Statistical Aspects of Equitable Apportionment
研究了美国众议院席位分配中因人口测量误差和整数约束导致的代表权不平等问题，用决策理论统一处理，发现当前方法在数据有误差时表现良好，而配额法则相反，并提出了偏差的量化定义。
Abstract Two problems that arise in apportioning the U.S. House of Representatives are: (a) fractional numbers of representatives cannot be allocated, so states receive different per capita representation, and (b) the state population sizes are known only with error. Both problems are addressed in a unified way with decision theory. Although the method currently in use, equal proportions, has poor properties when the populations are assumed perfectly known, it performs surprisingly well in the presence of modest errors in the data. The converse is true for the quota method. Previously developed qualitative notions of bias in apportionment methods are extended to provide a quantitative definition of bias. The new definition accounts both for bias in the apportionment method and for bias arising from imperfect population measurements. Illustrative estimates of the bias against states with large black populations are developed.