %>%
mutate(env = recode(!! ques, "1=1; 2=0; else = NA")) %>%
group_by(groups) %>%
mean_ci(env) %>%
mutate(question = !! q2)
}
ggg1 <- cces16 %>% env_fun(CC16_333a, "EPA Regulate Carbon Dioxide")
ggg2 <- cces16 %>% env_fun(CC16_333b, "Raise Fuel Efficiency Standards")
ggg3 <- cces16 %>% env_fun(CC16_333c, "Require Alt. Fuels, Even if Prices Rise")
ggg4 <- cces16 %>% env_fun(CC16_333d, "Strengthen Enforce of Clean Air/Water")
graph <- bind_df("ggg")
graph %>%
ggplot(., aes(x = groups, y =mean, fill = groups)) +
geom_col(color = "black") +
facet_grid(. ~ question) +
geom_errorbar(aes(ymin=lower, ymax=upper), width=.2, position=position_dodge(.9)) +
theme_gg("Lato") +
scale_y_continuous(labels = percent) +
scale_fill_paletteer_d(ghibli, PonyoMedium) +
# scale_fill_nord(palette = "red_mountain")+
theme(axis.text.x = element_text(angle = 45, hjust =1)) +
labs(x = "Age Group", y = "Percent in Favor", title = "Younger, White Evangelicals are Supportive of Environmental Protection", caption = "Data: CCES 2016") +
ggsave("D://env_evan.png", width = 12)
## Importance of Environment ####
g2 <- cces16 %>%
mutate(environment = recode(CC16_301h, "1=5; 2=4; 3=3; 4=2; 5=1; else=99")) %>%
filter(race ==1) %>%
filter(evangelical ==1) %>%
filter(environment != 99) %>%
mutate(age = 2016 - birthyr) %>%
mutate(groups = recode(age, "18:29 = '18-29'; 30:44 = '30-44'; 45:54 = '45-54'; 55:64 = '55-64'; 65:74 = '65-74'; 75:100 = '75 and Older'")) %>%
group_by(groups) %>%
mean_ci(environment)
g2 %>%
ggplot(., aes(y=mean, x= groups, color = groups)) +
geom_point(position=position_dodge(width=0.5), size =4) +
geom_errorbar(aes(ymin = lower, ymax=upper), position=position_dodge(0.5), size = .75, width = .2) +
coord_flip() +
theme_gg("Lato") +
scale_color_paletteer_d(ghibli, PonyoMedium) +
labs(title = "How Important is the Environment to You?", x = "Age Group", y = "Level of Importance", caption = "Data: CCES 2016") +
scale_y_continuous(limits = c(0.85,5.05), breaks = c(1,2,3,4,5), labels = c("No Importance", "Very Low", "Somewhat Low", "Somewhat High", "Very High")) +
ggsave("D://env_imp.png", width = 12)
## Mapping Importance on Vote Choice ####
fff <- cces16 %>%
mutate(environment = recode(CC16_301h, "1=5; 2=4; 3=3; 4=2; 5=1; else=99")) %>%
mutate(env2 = recode(environment, "4:5 = 'High Importance '; 1:3 = 'Low Importance '; else= NA")) %>%
mutate(vote16 = recode(CC16_410a, "1=1; 2=0; else = NA")) %>%
filter(race ==1) %>%
filter(evangelical ==1) %>%
mutate(age = 2016 - birthyr) %>%
mutate(groups = recode(age, "18:29 = '18-29'; 30:44 = '30-44'; 45:54 = '45-54'; 55:64 = '55-64'; 65:74 = '65-74'; 75:100 = '75 and Older'")) %>%
group_by(groups, env2) %>%
mean_ci(vote16) %>%
filter(env2 != "NA")
fff2 <- cces16 %>%
mutate(vote16 = recode(CC16_410a, "1=1; 2=0; else = NA")) %>%
filter(race ==1) %>%
filter(evangelical ==1) %>%
mutate(age = 2016 - birthyr) %>%
mutate(groups = recode(age, "18:29 = '18-29'; 30:44 = '30-44'; 45:54 = '45-54'; 55:64 = '55-64'; 65:74 = '65-74'; 75:100 = '75 and Older'")) %>%
group_by(groups) %>%
mean_ci(vote16) %>%
mutate(env2 = "Entire Group ")
gg <- bind_df("fff")
gg$env2 <- factor(gg$env2, levels = c("Low Importance ", "Entire Group ", "High Importance "))
gg %>%
ggplot(., aes(x = env2, y = mean, fill = env2)) +
geom_col(color = "black") +
facet_grid(~ groups) +
geom_errorbar(aes(ymin = lower, ymax=upper), position=position_dodge(0.5), size = .75, width = .2) +
theme_gg("Lato") +
theme(legend.position = "bottom") +
scale_y_continuous(labels = percent) +
scale_fill_paletteer_d(dutchmasters, milkmaid) +
theme(axis.text.x = element_blank()) +
theme(axis.ticks.x = element_blank()) +
labs(x = "", y = "Share of the Two Party Vote for Trump", title = "The Importance of the Environment and Vote Choice", subtitle = "Among White Evangelicals", caption = "Data: CCES 2016")
ggsave("D://env_vote_groups.png", width = 12)
### This is doing the 2012 Climate Change Stuff ####
library(haven)
library(labelled)
library(car)
cces12 <- read_dta("D://cces/data/cces12.dta")
gg2 <- cces12 %>%
filter(evangelical ==1) %>%
filter(race ==1) %>%
mutate(age = 2012 - birthyr) %>%
mutate(groups = recode(age, "18:29 = '18-29'; 30:44 = '30-44'; 45:54 = '45-54'; 55:64 = '55-64'; 65:74 = '65-74'; 75:100 = '75 and Older'")) %>%
group_by(groups) %>%
ct(CC321) %>%
# mutate(env = recode(CC321, "1 = 'Serious problem-needs immediate action';
# 2 = 'Enough evidence-some action needed';
# 3 = 'Don`t Know Enough-more research necessary';
# 4 = 'Concern is exaggerated-no action necessary';
# 5 = 'Is not occurring-not a real issue';
# else = NA")) %>%
na.omit()
gg2$env <- factor(gg2$env, levels = c("Serious problem-needs immediate action", "Enough evidence-some action needed", "Don`t Know Enough-more research necessary", "Concern is exaggerated-no action necessary", "Is not occurring-not a real issue"))
gg2 %>%
ggplot(., aes(x =CC321, y = pct, fill = groups)) +
geom_col(color = "black", position = "dodge") +
theme_gg("Lato") +
theme(legend.position = "bottom") +
scale_fill_paletteer_d(ghibli, PonyoMedium) +
scale_y_continuous(labels = percent) +
geom_text(aes(y = pct + .01, label = paste0(pct*100, '%')), position = position_dodge(width = .9), size = 8, family = "font") +
labs(x = "", y = "", title = "View of Climate Change Among White Evangelicals", subtitle = "", caption = "Data: CCES 2012") +
scale_x_continuous(breaks = c(1,2,3,4,5), labels = c("Serious problem\nNeeds immediate action", "Enough evidence\nSome action needed", "Don`t know enough\nMore research necessary", "Concern is exaggerated\nNo action necessary", "Is not occurring\nNot a real issue")) +
ggsave("D://env12_climate.png", width = 12)
gg2 <- cces12 %>%
mutate(age = 2012 - birthyr) %>%
mutate(groups = recode(age, "18:29 = '18-29'; 30:44 = '30-44'; 45:54 = '45-54'; 55:64 = '55-64'; 65:74 = '65-74'; 75:100 = '75 and Older'")) %>%
group_by(groups) %>%
ct(CC321) %>%
# mutate(env = recode(CC321, "1 = 'Serious problem-needs immediate action';
# 2 = 'Enough evidence-some action needed';
# 3 = 'Don`t Know Enough-more research necessary';
# 4 = 'Concern is exaggerated-no action necessary';
# 5 = 'Is not occurring-not a real issue';
# else = NA")) %>%
na.omit()
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