Cross-Linguistic Evidence for Cognitive Universals in the Noun Phrase, Linguistics Vanguard, 2017-2022

DOI

Noun phrase word order varies cross-linguistically, however, two distributional asymmetries have attracted substantial attention. First, the most common orders place adjectives closest to the noun, then numerals, then demonstratives (e.g., N-Adj-Num-Dem). Second, exceptions to this are restricted to post-nominal position (e.g., N-Dem-Num-Adj, but not, for instance, Adj-Num-Dem-N). These observations have been argued to reflect constraints on cognition. Here we report on two experiments, providing support for this claim. We taught English- and Thai-speaking participants artificial languages in which the position of modifiers relative to the noun differed from their native order (post-nominal position in English, pre-nominal in Thai). We trained participants on single-modifier phrases, and asked them to extrapolate to multiple modifier phrases. We found that both populations infer relative orders of modifiers that conform to the tendency for closest proximity of adjectives, then numerals, then demonstratives. Further, we show that Thai participants, learning pre-nominal modifiers, exhibit a stronger such preference. These results track the typology closely and are consistent with the claim that noun phrase word order reflects properties of human cognition. We discuss future research needed to rule out alternative explanations for our findings, including prior language experience.Languages can be very different from each other. For example, just focussing on the order of words, languages like English put adjectives before nouns ('red house') while languages like Thai put them afterwards ('house red'). Similarly, languages like Vietnamese put Numerals before nouns ('three houses'), while others, like the Kitharaka (spoken in Kenya), put numerals after ('houses three'). If word ordering was simply due to happenstance, we would expect to see all different orders appearing in equal proportion across languages, but we don't find that. In fact, some orders are very common, some are very rare, and some don't seem to appear at all. For example, many languages are ordered like English ('three red houses'), and many are also ordered like Thai, which is exactly the reverse ('houses red three'). But the Kitharaka order ('houses three red') is much rarer, and its mirror image ('red three houses') never seems to occur. Why is this? One of the major controversies in the language sciences is whether we need to appeal to the basic set-up of the human mind to explain the ways languages can vary, or whether these properties are instead a result of cultural differences in communication and social interaction. A great deal of recent work coming from the perspective of psychology assumes the latter: that the properties of language can be boiled down to communication, interaction and the vagaries of history, while most work in linguistics assumes the former: there must be biases in the human mind that allow us to learn languages of particular types more easily than others. This project seeks to resolve that issue. In order to do this, we test how well people learn languages of various types, to see whether their behaviour follows the general tendencies we see across real languages. Importantly, we use artificially constructed languages, rather than natural languages, in order to make sure that they only differ in the crucial respects. For example, we present English speakers with artificial languages that use word orders from Thai and Kitharaka. If Thai orders are more common across languages than Kitharaka ones because the former are easier to learn, then we should see this reflected in the behaviour of learners in our experiments. We can also see whether such patterns are always harder to learn, or if speaking a language which uses them-like Kitharaka-makes them easier to pick up in a new language. To do this, our experiments compare English, Thai, Vietnamese and Kitharaka speakers. If our learners all show the same kinds of patterns in how they learn our artificial languages that we find across real languages, that will suggest that the way languages vary is not random, nor is it entirely a product of historical facts. Rather it would suggest that there are universal cognitive biases at play. We plan to look at not just the basic question of what orders appear, but also two other well-known cases where languages don't seem to vary randomly. The first relates to how words like adjectives and numbers are placed relative to the nouns they modify: most languages place them both before or after (like English and Thai), rather than putting them on opposite sides (e.g., 'two houses red', like Vietnamese). We will test whether this type of pattern is always easier to learn in a new language. Second, we will look at whether people prefer to learn languages with suffixes (e.g., 'cat-s') rather than prefixes (e.g., 'un-happy'). Both types are present in English, but most languages have (more) suffixes. Our project we will shed light on whether there are universal cognitive biases in language learning, if such biases are at play for the particular phenomena we look at, and how people's native languages affect these biases.

The data collection method for this study is artificial language learning experiments. Participants were trained and tested on a miniature linguistic system. Participants were native English and Thai speakers, recruited from Universities in UK and Thailand respectively.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-856693
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=d93e7c175ca4876fbec68a0f483d185dd80fa56796231d83c6c403f775d8c2d4
Provenance
Creator Culbertson, J, University of Edinburgh; Theeraporn, R, Chulalongkorn University; Alexander, M, University of Groningen; Klaus, A, UCL; David, A, QMUL
Publisher UK Data Service
Publication Year 2023
Funding Reference ESRC
Rights Jennifer Culbertson, University of Edinburgh. Ratitamkul Theeraporn, Chulalongkorn University. Martin Alexander, University of Groningen. Abels Klaus, UCL. Adger David, QMUL; The Data Collection is available to any user without the requirement for registration for download/access.
OpenAccess true
Representation
Resource Type Numeric; Text
Discipline Humanities; Linguistics; Psychology; Social and Behavioural Sciences
Spatial Coverage United Kingdom; Thailand