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About this paper
Mari Kawakatsu, Philip S. Chodrow, Nicole Eikmeier, Daniel B. Larremore
Researchers from Princeton, MIT, UCLA, and University of Colorado Boulder developed a generative adaptive network model to explain how hierarchies emerge through social reinforcement, demonstrating that a preference for high status can destabilize egalitarian states. The model, which is analytically tractable and supports statistical inference, revealed consistent empirical patterns where endorsements flow upwards but preferentially to nodes with similar ranks across diverse real-world datasets.
Key insights
- Hierarchies can emerge and persist solely through social reinforcement (winner effects via prestige preference) when the preference for high status exceeds a specific critical value, even without intrinsic differences in individual strengths.
- A critical `β_c1` separates egalitarian from hierarchical regimes, with the proximity preference `β_2` shaping the structure of the hierarchy but not determining its onset.
- Across diverse empirical datasets (academic hiring, animal dominance, human friendships), endorsements consistently show a preference for high status (`ˆβ_1 > 0`) but also for nodes with similar ranks (`ˆβ_2 < 0`), suggesting a pattern of 'short hops' up the hierarchical ladder.
Summary by alphaXiv.
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