FBS analyses

RQ1

Absolute output

years <- tibble(year = 1600:1700) %>%
  copy_to_a(con)

years %>% 
  transmute(m=year,b=year-5,e=year+5) %>%
  left_join(fbs_metadata_a %>% 
    count(year=Estimated_admission_year), join_by(b<=year,e>=year)) %>%
  group_by(m) %>%
  summarise(mn=mean(n),.groups="drop") %>%
  transmute(year=m,n=mn,set="Member inductments 10 year rolling mean") %>%
  union_all(years %>% left_join(fbs_metadata_a %>% 
              count(year=Estimated_admission_year) %>%
              mutate(set="Member inductments"))) %>%
  union_all(years %>% inner_join(fbs_metadata_a, join_by(year>=Estimated_admission_year,year<=Estimated_DOD)) %>%
              count(year) %>%
              mutate(set="Active members")) %>%
  union_all(years %>% left_join(fbs_records_a %>%
    inner_join(vd17_id_a, join_by(vd17_id)) %>%
    inner_join(vd17_normalized_years_a, join_by(record_number)) %>%
    count(year=normalized_year, set))) %>%
  union_all(years %>% left_join(vd17_normalized_years_a %>%
    count(year=normalized_year) %>%
    mutate(set = "VD17"))) %>%
  mutate(graph=case_when(
    str_detect(set,"^Member inductments") ~ "Member inductments",
    set=="Active members" ~ "Active members",
    set=="VD17" ~ "VD17",
    str_detect(set,"^Active") ~ "Active member publications",
    T ~ "Member publications"
  )) %>%
  filter(year > 1600, year < 1700) %>%
  arrange(desc(set)) %>%
  collect() %>%
  mutate(graph=fct_relevel(graph,"VD17","Active member publications","Member publications", "Active members", "Member inductments")) %>%
  ggplot(aes(x = year, y = n, color = set)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  theme(legend.justification = c(1, 0), legend.position = c(0.98, -0.06), legend.background = element_blank(), legend.box.just = "bottom", legend.key = element_blank(), legend.box = "horizontal") +
  facet_wrap(~ graph, scales = "free_y", ncol = 2)

Joining with `by = join_by(year)`Joining with `by = join_by(year)`Joining with `by = join_by(year)`

years %>% left_join(fbs_metadata_a, join_by(year>=Estimated_admission_year,year<=Estimated_DOD)) %>%
              count(year,name="members") %>%
  replace_na(list(members=0)) %>%
  inner_join(years %>% left_join(fbs_records_a %>%
                                  filter(str_detect(set,"^Active")) %>%
    inner_join(vd17_id_a, join_by(vd17_id)) %>%
    inner_join(vd17_normalized_years_a, join_by(record_number)) %>%
    count(year=normalized_year, set))) %>%
  filter(year > 1600, year < 1700) %>%
  ggplot(aes(x = year, y = n/members, color = set)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  theme(legend.position = "bottom")

years %>% left_join(fbs_metadata_a %>% inner_join(fbs_links_of_interest_a %>% distinct(member_number)), join_by(year>=Estimated_admission_year,year<=Estimated_DOD)) %>%
              count(year,name="members") %>%
  replace_na(list(members=0)) %>%
  inner_join(years %>% left_join(fbs_records_a %>%
                                  filter(str_detect(set,"^Active")) %>%
    inner_join(vd17_id_a, join_by(vd17_id)) %>%
    inner_join(vd17_normalized_years_a, join_by(record_number)) %>%
    count(year=normalized_year, set))) %>%
  filter(year > 1600, year < 1700) %>%
  ggplot(aes(x = year, y = n/members, color = set)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  theme(legend.position = "bottom")

years %>% left_join(fbs_metadata_a %>% inner_join(fbs_links_of_interest_a %>% distinct(member_number)), join_by(year>=Estimated_admission_year,year<=Estimated_DOD)) %>% 
  count(year) %>%
  mutate(set="Active members associated with publishing") %>%
  union_all(
    years %>% left_join(fbs_metadata_a, join_by(year>=Estimated_admission_year,year<=Estimated_DOD)) %>% 
    count(year) %>%
    mutate(set="Active members")
  ) %>%
  filter(year > 1600, year < 1700) %>%
  ggplot(aes(x = year, y = n, color = set)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  theme(legend.position = "bottom")

years %>% left_join(fbs_metadata_a, join_by(year>=Estimated_admission_year,year<=Estimated_DOD)) %>%
              count(year) %>%
              mutate(set="Active members") %>%
  union_all(years %>% left_join(fbs_records_a %>%
                                  filter(str_detect(set,"^Active")) %>%
    inner_join(vd17_id_a, join_by(vd17_id)) %>%
    inner_join(vd17_normalized_years_a, join_by(record_number)) %>%
    count(year=normalized_year, set))) %>%
  filter(year > 1600, year < 1700) %>%
  ggplot(aes(x = year, y = n, color = set)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  theme(legend.position = "bottom")

Error in UseMethod("left_join") : 
  no applicable method for 'left_join' applied to an object of class "function"

fbs_records_a %>%
    filter(str_detect(set,"^Active")) %>%
    inner_join(vd17_id_a, join_by(vd17_id)) %>%
    inner_join(vd17_normalized_years_a, join_by(record_number)) %>%
  left_join(vd17_genres_a, join_by(record_number)) %>%
  left_join(vd17_genre_categorisation_a) %>%
    count(year=normalized_year, group_1, set) %>%
  ggplot(aes(x=year,y=n,color=group_1)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  theme(legend.position = "bottom") +
  facet_wrap(~set)

years %>% 
  transmute(m=year,b=year-2,e=year+2) %>%
  inner_join(
    fbs_records_a %>%
      filter(set=="Active member substantive role and society purpose related") %>%
      inner_join(vd17_id_a, join_by(vd17_id)) %>%
      inner_join(vd17_genres_a, join_by(record_number)) %>%
      inner_join(vd17_normalized_years_a, join_by(record_number)) %>%    
      left_join(vd17_genre_categorisation_a) %>%
      count(year=normalized_year, group_1, group_3, set) %>%
      filter(group_1=="Society-related"), join_by(b<=year,e>=year)
  ) %>%
  group_by(m,group_3) %>%
  summarise(mn=mean(n),.groups="drop") %>%
  collect() %>%
  mutate(group_3=fct_lump_n(group_3,n=8,w=mn)) %>%
  ggplot(aes(x=m,y=mn,color=group_3)) +
  geom_point() +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete()

RQ2

Original language of society-linked translations

vd17_normalized_langs_a %>% 
  filter(!is.na(original_language)) %>% 
  inner_join(fbs_records_a %>% inner_join(vd17_id_a)) %>% 
  count(original_language, set) %>% 
  arrange(set,desc(n)) %>%
  ggplot(aes(x=original_language,y=n)) + 
  geom_col() +
  theme_hsci_discrete() +
  coord_flip() +
  facet_wrap(~set,scales="free_x")

Joining with `by = join_by(vd17_id)`Joining with `by = join_by(record_number)`

#  gt(rowname_col="original_language", groupname_col = "set") %>%
#  fmt_integer(n)

vd17_normalized_langs_a %>% 
  filter(!is.na(original_language)) %>% 
  inner_join(fbs_records_a %>% inner_join(vd17_id_a)) %>% 
  left_join(vd17_genres_a %>% inner_join(vd17_genre_categorisation_a), join_by(record_number)) %>%
  count(group_3, set) %>% 
  arrange(set,desc(n)) %>%
  ggplot(aes(x=group_3,y=n)) + 
  geom_col() +
  theme_hsci_discrete() +
  coord_flip() +
  facet_wrap(~set,scales="free_x")

Joining with `by = join_by(vd17_id)`Joining with `by = join_by(record_number)`Joining with `by = join_by(genre)`

#  gt(rowname_col="original_language", groupname_col = "set") %>%
#  fmt_integer(n)

RQ 3

fbs_records_a %>% 
  filter(set=="Active member substantive role") %>%
  inner_join(vd17_id_a) %>%
  left_join(all_printers %>% inner_join(vd17_auth_id_a %>% inner_join(vd17_auth_name_a), join_by(printer_gnd==GND))) %>%
  count(unified_name, set) %>% 
  arrange(set,desc(n)) %>%
  collect() %>%
  mutate(unified_name=fct_lump_n(unified_name,n=30,w=n)) %>%
  filter(!is.na(unified_name),unified_name!="Other") %>%
  ggplot(aes(x=unified_name,y=n)) + 
  geom_col() +
  theme_hsci_discrete() +
  coord_flip() +
  facet_wrap(~set,scales="free_x")

Joining with `by = join_by(vd17_id)`Error: object 'all_printers' not found

years %>% 
  transmute(m=year,b=year-5,e=year+5) %>%
  left_join(
    fbs_records_a %>% 
      filter(set=="Active member substantive role") %>%
      inner_join(vd17_id_a) %>%
      left_join(unified_places_of_publication) %>%
      left_join(vd17_normalized_years_a) %>%
      count(normalized_year,place_of_publication, set),
    join_by(b<=normalized_year,e>=normalized_year)
  ) %>%
  replace_na(list(n=0)) %>%
#  complete(m,set,place_of_publication,fill=list(n=0)) %>%
  group_by(m,place_of_publication) %>% 
  summarise(n=sum(n),.groups="drop") %>%
  collect() %>%
  mutate(place_of_publication=fct_lump_n(place_of_publication,n=10,w=n)) %>%
  ggplot(aes(x=m,y=n,color=place_of_publication)) + 
  geom_point() +
  theme_hsci_discrete()

Joining with `by = join_by(vd17_id)`Joining with `by = join_by(record_number)`Joining with `by = join_by(record_number)`

RQ4

fbs_records_a %>% 
  inner_join(vd17_id_a) %>% 
  inner_join(vd17_person_links_a %>% 
              filter(role=="dte"), join_by(record_number)) %>%
  count(combined_name, set) %>% 
  arrange(set,desc(n)) %>%
  collect() %>%
  group_by(set) %>%
  mutate(combined_name=fct_lump_n(combined_name,n=10,w=n)) %>%
  ungroup() %>%
  filter(combined_name!="Other") %>%
  ggplot(aes(x=combined_name,y=n)) + 
  geom_col() +
  theme_hsci_discrete() +
  coord_flip() +
  facet_wrap(~set,scales="free",ncol=1)

Joining with `by = join_by(vd17_id)`

Misc

fbs_metadata_a %>%
  mutate(active_time = as.integer(Estimated_DOD) - as.integer(Estimated_admission_year)) %>%
  filter(active_time >= 0) %>%
  ggplot(aes(x = 1, y = active_time)) +
  geom_quasirandom() +
  theme_hsci_discrete()

fbs_links_of_interest_a %>%
  left_join(vd17_normalized_years_a, join_by(record_number)) %>%
  group_by(member_number) %>%
  summarise(earliest_year = min(normalized_year), latest_year = max(normalized_year)) %>%
  mutate(active_time = latest_year - earliest_year) %>%
  ggplot(aes(x = 1, y = active_time)) +
  geom_quasirandom() +
  theme_hsci_discrete()

years <- tibble(year = 1600:1700) %>%
  copy_to_a(con)

members_through_time <- seq(20, 60, by = 10) %>%
  map(~ years %>%
    inner_join(fbs_metadata_a %>% mutate(Estimated_admission_year = as.integer(Estimated_admission_year), latest_year = as.integer(Estimated_admission_year) + .x), join_by(year >= Estimated_admission_year, year <= latest_year)) %>%
    count(year) %>%
    mutate(set = .x)) %>%
  reduce(union_all)
members_through_time %>%
  ggplot(aes(x = year, y = n, color = as.character(set))) +
  geom_point() +
  theme_hsci_discrete()

fbs_records_a %>%
  inner_join(vd17_id_a, join_by(vd17_id)) %>%
  inner_join(vd17_normalized_years_a, join_by(record_number)) %>%
  count(normalized_year, set) %>%
  inner_join(members_through_time %>% rename(normalized_year = year, members = n, memberset = set)) %>%
  filter(normalized_year > 1630, normalized_year < 1680) %>%
  ggplot(aes(x = normalized_year, y = n / members, color = set)) +
  geom_point(size = 0.5) +
  scale_x_continuous(breaks = seq(1600, 1700, by = 10)) +
  theme_hsci_discrete() +
  facet_wrap(~memberset) +
  theme(legend.position = "bottom")

Error: object 'members_through_time' not found