ARC is the first systematic dataset to code how rebel organizations recruit — across nine dimensions, from gender and age diversity to military background. Explore 319 armed groups across 66 countries, 1941–2012.
Share of groups exhibiting each characteristic. Groups with missing data on a given dimension are excluded from its denominator. Click a bar to filter to groups with that trait.
Each glyph is a group's recruitment "fingerprint" — 9 segments represent the 9 dimensions. Blue = Yes, dim = No, faint = No data. Score shown in center. Hover to identify; click to explore.
Each line is one rebel group crossing all 9 dimensions. Lines that cluster toward the top recruited broadly on that dimension; those at the bottom did not. Color by primary ideology to reveal patterns.
The composite score (0–9) sums how many of the nine dimensions a group scores YES on. Limited to fully-coded groups; partially-coded groups are excluded to avoid distortion. Hover a bar to see the groups in that bin.
Highest and lowest diversity scorers, plus a well-known group for reference. Click to explore their full profiles.
Click any column header to sort. Click a row to open its full profile. All active filters apply.
The Armed Rebellion Coding (ARC) dataset provides the first systematic, cross-national data on rebel group recruitment patterns. For each group, ARC codes whether members were recruited with diversity across nine dimensions: gender, age, education, intra-country origin, extra-country origin, language, plus prior experience in irregular military, regular military, and police.
ARC covers 319 armed groups drawn from the UCDP/PRIO armed conflict database, active between 1941 and 2012. Groups active in multiple countries appear once per country. A composite Recruitment Diversity Score (0–9) sums positive codings across all nine dimensions.
For methodology, variable definitions, and the full replication archive, see the data release article.