Weighted scoring rules, perhaps the most common procedures for multi-candidate, single-winner elections, are defined by score vectors, of which the Borda Count is the best known example. The concept of Borda dominance identifies candidates who cannot win under any score vector; we assess its usefulness in the context of single-winner elections. We propose several families of score vectors that can accommodate any number of candidates, asking whether any of them can improve on Borda Count. Using large-scale simulation, we compare score vectors on Condorcet efficiency, or ability to find a Condorcet winner when one exists, on resilience to ballot truncation, and on ability to maximize the Copeland score using both complete and uniformly truncated ballots. Borda performs well on criteria related to Condorcet winner and Copeland score but, depending on the preference model, may not be optimal. Convex score vectors are the most resilient to ballot truncation.

加权评分规则，也许是多候选人、单赢选举中最常见的程序，由评分向量定义，其中 Borda Count 是最著名的例子。Borda 优势的概念确定了在任何分数向量下都无法获胜的候选人；我们评估它在单一获胜者选举中的用处。我们提出了几个可以容纳任意数量候选者的分数向量系列，询问它们中的任何一个是否可以改进 Borda Count。使用大规模模拟，我们比较了 Condorcet 效率的得分向量，或在存在时找到 Condorcet 获胜者的能力，对选票截断的弹性，以及使用完整和统一截断选票最大化 Copeland 得分的能力。Borda 在与 Condorcet 冠军和 Copeland 得分相关的标准上表现良好，但是，取决于偏好模型，可能不是最佳的。凸分数向量对选票截断最有弹性。