城市规模分布由每一代人的留下还是离开决策驱动
City size distributions are driven by each generation's stay-vs-leave decision
AI总结：
本文提出一个仅含“留下概率r”和最大城市数两个参数的模型，证明并模拟了城市规模幂律分布，指数为α=1+1/r，强调家庭纽带与风险规避而非经济优化是城市规模分布的根本驱动力。
摘要：
纵观历史，大多数年轻成年人选择居住在父母居住的地方，而较少的人搬离。通过证明和模拟，这足以解释众所周知的城市规模幂律分布。该模型仅需两个参数：$r$ = 孩子留下的概率，以及最大城市数量（用于模拟高城市排名处观察到的饱和现象）。幂律指数直接由 $α= 1 + 1/r$ 得出，齐普夫定律只是 $r \rightarrow 1$ 时的极限情形。观察到的指数 $(α= 2.2 \pm 0.4, n = 158)$ 与大型谱系研究中的留下或离开数据一致。该模型可自初始化，并可能从最早稳定聚落时期起就已适用。城市规模分布背后的驱动叙事从根本上关乎家庭纽带、熟悉感和风险规避，而非经济优化。
英文摘要：
Throughout history most young adults have chosen to live where their parents did while a smaller number moved away. This is sufficient, by proof and simulation, to account for the well-known power law distributions of city sizes. The model needs only two parameters, $r$ = the probability that a child stays, and the maximum number of cities (which models the observed saturation at high city rank). The power law exponent follows directly as $α= 1 + 1/r$, with Zipf's Law simply the limiting case as $r \rightarrow 1$. Observed exponents $(α= 2.2 \pm 0.4, n = 158)$ are consistent with stay-or-leave data from large genealogic studies. This model is self-initializing and could have applied from the time of the earliest stable settlements. The driving narrative behind city-size distributions is fundamentally about family ties, familiarity, and risk-avoidance, rather than economic optimization.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
