Cascades model

Walkthrough parameters & run controls

Batch

Seed τ list

Private evidence: A Private evidence: B Public vote: A Public vote: B

True state—Model constants—

Single community demonstrations & aggregate metrics

Communities (same signals, different τ; sorted high→low)

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No-cascade & Incorrect Cascade & Incorrect No-cascade & Correct Cascade & Correct

Event log

L = log-odds; λ = log(q/(1−q))

Parameters & batch controls

Signal accuracy, q

Number of agents, N

Random seed (optional)

Batch size

τ sweep resolution

Main τ figure

Order parameters over τ

Empirical P(cascade) Empirical P(correct aggregate vote) Predicted phase P(cascade) Predicted phase P(correct aggregate vote) Phase cutoff τ = 1/d

Phase performance

τ phase performance

p range (start / step / end)

q range (start / step / end)

Number of agents, N

Batch size per (p,q)

Random seed (optional)

Signal accuracy, q

τ range (start / step / end)

Population size range (min N / max N)

Batch size (number of signal sequences; reused across all τ)

Random seed (optional)

Fixed number of agents, N

q range (start / step / end)

τ range (start / step / end)

Batch size (number of runs per q; signals monotone in q within each run)

Random seed (optional)