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Fig 1.

Distribution of normalized centrality scores in the largest component (n = 623).

Ridgeline density plots of Degree, closeness, betweenness and eigenvector centralities (textbook-normalized) reveal starkly different shapes: over 50% of clans have zero betweenness and very low degree (medians at 0.002), closeness is more symmetrically distributed (median = 0.155), and only one clan achieves the maximum eigenvector score of 1. The horizontal axis is zoomed to [0, 0.3] to focus on the bulk of the distribution.

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Fig 2.

‘Ndrangheta matrimonial alliance network: structure, core, and tie composition.

(A) Undirected network of inter-clan matrimonial alliances (largest connected component); nodes represent families and node size is proportional to eigenvector centrality; red nodes indicate clans classified as powerful (per the La C Play classification), blue nodes other clans; labels show powerful clans. (B) k-core backbone of the same network (upper quartile coreness), using the same encoding for node size and clan status. (C) Composition of unique alliances by clan status: powerful–powerful (red), powerful–other / other–powerful (purple), and other–other (blue).

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Fig 3.

Distribution of bride-receiving shares across ’Ndrangheta families.

Histogram showing counts of 623 families in the largest weakly connected component. Bin ranges: [0.0, 0.2), [0.2, 0.4), [0.4, 0.6), [0.6, 0.8), [0.8, 1.0]. Bimodal peaks occur at distribution extremes.

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Table 1.

Network centrality by clan status (5,000 permutation tests).

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Fig 4.

Resilience of the ’Ndrangheta matrimonial network under two edge-removal schemes.

Monte-Carlo simulations (100 replicates) in which edges are deleted either by equal-share (left column) or equal-count (right column) schemes, separately for edges involving powerful clans (red) and those not involving powerful clans (blue). Rows: (A, B) Connectivity—size of the largest connected component as a share of all families; (C, D) Reachability density—the proportion of unordered family pairs that remain connected by some undirected path; (E, F) Largest bicomponent—size of the largest biconnected component as a share of all families; (G, H) Average path length (giant)—average shortest-path length within the largest connected component. Columns: (left) Equal-share removal: at each step a fixed fraction of that edge category is removed (x-axis = fraction removed within the category); (right) Equal-count removal: at each step the same absolute number of deletions is applied to each category (x-axis = number of edges removed, up to the maximum number of powerful-involving ties). Shaded ribbons show the 10th – 90th percentile range across replicates.

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Table 2.

Permutation test of bride-receiving share by clan status.

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Table 2 Expand

Fig 5.

Adaptive sliding-window contrasts of structural centrality across the bride-receiving spectrum.

Each panel reports local contrasts in normalized centrality as a function of bride-receiving share c, where c = 0 denotes exclusive bride-sending and c = 1 denotes exclusive bride-receiving. The y-axis shows the difference in average centrality between clans near each c and parity-oriented clans (c ≈ 0.50); values above zero indicate greater centrality than parity, and values below zero indicate a structural penalty. Two specifications assess sensitivity to the parity definition: a strict neutrality band (; thinner/darker intervals) and a relaxed band (; thicker/lighter intervals). Pointwise 95% randomization intervals are obtained from the empirical 2.5% and 97.5% quantiles of across B = 5,000 outcome permutations; points and lines track the strict specification.

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Table 3.

Directed robustness checks of status differences.

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Table 3 Expand

Table 4.

Peak mean differences in network centrality under alternative specifications.

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Fig 6.

Status-conditioned returns on matrimonial strategy.

Scatterplots show the relationship between bride-receiving share and normalized centrality, faceted by measure and colored by clan status. Solid curves overlay a robust, local-linear LOESS smoother drawn separately for each status group.

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