Beyond its theoretical success, the development of molecular genetics has brought about the possibility of extraordinary progress in the study of classification and in the inference of the evolutionary history of many species and populations. A major step forward was represented by the availability of extremely large sets of molecular data suited to quantitative and computational treatments. In this paper, we argue that even in cognitive sciences, purely theoretical progress in a discipline such as linguistics may have analogous impact. Thus, exactly on the model of molecular biology, we propose to unify two traditionally unrelated lines of linguistic investigation: 1) the formal study of syntactic variation (parameter theory) in the biolinguistic program; 2) the reconstruction of relatedness among languages (phylogenetic taxonomy). The results of our linguistic analysis have thus been plotted against data from population genetics and the correlations have turned out to be largely significant: given a non-trivial set of languages/populations, the description of their variation provided by the comparison of systematic parametric analysis and molecular anthropology informatively recapitulates their history and relationships. As a result, we can claim that the reality of some parametric model of the language faculty and language acquisition/transmission (more broadly of generative grammar) receives strong and original support from its historical heuristic power. Then, on these grounds, we can begin testing Darwin's prediction that, when properly generated, the trees of human populations and of their languages should eventually turn out to be significantly parallel.

中文翻译：

---

形式语言学作为人口统计历史的线索。

除了其理论上的成功之外，分子遗传学的发展还带来了在分类研究和推断许多物种和种群进化史方面取得非凡进步的可能性。向前迈出的一大步是提供了适用于定量和计算处理的大量分子数据。在本文中，我们认为，即使在认知科学中，语言学等学科的纯理论进展也可能具有类似的影响。因此，正好在分子生物学模型上，我们建议统一两种传统上不相关的语言学研究路线：1）在生物语言程序中对句法变异（参数理论）进行形式化研究；2）语言之间的关联性重建（系统分类学）。因此，我们根据人口遗传学的数据对语言分析的结果进行了绘图，相关性已证明是非常重要的：给定一组非平凡的语言/种群，通过系统参数分析的比较来提供对它们的变异的描述分子人类学从内容上概括了他们的历史和关系。结果，我们可以断言，语言学院和语言习得/传输（更广泛地说是生成语法）的某些参数模型的现实从其历史启发力中获得了强大而原始的支持。然后，基于这些理由，我们可以开始检验达尔文的预测，即正确生成的人口树和其语言最终应最终证明是平行的。