#

# Proportion of Female Journalists

#

# Assuming author info. is missing at random

# Set Working dir.

setwd(githubdir)

# Source recode

source("good_nyt/scripts/00_nyt_recode.R")

"

Proportion Female Authors (entire newspaper)

"

# Wide to long for fname cols + pub.year

nyt_s <-

nyt[, c(authcols_fname, "publication.year")] %>%

gather(key, name, -publication.year)

# Get gender assuming age = 40

nyt_s_gen <-

nyt_s %>%

distinct(name, publication.year) %>%

rowwise() %>%

do(results = gender(.$name, years = .$publication.year -40, method = "demo")) %>%

do(bind_rows(.$results))

# Proportion Female Authors per year

avg_fem_yr <-

nyt_s_gen %>%

select(proportion_female, year_max) %>%

group_by(year_max) %>%

summarize(avg_fem = mean(proportion_female))

ggplot(avg_fem_yr, aes(year_max + 40, avg_fem)) +

geom_point(color = "#42C4C7") +

ylab("Proportion of Female Journalists") +

xlab("Publication Year") +

scale_x_continuous(breaks = seq(1987, 2007, 1), labels = substr(seq(1987, 2007, 1), 3, 4), expand = c(.03, .03)) +

scale_y_continuous(lim = c(.25, .5), breaks = seq(.2, .5, .05), labels = nolead0s(seq(.2, .5, .05)), expand = c(0, 0)) +

cust_theme

ggsave("good_nyt/figs/all_avg_fem_by_yr.pdf")

# Proportion of Female Journalists per article

# Missing at random

nyt_w <-

nyt_s %>%

left_join(nyt_s_gen, by = "name") %>%

group_by(year_max) %>%

summarize(avg_fem = mean(proportion_female))

ggplot(nyt_w, aes(year_max + 40, avg_fem)) +

geom_point(color = "#42C4C7") +

ylab("Proportion of Female Journalists Per Article") +

xlab("Publication Year") +

scale_x_continuous(breaks = seq(1987, 2007, 1), labels = substr(seq(1987, 2007, 1), 3, 4), expand = c(.03, .03)) +

scale_y_continuous(lim = c(.0, .25), breaks = seq(0, .25, .05), labels = nolead0s(seq(0, .25, .05)), expand = c(0, 0)) +

cust_theme

ggsave("good_nyt/figs/all_avg_fem_per_art_by_yr.pdf")

ggsave("good_nyt/figs/all_avg_fem_per_art_by_yr.png")