Democracy Has Declined–But Remains Deeply Divided

Global scores have declined since 2006, while countries remain sharply divided between democratic and authoritarian systems

A two-panel redesign of the OWID Democracy Index choropleth. A line chart traces the global median score falling from 5.89 in 2006 to 5.32 in 2024, while a beeswarm chart shows how 167 countries cluster sharply at the democratic and authoritarian extremes in 2024 — with few near the middle. Built with ggplot2, ggbeeswarm, and patchwork in R.

Original

The original visualization comes from AI Risk Rankings

Original visualization

Makeover

Figure 1: A two-panel chart titled “Democracy Has Declined–But Remains Deeply Divided.” The top panel shows a line chart of the global Democracy Index median falling from 5.89 in 2006 to 5.32 in 2024, with individual country trajectories as faint gray lines. The bottom panel is a beeswarm chart showing 2024 scores for 167 countries grouped by region and colored by regime type: teal for full democracies, steel blue for flawed democracies, amber for hybrid regimes, and dark purple for authoritarian regimes. Europe clusters near the top; Africa and Asia near the bottom. Data source: Economist Intelligence Unit, with major processing by Our World in Data.

Steps to Create this Graphic

1. Load Packages & Setup

```{r}
#| label: load
#| warning: false
#| message: false      
#| results: "hide"     

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
  if (!require("pacman")) install.packages("pacman")
  pacman::p_load(
    tidyverse, ggtext, showtext, scales, 
  glue, janitor, patchwork, ggbeeswarm
)
})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 10,
  height = 10,
  units  = "in",
  dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

2. Read in the Data

```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false
#| 

df_raw <- readxl::read_excel(
  here::here("data/MakeoverMonday/2026/2024 Democracy Index.xlsx")) |>
  clean_names()
```

3. Examine the Data

```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(df_raw)
skimr::skim_without_charts(df_raw)
```

4. Tidy Data

```{r}
#| label: tidy
#| warning: false

### |- regime type factor levels ----
regime_levels <- c(
  "Authoritarian regime",
  "Hybrid regime",
  "Flawed democracy",
  "Full democracy"
)

### |- clean and encode ----
df <- df_raw |>
  mutate(
    regime_classification = factor(regime_classification, levels = regime_levels),
    region_short = case_when(
      world_region_according_to_owid == "North America" ~ "North\nAmerica",
      world_region_according_to_owid == "South America" ~ "South\nAmerica",
      world_region_according_to_owid == "Europe" ~ "Europe",
      world_region_according_to_owid == "Asia" ~ "Asia",
      world_region_according_to_owid == "Africa" ~ "Africa",
      world_region_according_to_owid == "Oceania" ~ "Oceania",
      TRUE ~ world_region_according_to_owid
    )
  )

### |- Panel A data: global median trend ----
df_trend <- df |>
  group_by(year) |>
  summarise(
    global_median = median(democracy_index, na.rm = TRUE),
    .groups = "drop"
  )

# 2006 and 2024 endpoints for annotation
trend_2006 <- df_trend |>
  filter(year == 2006) |>
  pull(global_median)
trend_2024 <- df_trend |>
  filter(year == 2024) |>
  pull(global_median)

### |- Panel B data: 2024 cross-section with region medians ----
df_2024 <- df |>
  filter(year == 2024)

# Region medians for sorting and overlay dots
df_region_medians <- df_2024 |>
  group_by(region_short) |>
  summarise(
    region_median = median(democracy_index, na.rm = TRUE),
    .groups = "drop"
  ) |>
  arrange(desc(region_median))

# Sorted region order (highest median → top of chart after coord_flip)
region_order <- df_region_medians$region_short

df_2024 <- df_2024 |>
  mutate(region_short = factor(region_short, levels = region_order))
```

5. Visualization Parameters

```{r}
#| label: params
#| include: true
#| warning: false

## |- plot aesthetics ----
colors <- get_theme_colors(
  palette = list(
    full_dem    = "#1D9E75",
    flawed_dem  = "#74ADD1",
    hybrid      = "#E09338",
    authoritar  = "#4A1A2C",
    trend_line  = "#1A1A2E",
    country_bg  = "#D9D9D9",
    region_dot  = "#F7F5F2",
    background  = "#F7F5F2"
  )
)

# Convenience aliases
col_full_dem <- colors$palette$full_dem
col_flawed_dem <- colors$palette$flawed_dem
col_hybrid <- colors$palette$hybrid
col_authoritar <- colors$palette$authoritar
col_trend <- colors$palette$trend_line
col_country_bg <- colors$palette$country_bg
col_region_dot <- colors$palette$region_dot
col_background <- colors$palette$background

# Named vector for regime color scale
regime_colors <- c(
  "Full democracy"       = col_full_dem,
  "Flawed democracy"     = col_flawed_dem,
  "Hybrid regime"        = col_hybrid,
  "Authoritarian regime" = col_authoritar
)

### |- titles and caption ----
title_text <- "Democracy Has Declined\u2013But Remains Deeply Divided"

subtitle_text <- "Global scores have declined since 2006, while countries remain sharply divided between democratic\nand authoritarian systems"

caption_text <- create_mm_caption(
  mm_year     = 2026,
  mm_week     = 17,
  source_text = "Economist Intelligence Unit (2006–2024), Democracy Index<br>with major processing by Our World in Data"
)

### |- fonts ----
setup_fonts()
fonts <- get_font_families()

### |- base and weekly theme ----
base_theme <- create_base_theme(colors)

weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Panel
    panel.background = element_rect(fill = col_background, color = NA),
    plot.background = element_rect(fill = col_background, color = NA),
    panel.grid.major.y = element_line(color = "gray88", linewidth = 0.25),
    panel.grid.major.x = element_blank(),
    panel.grid.minor = element_blank(),

    # Axes
    axis.ticks = element_blank(),
    axis.title = element_text(size = 9, color = "gray40"),
    axis.text = element_text(size = 8, color = "gray30"),

    # Legend
    legend.position = "top",
    legend.justification = "left",
    legend.title = element_blank(),
    legend.text = element_text(size = 8, color = "gray20"),
    legend.key.size = unit(8, "pt"),
    legend.key = element_rect(fill = NA, color = NA),
    legend.background = element_rect(fill = NA, color = NA),
    legend.spacing.x = unit(10, "pt"),

    # Plot margin
    plot.margin = margin(6, 10, 6, 10)
  )
)

theme_set(weekly_theme)
```

6. Plot

```{r}
#| label: plot
#| warning: false

### |- Panel A: Global Median Trend (2006–2024) ----
p_trend <- ggplot() +

  # Geoms
  geom_line(
    data = df |> filter(!is.na(democracy_index)),
    aes(x = year, y = democracy_index, group = entity),
    color = col_country_bg,
    linewidth = 0.25,
    alpha = 0.5
  ) +
  geom_line(
    data = df_trend,
    aes(x = year, y = global_median),
    color = col_trend,
    linewidth = 1.2
  ) +
  geom_point(
    data  = df_trend |> filter(year %in% c(2006, 2024)),
    aes(x = year, y = global_median),
    color = col_trend,
    size  = 3
  ) +
  geom_hline(
    yintercept = 5.0,
    linetype   = "dashed",
    color      = "gray60",
    linewidth  = 0.3
  ) +
  # Annnotate
  annotate(
    "text",
    x = 2006, y = trend_2006 + 0.4,
    label = glue("{round(trend_2006, 2)}"),
    size = 3, hjust = 0.5,
    color = col_trend,
    fontface = "bold",
    family = fonts$text
  ) +
  annotate(
    "text",
    x = 2024, y = trend_2024 + 0.4,
    label = glue("{round(trend_2024, 2)}"),
    size = 3, hjust = 0.5,
    color = col_trend,
    fontface = "bold",
    family = fonts$text
  ) +
  annotate(
    "text",
    x = 2011.5, y = 4.35,
    label = "Global democracy has declined\nfor nearly two decades",
    size = 2.9, hjust = 0,
    color = "gray20",
    fontface = "bold",
    lineheight = 1.2,
    fill = "#F7F5F2",
    label.size = 0,
    label.padding = unit(0.25, "lines"),
    family = fonts$text
  ) +
  annotate(
    "text",
    x = 2011.5, y = 3.38,
    label = glue("({round(trend_2006 - trend_2024, 2)} point drop, {min(df_trend$year)}\u2013{max(df_trend$year)})"),
    size = 2.5, hjust = 0,
    color = "gray45",
    lineheight = 1.2,
    family = fonts$text
  ) +
  annotate(
    "text",
    x = 2006.2, y = 5.19,
    label = "Scale midpoint (5.0)",
    size = 2.3, hjust = 0,
    color = "gray50",
    family = fonts$text
  ) +
  # Scales
  scale_x_continuous(
    breaks = seq(2006, 2024, by = 4),
    expand = expansion(mult = c(0.02, 0.04))
  ) +
  scale_y_continuous(
    limits = c(0, 10.5),
    breaks = seq(0, 10, by = 2),
    labels = label_number(accuracy = 1)
  ) +
  # Labs
  labs(
    x = NULL,
    y = "Democracy Index (0–10)",
    title = "**Global median has declined steadily since 2006**",
    subtitle = "Gray lines = individual countries · Dark line = global median"
  ) +
  # Theme
  theme(
    plot.title = element_text(size = 12, color = "gray10", family = fonts$title, margin = margin(b = 3)),
    plot.subtitle = element_text(size = 9, color = "gray40", family = fonts$subtitle, margin = margin(b = 6))
  )

### |- Panel B: 2024 Beeswarm by Region ----
p_beeswarm <- ggplot() +

  # Geoms
  geom_beeswarm(
    data = df_2024 |>
      mutate(dot_alpha = if_else(
        regime_classification %in% c("Full democracy", "Authoritarian regime"),
        0.95, 0.60
      )),
    aes(
      x = region_short, y = democracy_index, color = regime_classification,
      alpha = I(dot_alpha)
    ),
    size = 2.2,
    cex = 2.8,
    method = "swarm"
  ) +
  geom_point(
    data = df_region_medians |>
      mutate(region_short = factor(region_short, levels = region_order)),
    aes(x = region_short, y = region_median),
    shape = 23,
    size = 4,
    fill = col_region_dot,
    color = col_trend
  ) +
  geom_hline(yintercept = 8.0, linetype = "dotted", color = "gray55", linewidth = 0.3) +
  geom_hline(yintercept = 6.0, linetype = "dotted", color = "gray55", linewidth = 0.3) +
  geom_hline(yintercept = 4.0, linetype = "dotted", color = "gray55", linewidth = 0.3) +
  # Annotate
  annotate("text",
    x = 6.6, y = 8.18, label = "Full democracy \u2265 8.0",
    size = 2.6, hjust = 1, color = "gray35", family = fonts$text
  ) +
  annotate("text",
    x = 6.6, y = 6.18, label = "Flawed democracy \u2265 6.0",
    size = 2.6, hjust = 1, color = "gray35", family = fonts$text
  ) +
  annotate("text",
    x = 6.6, y = 4.18, label = "Hybrid regime \u2265 4.0",
    size = 2.6, hjust = 1, color = "gray35", family = fonts$text
  ) +
  annotate(
    "text",
    x = 5.15, y = 1.3,
    label = "Most African countries\ncluster below 4.0",
    size = 2.5, hjust = 0.5,
    color = col_authoritar,
    lineheight = 1.2,
    family = fonts$text
  ) +
  # Scales
  scale_color_manual(
    values = regime_colors,
    guide = guide_legend(
      override.aes = list(size = 4),
      nrow = 1
    )
  ) +
  scale_y_continuous(
    limits = c(0, 10.5),
    breaks = seq(0, 10, by = 2),
    labels = label_number(accuracy = 1)
  ) +
  # Labs
  labs(
    x = NULL,
    y = "Democracy Index (0–10)",
    title = "**2024: Countries cluster at the extremes\u2013few sit in the middle**",
    subtitle = "Each dot = one country \u00b7 \u25c6 = regional median \u00b7 Regions sorted by median score"
  ) +
  # Theme
  theme(
    plot.title = element_text(size = 12, color = "gray10", family = fonts$title, margin = margin(b = 3)),
    plot.subtitle = element_text(size = 9, color = "gray40", family = fonts$subtitle, margin = margin(b = 6)),
    legend.position = "top",
    legend.justification = "left"
  )

### |- Combined plots ----
p_combined <- p_trend / p_beeswarm +
  plot_layout(heights = c(2, 3)) +
  plot_annotation(
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text,
    theme = theme(
      plot.title = element_text(
        size = 24, face = "bold",
        color = "gray10",
        family = fonts$title,
        margin = margin(b = 4)
      ),
      plot.subtitle = element_text(
        size = 12, color = "gray30",
        family = fonts$subtitle,
        margin = margin(b = 12)
      ),
      plot.caption = element_markdown(
        size = 7, color = "gray50",
        family = fonts$caption,
        hjust = 0,
        margin = margin(t = 10)
      ),
      plot.background = element_rect(fill = col_background, color = NA),
      plot.margin = margin(16, 16, 10, 16)
    )
  )
```

7. Save

```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot_patchwork(
  plot = p_combined, 
  type = "makeovermonday", 
  year = current_year,
  week = current_week,
  width = 10, 
  height = 10
  )
```

8. Session Info

TipExpand for Session Info

R version 4.5.3 (2026-03-11 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default
  LAPACK version 3.12.1

locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] here_1.0.2       ggbeeswarm_0.7.3 patchwork_1.3.2  janitor_2.2.1   
 [5] glue_1.8.0       scales_1.4.0     showtext_0.9-8   showtextdb_3.0  
 [9] sysfonts_0.8.9   ggtext_0.1.2     lubridate_1.9.5  forcats_1.0.1   
[13] stringr_1.6.0    dplyr_1.2.1      purrr_1.2.2      readr_2.2.0     
[17] tidyr_1.3.2      tibble_3.3.1     ggplot2_4.0.3    tidyverse_2.0.0 
[21] pacman_0.5.1    

loaded via a namespace (and not attached):
 [1] gtable_0.3.6       beeswarm_0.4.0     xfun_0.57          htmlwidgets_1.6.4 
 [5] tzdb_0.5.0         yulab.utils_0.2.4  vctrs_0.7.3        tools_4.5.3       
 [9] generics_0.1.4     curl_7.0.0         gifski_1.32.0-2    pkgconfig_2.0.3   
[13] ggplotify_0.1.3    skimr_2.2.2        RColorBrewer_1.1-3 S7_0.2.1          
[17] readxl_1.4.5       lifecycle_1.0.5    compiler_4.5.3     farver_2.1.2      
[21] textshaping_1.0.5  repr_1.1.7         codetools_0.2-20   snakecase_0.11.1  
[25] litedown_0.9       vipor_0.4.7        htmltools_0.5.9    yaml_2.3.12       
[29] pillar_1.11.1      camcorder_0.1.0    magick_2.9.1       commonmark_2.0.0  
[33] tidyselect_1.2.1   digest_0.6.39      stringi_1.8.7      rsvg_2.7.0        
[37] rprojroot_2.1.1    fastmap_1.2.0      grid_4.5.3         cli_3.6.6         
[41] magrittr_2.0.5     base64enc_0.1-6    withr_3.0.2        rappdirs_0.3.4    
[45] timechange_0.4.0   rmarkdown_2.31     otel_0.2.0         cellranger_1.1.0  
[49] hms_1.1.4          evaluate_1.0.5     knitr_1.51         markdown_2.0      
[53] gridGraphics_0.5-1 rlang_1.2.0        gridtext_0.1.6     Rcpp_1.1.1        
[57] xml2_1.5.2         svglite_2.2.2      rstudioapi_0.18.0  jsonlite_2.0.0    
[61] R6_2.6.1           fs_2.0.1           systemfonts_1.3.2 

9. GitHub Repository

TipExpand for GitHub Repo

The complete code for this analysis is available in mm_2026_17.qmd.

For the full repository, click here.

10. References

TipExpand for References

Primary Data (Makeover Monday): 1. Makeover Monday 2026 Week 17: 2024 EIU Democracy Index 2. Original Chart: Democracy Index, 2024 — Our World in Data - Source: Our World in Data interactive choropleth map - Coverage: 167 countries, Democracy Index scores 0–10 (2006–2024)

Source Data: 3. Economist Intelligence Unit — Democracy Index 2024 - Coverage: 167 countries scored annually on five sub-indices: electoral pluralism, functioning government, political participation, democratic culture, and civil liberties - Unit: Composite index 0–10; four regime classifications: Full Democracy (≥ 8.0), Flawed Democracy (≥ 6.0), Hybrid Regime (≥ 4.0), Authoritarian (< 4.0) 4. Our World in Data — Democracy Index (EIU) - Attribution: Economist Intelligence Unit (2006–2024), with major processing by Our World in Data

Note: Analysis uses the composite Democracy Index score as the primary variable. Regional medians were computed across all available countries per region for 2024. Regime classifications follow the EIU’s published thresholds. No additional normalization was applied.

11. Custom Functions Documentation

Note📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

Functions Used:

• fonts.R: setup_fonts(), get_font_families() - Font management with showtext
• social_icons.R: create_social_caption() - Generates formatted social media captions
• image_utils.R: save_plot() - Consistent plot saving with naming conventions
• base_theme.R: create_base_theme(), extend_weekly_theme(), get_theme_colors() - Custom ggplot2 themes

Why custom functions?
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

Source Code:
View all custom functions → GitHub: R/utils