ct_selection_untitled-8CA268FB.R

fun <- function(df, var, type){
  
  df %>% 
    mutate(con = frcode({{var}} == 1 ~ "Great Deal",
                           {{var}} == 2 ~ "Only Some", 
                         {{var}} == 3 ~ "Hardly Any")) %>% 
    group_by(year) %>% 
    ct(con, wt = wtssall,show_na = FALSE) %>% 
    mutate(name = type) %>% 
    na.omit()
  
  
}


yyy3 <- gss %>% fun(conclerg, "Organized Religion")

yyy4 <- gss %>% 
  filter(year > 2018) %>% 
  mutate(con = frcode(conclerg == 1 ~ "Great Deal",
                      conclerg == 2 ~ "Only Some", 
                      conclerg == 3 ~ "Hardly Any")) %>% 
  group_by(year) %>% 
  ct(con, wt = wtssnrps, show_na = FALSE) %>% 
  mutate(name = "Organized Religion") %>% 
  na.omit()

all <- bind_rows(yyy3, yyy4)

all %>%
  ggplot(., aes(x = year, y = pct, color = con, group = con)) +
  geom_point(stroke = 1, shape = 21, fill = "white") +  
  scale_y_continuous(labels =  percent, limits = c(0, .60)) +
  scale_color_fivethirtyeight() +
  geom_labelsmooth(aes(label = con),  method = "loess", formula = y ~ x, family = "font", linewidth = 1, text_smoothing = 30, size = 6, linewidth = 1, boxlinewidth = 0.3, hjust = .20) +
  theme_rb() +
  labs(x = "", y = "", title = "How Much Confidence Do You Have in Organized Religion?", 
       caption = "@ryanburge + @religiondata\nData: General Social Survey, 1972-2022")
save("conf_relig_gss22.png")


gg1 <- gss %>% 
  filter(year <= 2018) %>% 
  mutate(birthyr = year - age) %>% 
  mutate(cohorts = frcode(birthyr >= 1940 & birthyr <= 1944 ~ "1940-1944",
                          birthyr >= 1945 & birthyr <= 1949 ~ "1945-1949",
                          birthyr >= 1950 & birthyr <= 1954 ~ "1950-1954",
                          birthyr >= 1955 & birthyr <= 1959 ~ "1955-1959",
                          birthyr >= 1960 & birthyr <= 1964 ~ "1960-1964",
                          birthyr >= 1965 & birthyr <= 1969 ~ "1965-1969",
                          birthyr >= 1970 & birthyr <= 1974 ~ "1970-1974",
                          birthyr >= 1975 & birthyr <= 1979 ~ "1975-1979",
                          birthyr >= 1980 & birthyr <= 1984 ~ "1980-1984",
                          birthyr >= 1985 & birthyr <= 1989 ~ "1985-1989",
                          birthyr >= 1990 & birthyr <= 1994 ~ "1990-1994",
                          birthyr >= 1995 & birthyr <= 2000 ~ "1995-2000")) %>% 
  mutate(con = frcode(conclerg == 1 ~ "Great Deal",
                      conclerg == 2 ~ "Only Some", 
                      conclerg == 3 ~ "Hardly Any")) %>% 
  group_by(cohorts, year) %>% 
  ct(con, wt = wtssall, show_na = FALSE)  
  


gg2 <- gss %>% 
  filter(year > 2018) %>% 
  mutate(birthyr = year - age) %>% 
  mutate(cohorts = frcode(birthyr >= 1940 & birthyr <= 1944 ~ "1940-1944",
                          birthyr >= 1945 & birthyr <= 1949 ~ "1945-1949",
                          birthyr >= 1950 & birthyr <= 1954 ~ "1950-1954",
                          birthyr >= 1955 & birthyr <= 1959 ~ "1955-1959",
                          birthyr >= 1960 & birthyr <= 1964 ~ "1960-1964",
                          birthyr >= 1965 & birthyr <= 1969 ~ "1965-1969",
                          birthyr >= 1970 & birthyr <= 1974 ~ "1970-1974",
                          birthyr >= 1975 & birthyr <= 1979 ~ "1975-1979",
                          birthyr >= 1980 & birthyr <= 1984 ~ "1980-1984",
                          birthyr >= 1985 & birthyr <= 1989 ~ "1985-1989",
                          birthyr >= 1990 & birthyr <= 1994 ~ "1990-1994",
                          birthyr >= 1995 & birthyr <= 2000 ~ "1995-2000")) %>% 
  mutate(con = frcode(conclerg == 1 ~ "Great Deal",
                      conclerg == 2 ~ "Only Some", 
                      conclerg == 3 ~ "Hardly Any")) %>% 
  group_by(cohorts, year) %>% 
  ct(con, wt = wtssnrps, show_na = FALSE) 
  
both <- bind_rows(gg1, gg2)

both %>% 
  filter(cohorts != "NA") %>% 
  ggplot(., aes(x = year, y = pct, color = con, group = con)) +
  geom_point(stroke = .15, shape = 21, alpha = 1) + 
  geom_smooth(se = FALSE) +
  facet_wrap(~ cohorts) +
  scale_color_fivethirtyeight() +
  theme_rb(legend = TRUE) +
  y_pct() + 
  labs(x = "", y = "", title = "How Much Confidence Do You Have in Organized Religion?", 
       caption = "@ryanburge + @religiondata\nData: General Social Survey, 1972-2022") 
save("conf_relig_cohorts22.png", ht = 9)



gg1 <- gss %>% 
  gss_reltrad6(reltrad) %>% 
  mutate(con = frcode(conclerg == 1 ~ "Great Deal",
                      conclerg == 2 ~ "Only Some", 
                      conclerg == 3 ~ "Hardly Any")) %>% 
  group_by(year, reltrad) %>% 
  ct(con, wt = wtssall, show_na = FALSE) 

  

gg2 <- gss %>% 
  gss_reltrad6(reltrad) %>% 
  mutate(con = frcode(conclerg == 1 ~ "Great Deal",
                      conclerg == 2 ~ "Only Some", 
                      conclerg == 3 ~ "Hardly Any")) %>% 
  group_by(year, reltrad) %>% 
  ct(con, wt = wtssnrps, show_na = FALSE) 

all <- bind_rows(gg1, gg2)


all %>% 
  filter(reltrad != "NA") %>% 
  ggplot(., aes(x = year, y = pct, color = con, group = con)) +
  geom_point(stroke = .15, shape = 21, alpha = 1) + 
  geom_smooth(se = FALSE) +
  facet_wrap(~ reltrad) +
  scale_color_fivethirtyeight() +
  theme_rb(legend = TRUE) +
  y_pct() + 
  theme(strip.text = element_text(size = 17)) +
  labs(x = "", y = "", title = "How Much Confidence Do You Have in Organized Religion?", 
       caption = "@ryanburge + @religiondata\nData: General Social Survey, 1972-2022") 
save("conf_relig_reltrad6_22.png", ht = 7)

gg <- all %>% 
  filter(year == 2022) %>% 
  filter(n > 0) %>% 
  filter(con == "Great Deal") %>% 
  na.omit()

gg %>% 
  mutate(lab = round(pct, 2)) %>%  
  ggplot(., aes(x = reorder(reltrad, pct), y = pct, fill = reltrad)) +
  geom_col(color = "black") +
  coord_flip() +
  theme_rb() +
  scale_fill_manual(values = c("#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e", "#e6ab02")) +
  geom_text(aes(y = pct + .02, label = ifelse(pct > .10, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 8, family = "font") +
  geom_text(aes(y = pct + .015, label = ifelse(pct < .10, paste0(lab*100, '%'), "")), position = position_dodge(width = .9), size = 8, family = "font") +
  scale_y_continuous(labels = percent) +
  labs(x = "", y = "", title = "Share of Each Tradition with A Great Deal of Trust in Organized Religion in 2022", 
       caption = "@ryanburge + @religiondata\nData: General Social Survey, 2022")
save("great_deal_conf_reltrad.png", ht = 4)




fun <- function(df, var, type){
  
  aa1 <- df %>% 
    filter(year <= 2018) %>% 
    mutate(con = case_when({{var}} == 1 ~ 1,
                           {{var}} == 2 | {{var}} == 3 ~ 0)) %>% 
    group_by(year) %>% 
    mean_ci(con, wt = wtssall, ci = .84) %>% 
    mutate(name = type) %>% 
    na.omit()
  
  
  aa2 <- df %>% 
    filter(year == 2021 | year == 2022) %>% 
    mutate(con = case_when({{var}} == 1 ~ 1,
                           {{var}} == 2 | {{var}} == 3 ~ 0)) %>% 
    group_by(year) %>% 
    mean_ci(con, wt = wtssnrps, ci = .84) %>% 
    mutate(name = type) %>% 
    na.omit()
  
  bind_rows(aa1, aa2)
  
}

yyy1 <- gss %>% fun(confinan, "Banks")
yyy2 <- gss %>% fun(conbus, "Major Companies")
yyy4 <- gss %>% fun(coneduc, "Education")
yyy5 <- gss %>% fun(confed, "Executive Branch")
yyy6 <- gss %>% fun(conlabor, "Organized Labor")
yyy7 <- gss %>% fun(conpress, "Press")
yyy8 <- gss %>% fun(conmedic, "Medicine")
yyy9 <- gss %>% fun(conjudge, "SCOTUS")
yyy10 <- gss %>% fun(contv, "Television")
yyy11 <- gss %>% fun(consci, "Scientific Community")
yyy12 <- gss %>% fun(conlegis, "Congress")
yyy13 <- gss %>% fun(conarmy, "Military")

all_data <- bind_rows(yyy1, yyy2, yyy4, yyy5, yyy6, yyy7, yyy8, yyy9, yyy10, yyy11, yyy12, yyy13)

# Calculate the average institutional trust score over time
all_trust <- all_data %>%
  group_by(year) %>%
  summarise(
    trust = mean(mean, na.rm = TRUE),
    lower = mean(lower, na.rm = TRUE), # Average of lower confidence intervals
    upper = mean(upper, na.rm = TRUE)  # Average of upper confidence intervals
  ) %>% 
  mutate(type = "All Other Institutions")


rel <- gss %>% fun(conclerg, "Organized Religion") %>% 
  select(year, trust = mean, lower, upper, type = name)

both <- bind_rows(all_trust, rel)

both %>% 
  ggplot(., aes(x = year, y = trust, color = type, group = type)) +
  geom_line() +
  geom_point(stroke = .75, shape = 21, fill = "white") +
  theme_rb() + 
  scale_y_continuous(labels = percent, limits = c(0, .47)) +
  scale_color_calc() +
  theme(legend.position =  c(.75,  .75)) +
  theme(legend.text = element_text(size = 18)) +
  labs(x = "", y = "% With Great Deal of Confidence", title = "Do People Distrust Organized Religion More Than Other Institutions?", 
       caption = "@ryanburge + @religiondata\nData: General Socail Survey, 1972-2022")
save("rel_trust_compare_to_all22.png")