Speakers' cognitive representations of gender and number morphology shape cross-linguistic tendencies in morpheme order

Languages exhibit a tremendous amount of variation in how they organise and order morphemes within words; however, regularities are also found. For example, gender and number inflectional morphology tend to appear together within a single affix, and when they appear in two separate affixes, gender marking tends to be placed closer to the stem than number. Formal theories of gender and number have been designed (in part) to explain these tendencies. However, determining whether the abstract representations hypothesised by these theories indeed drive the patterns we find cross-linguistically is difficult, if not impossible, based on the natural language data alone. In this study we use an artificial language learning paradigm to test whether the inferences learners make about the order of gender and number affixes—in the absence of any explicit information in the input—accord with formal theories of how they are represented. We test two different populations, English and Italian speakers, with substantially differ- ent gender systems in their first language. Our results suggest a clear preference for placing gender closest to the noun across these populations, across different types of gender systems, and across prefixing and suffixing morphology. These results expand the range of behavioural evidence for the role of cognitive representations in determining morpheme order

Rational After All: Changes in Probability Matching Behaviour Across Time inHumans and Monkeys

Probability matching—where subjects given probabilistic in-put respond in a way that is proportional to those inputprobabilities—has long been thought to be characteristic ofprimate performance in probability learning tasks in a vari-ety of contexts, from decision making to the learning of lin-guistic variation in humans. However, such behaviour is puz-zling because it is not optimal in a decision theoretic sense;the optimal strategy is to always select the alternative with thehighest positive-outcome probability, known as maximising(in decision making) or regularising (in linguistic tasks). Whilethe tendency to probability match seems to depend somewhaton the participants and the task (i.e., infants are less likelyto probability match than adults, monkeys probability matchless than humans, and probability matching is less likely inlinguistic tasks), existing studies suffer from a range of defi-ciencies which make it difficult to robustly assess these dif-ferences. In this paper we present three experiments whichsystematically test the development of probability matchingbehaviour over time in simple decision making tasks, acrossspecies (humans and Guinea baboons), task complexity, andtask domain (linguistic vs non-linguistic). In Experiments 1and 2 we show that adult humans and Guinea baboons exhibitsimilar behaviour in a non-linguistic decision-making task and,contrary to the prevailing view, a tendency to maximise (ba-boons) or significantly over-match (humans) rather than prob-ability match, which strengthens over time and more so withgreater task complexity; our non-human sample size (N = 20baboons) is unprecedented in the probability-matching litera-ture. Experiment 3 provides evidence against domain-specificprobability learning mechanisms, showing that human subjectsover-match high positive-outcome probabilities to a similar de-gree across linguistic and non-linguistic tasks. Our results sug-gest that previous studies may simply have insufficient trials toshow maximising, or be too short to show maximising strate-gies which unfold over time. We thus provide evidence ofshared probability learning mechanisms not only across lin-guistic and non-linguistic tasks but also across primate species

Cross-linguistic patterns of morpheme order reflect cognitive biases: An experimental study of case and number morphology

A foundational goal of linguistics is to investigate whether shared features of the human cognitive system can explain how linguistic patterns are distributed across languages. In this paper we report a series of artificial language learning experiments which aim to test a hypothesised link between cognition and a persistent regularity of morpheme order: number morphemes (e.g., plural markers) tend to be ordered closer to noun stems than case morphemes (e.g., accusative markers) (Universal 39; Greenberg, 1963). We argue that this typological tendency may be driven by learners’ bias towards orders that reflect scopal relationships in morphosyntactic and semantic composition (Bybee, 1985; Rice, 2000; Culbertson & Adger, 2014). This bias is borne out by our experimental results: learners—in the absence of any evidence on how to order number and case morphology—consistently produce number closer to the noun stem. We replicate this effect across two populations (English and Japanese speakers). We also find that it holds independent of morpheme position (prefixal or suffixal), degree of boundedness (free or bound morphology), frequency, and which particular case/number feature values are instantiated in the overt markers (accusative or nominative, plural or singulative). However, we show that this tendency can be reversed when the form of the case marker is made highly dependent on the noun stem, suggesting an influence of an additional bias for local dependencies. Our results provide evidence that universal features of cognition may play a causal role in shaping the relative order of morphemes

More or Less Unnatural: Semantic Similarity Shapes the Learnability and Cross-Linguistic Distribution of Unnatural Syncretism in Morphological Paradigms

Morphological systems often reuse the same forms in different functions, creating what is known as syncretism. While syncretism varies greatly, certain cross-linguistic tendencies are apparent. Patterns where all syncretic forms share a morphological feature value (e.g., first person, or plural number) are most common cross-linguistically, and this preference is mirrored in results from learning experiments. While this suggests a general bias towards natural (featurally homogeneous) over unnatural (featurally heterogeneous) patterns, little is yet known about gradients in learnability and distributions of different kinds of unnatural patterns. In this paper we assess apparent cross-linguistic asymmetries between different types of unnatural patterns in person-number verbal agreement paradigms and test their learnability in an artificial language learning experiment. We find that the cross-linguistic recurrence of unnatural patterns of syncretism in person-number paradigms is proportional to the amount of shared feature values (i.e., similarity) amongst the syncretic forms. Our experimental results further suggest that the learnability of syncretic patterns also mirrors the paradigm’s degree of feature-value similarity. We propose that this gradient in learnability reflects a general bias towards similarity-based structure in morphological learning, which previous literature has shown to play a crucial role in word learning as well as in category and concept learning more generally. Rather than a dichotomous natural/unnatural distinction, our results thus support a more nuanced view of (un)naturalness in morphological paradigms and suggest that a preference for similarity-based structure during language learning might shape the worldwide transmission and typological distribution of patterns of syncretism

Simplifying linguistic complexity: culture and cognition in language evolution

Languages are culturally transmitted through a repeated cycle of learning and communicative interaction. These two aspects of cultural transmission impose (at least) three interacting pressures that can shape the evolution of linguistic structure: a pressure for learnability, a pressure for expressivity, and a pressure for coordination amongst users in a linguistic community. This thesis considers how these sometimes competing pressures impact linguistic complexity across cultural time. Using artificial language and iterated learning experimental paradigms, I investigate the conditions under which complexity in morphological and syntactic systems emerges, spreads, and reduces. These experiments illustrate the interaction of transmission, learning and use in hitherto understudied domains—morphosyntax and word order. In a first study (Chapter 2), I report the first iterated learning experiments to investigate the evolution of complexity in compositional structure at the word and sentence level. I demonstrate that a complex meaning space paired with pressures for learnability and communication can result in compositional hierarchical constituent structure, including fixed combinatorial rules of word formation and word order. This structure grants a productive and productively interpretable language and only requires learners to acquire a finite lexicon and a finite set of combinatorial rules (i.e., a grammar). In Chapter 3, I address the unique effect of communicative interaction on linguistic complexity, by removing language learning completely. Speakers use their native language to express novel meanings either in isolation or during communicative interaction. I demonstrate that even in this case, communicative interaction leads to more efficient and overall simpler linguistic systems. These first two studies provide support for the claim that morphological and syntactic complexity are shaped by an overarching drive towards simplicity (or learnability) in language learning and communication. Chapter 4 reports a series of experiments assessing the possibility that the simplicity bias found in the first two studies operates at a different strength depending on the linguistic level. Studies in natural language learning and in pidgin/creole genesis suggest that while morphological variation seems to be highly susceptible to regularisation, variation in other syntactic features, like word order, appears more likely to be reproduced. I test this experimentally by comparing regularisation of unconditioned variation across morphology and word order in the context of artificial language learning. I show that language users in fact regularise unconditioned variation in a similar way across linguistic levels, suggesting that the simplicity bias may be driven by a single, non-level-specific mechanism. Taken together, the experimental evidence presented in this thesis supports the hypothesis that the cultural and cognitive pressures acting on language users during learning and communicative interaction—for learnability, expressivity and coordination—are at least partially responsible for the evolution of linguistic complexity. Specifically, they are responsible for the emergence of linguistic complexity which maximises learnability and communicative efficiency, and for the reduction of complexity which does not. More generally, the approach taken in this thesis promotes a view of complexity in linguistic systems as an evolving variable determined by the biases of language learners and users as languages are culturally transmitted

Is regularization uniform across linguistic levels? Comparing learning and production of unconditioned probabilistic variation in morphology and word order

Languages exhibit variation at all linguistic levels, from phonology, to the lexicon, to syntax. Importantly, that variation tends to be (at least partially) conditioned on some aspect of the social or linguistic context. When variation is unconditioned, language learners regularize it – removing some or all variants, or conditioning variant use on context. Previous studies using artificial language learning experiments have documented regularizing behavior in the learning of lexical, morphological, and syntactic variation. These studies implicitly assume that regularization reflects uniform mechanisms and processes across linguistic levels. However, studies on natural language learning and pidgin/creole formation suggest that morphological and syntactic variation may be treated differently. In particular, there is evidence that morphological variation may be more susceptible to regularization. Here we provide the first systematic comparison of the strength of regularization across these two linguistic levels. In line with previous studies, we find that the presence of a favored variant can induce different degrees of regularization. However, when input languages are carefully matched – with comparable initial variability, and no variant-specific biases – regularization can be comparable across morphology and word order. This is the case regardless of whether the task is explicitly communicative. Overall, our findings suggest an overarching regularizing mechanism at work, with apparent differences among levels likely due to differences in inherent complexity or variant-specific biases. Differences between production and encoding in our tasks further suggest this overarching mechanism is driven by production

Probability matching is not the default decision making strategy in human and non-human primates

International audienceProbability matching has long been taken as a prime example of irrational behaviour in human decision making; however, its nature and uniqueness in the animal world is still much debated. In this paper we report a set of four preregistered experiments testing adult humans and Guinea baboons on matched probability learning tasks, manipulating task complexity (binary or ternary prediction tasks) and reinforcement procedures (with and without corrective feedback). Our findings suggest that probability matching behaviour within primate species is restricted to humans and the simplest possible binary prediction tasks; utility-maximising is seen in more complex tasks for humans as pattern-search becomes more effortful, and we observe it across the board in baboons, altogether suggesting that it is a cognitively less demanding strategy. These results provide further evidence that neither human nor non-human primates default to probability matching; however, unlike other primates, adult humans probability match when the cost of pattern search is low

Probability matching is not the default decision making strategy in human and non-human primates

Probability matching has long been taken as a prime example of irrational behaviour in human decision making; however, its nature and uniqueness in the animal world is still much debated. In this paper we report a set of four preregistered experiments testing adult humans and Guinea baboons on matched probability learning tasks, manipulating task complexity (binary or ternary prediction tasks) and reinforcement procedures (with and without corrective feedback). Our findings suggest that probability matching behaviour within primate species is restricted to humans and the simplest possible binary prediction tasks; utility-maximising is seen in more complex tasks for humans as pattern-search becomes more effortful, and we observe it across the board in baboons, altogether suggesting that it is a cognitively less demanding strategy. These results provide further evidence that neither human nor non-human primates default to probability matching; however, unlike other primates, adult humans probability match when the cost of pattern search is low

Naturalness is gradient in morphological paradigms: Evidence from positional splits

Agreement markers that refer to the same feature or argument tend to be found in the same position (e.g., all subject agreement markers as suffixes, all object agreement markers as prefixes). However, little is known about the exceptions to this trend: cases where different values of the same feature are marked in different positions in the word (i.e., positional splits). In this study, we explore the positional properties of subject and object person-number agreement markers in a phylogenetically diverse sample of 227 languages. We find that the recurrence of a positional split is proportional to its degree of naturalness, that is, to the amount of shared feature values amongst the forms with the same positional arrangement. Natural patterns (e.g., where prefixal forms all share SG and suffixal forms all share PL) are over-represented in natural languages compared to a random baseline. The most unnatural patterns are underrepresented, and splits with an intermediate level of unnaturalness occur at around chance levels. We hypothesise that this graded bias for naturalness is grounded in a preference for morphological similarity amongst semantically similar forms during language learning. To test this hypothesis we conducted two online artificial language learning experiments where we trained and tested participants on person-number verbal agreement paradigms of different sizes with positional splits of different degrees of naturalness. We found that their relative learnability is also gradient, again proportional to the amount of feature value overlap, thus matching the observed cross-linguistic tendencies. Our findings support the notion that semantic similarity shapes the evolution of morphological structure in person-number verbal agreement systems and that it does so in a gradient way