The central argument is that queue position operates as a form of social currency that brokers convert into fees, and that this conversion is structured by the temporal and spatial organisation of machine access rather than by individual deviance. Because no primary observational data are available, the paper specifies a before-after-control-impact design and characterises its operating characteristics under a declared variance structure. The design uses 8, 16, 24, and 32 clusters, effect sizes of 3, 5, and 8 percentage points, and 2000 replications per cell. The intraclass correlation is 0.64, the between-cluster standard deviation is 6.0, and the residual standard deviation is 4.5. Power analysis indicates that 56 clusters are required to detect a 5-percentage-point effect at 80% power.
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Mwangi et al. (2026) studied this question.
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