Despite longstanding interest in the evolutionary origins and maintenance of vocal learning, we know relatively little about how social dynamics influence vocal learning processes in natural populations. The “social group membership” hypothesis proposes that socially learned calls evolved and are maintained as signals of group membership. However, in fission-fusion societies, individuals can interact in social groups across various social scales. For learned calls to signal group membership over multiple social scales, they must contain information about group membership over each of these scales, a concept termed “hierarchical mapping”. Monk parakeets (Myiopsitta monachus), small parrots native to South America, exhibit vocal mimicry in captivity and fission-fusion social dynamics in the wild. We examined patterns of contact call acoustic similarity in Uruguay to test the hierarchical mapping assumption of the signaling group membership hypothesis. We also asked whether geographic variation patterns matched regional dialects or geographic clines that have been documented in other vocal learning species. We used visual inspection, spectrographic cross-correlation and random forests, a machine learning approach, to evaluate contact call similarity. We compared acoustic similarity across social scales and geographic distance using Mantel tests and spatial autocorrelation. We found high similarity within individuals, and low, albeit significant, similarity within groups at the pair, flock and site social scales. Patterns of acoustic similarity over geographic distance did not match mosaic or graded patterns expected in dialectal or clinal variation. Our findings suggest that monk parakeet social interactions rely more heavily upon individual recognition than group membership at higher social scales.