While natural languages differ widely in both canonical word order and word order flexibility, their word orders still follow shared cross-linguistic statistical patterns, often attributed to functional pressures. In the effort to identify these pressures, prior work has compared real and counterfactual word orders. Yet one functional pressure has been overlooked in such investigations: the uniform information density (UID) hypothesis, which holds that information should be spread evenly throughout an utterance. Here, we ask whether a pressure for UID may have influenced word order patterns cross-linguistically. To this end, we use computational models to test whether real orders lead to greater information uniformity than counterfactual orders. In our empirical study of 10 typologically diverse languages, we find that: (i) among SVO languages, real word orders consistently have greater uniformity than reverse word orders, and (ii) only linguistically implausible counterfactual orders consistently exceed the uniformity of real orders. These findings are compatible with a pressure for information uniformity in the development and usage of natural languages.

翻译：尽管自然语言在典型词序和词序灵活性上差异显著，但其词序仍遵循共有的跨语言统计模式，这一现象常被归因于功能压力。在识别这些压力的研究中，已有工作通过对比真实词序与反事实词序展开分析。然而，此类研究忽略了信息密度均匀假说这一功能性压力——该假说认为信息应在话语中均匀分布。本文探究信息密度均匀压力是否可能影响跨语言的词序模式。为此，我们采用计算模型检验真实词序是否比反事实词序能带来更高的信息均匀性。在对10种类型学差异显著语言的实证研究中发现：（i）在SVO语言中，真实词序的均匀性始终高于反向词序；（ii）仅语言学上不可信的反事实词序能持续超越真实词序的均匀性。这些发现与自然语言发展和使用中存在信息均匀性压力的观点相符。