Treating the speech communities as homogeneous entities is not an accurate representation of reality, as it misses some of the complexities of linguistic interactions. Inter-individual variation and multiple types of biases are ubiquitous in speech communities, regardless of their size. This variation is often neglected due to the assumption that “majority rules,” and that the emerging language of the community will override any such biases by forcing the individuals to overcome their own biases, or risk having their use of language being treated as “idiosyncratic” or outright “pathological.” In this paper, we use computer simulations of Bayesian linguistic agents embedded in communicative networks to investigate how biased individuals, representing a minority of the population, interact with the unbiased majority, how a shared language emerges, and the dynamics of these biases across time. We tested different network sizes (from very small to very large) and types (random, scale-free, and small-world), along with different strengths and types of bias (modeled through the Bayesian prior distribution of the agents and the mechanism used for generating utterances: either sampling from the posterior distribution [“sampler”] or picking the value with the maximum probability [“MAP”]). The results show that, while the biased agents, even when being in the minority, do adapt their language by going against their a priori preferences, they are far from being swamped by the majority, and instead the emergent shared language of the whole community is influenced by their bias.

This paper argues for a gradient approach to word order, which treats word order preferences, both within and across languages, as a continuous variable. Word order variability should be regarded as a basic assumption, rather than as something exceptional. Although this approach follows naturally from the emergentist usage-based view of language, we argue that it can be beneficial for all frameworks and linguistic domains, including language acquisition, processing, typology, language contact, language evolution and change, variationist linguistics and formal approaches. Gradient approaches have been very fruitful in some domains, such as language processing, but their potential is not fully realized yet. This may be due to practical reasons. We discuss the most pressing methodological challenges in corpus-based and experimental research of word order and propose some solutions and best practices.

Languages of diverse structures and different families tend to share common patterns if they are spoken in geographic proximity. This convergence is often explained by horizontal diffusibility, which is typically ascribed to language contact. In such a scenario, speakers of two or more languages interact and influence each other’s languages, and in this interaction, more grammaticalized features tend to be more resistant to diffusion compared to features of more lexical content. An alternative explanation is vertical heritability: languages in proximity often share genealogical descent. Here, we suggest that the geographic distribution of features globally can be explained by two major pathways, which are generally not distinguished within quantitative typological models: feature diffusion and language expansion. The first pathway corresponds to the contact scenario described above, while the second occurs when speakers of genetically related languages migrate. We take the worldwide distribution of nominal classification systems (grammatical gender, noun class, and classifier) as a case study to show that more grammaticalized systems, such as gender, and less grammaticalized systems, such as classifiers, are almost equally widespread, but the former spread more by language expansion historically, whereas the latter spread more by feature diffusion. Our results indicate that quantitative models measuring the areal diffusibility and stability of linguistic features are likely to be affected by language expansion that occurs by historical coincidence. We anticipate that our findings will support studies of language diversity in a more sophisticated way, with relevance to other parts of language, such as phonology.

AbstractWe examine the complex nominal classification system in Nepali (Indo-European, Indic), a language spoken at the intersection of the Indo-European and Sino-Tibetan language families, which are usually associated with prototypical examples of grammatical gender and numeral classifiers, respectively. In a typologically rare pattern, Nepali possesses two gender systems based on the human/non-human and masculine/feminine oppositions, in addition to which it has also developed an inventory of at least ten numeral classifiers as a result of contact with neighbouring Sino-Tibetan languages. Based on an analysis of the lexical and discourse functions of the three systems, we show that their functional contribution involves a largely complementary distribution of workload with respect to individual functions as well as the type of categorized nouns and referents. The study thus contributes to the ongoing discussions concerning the typology and functions of nominal classification as well as the effects of long-term language contact on language structure.