Acquiring variation in an artificial language: Children and adults are sensitive to socially conditioned linguistic variation.

Languages exhibit sociolinguistic variation, such that adult native speakers condition the usage of linguistic variants on social context, gender, and ethnicity, among other cues. While the existence of this kind of socially conditioned variation is well-established, less is known about how it is acquired. Studies of naturalistic language use by children provide various examples where children's production of sociolinguistic variants appears to be conditioned on similar factors to adults' production, but it is difficult to determine whether this reflects knowledge of sociolinguistic conditioning or systematic differences in the input to children from different social groups. Furthermore, artificial language learning experiments have shown that children have a tendency to eliminate variation, a process which could potentially work against their acquisition of sociolinguistic variation. The current study used a semi-artificial language learning paradigm to investigate learning of the sociolinguistic cue of speaker identity in 6-year-olds and adults. Participants were trained and tested on an artificial language where nouns were obligatorily followed by one of two meaningless particles and were produced by one of two speakers (one male, one female). Particle usage was conditioned deterministically on speaker identity (Experiment 1), probabilistically (Experiment 2), or not at all (Experiment 3). Participants were given tests of production and comprehension. In Experiments 1 and 2, both children and adults successfully acquired the speaker identity cue, although the effect was stronger for adults and in Experiment 1. In addition, in all three experiments, there was evidence of regularization in participants' productions, although the type of regularization differed with age: children showed regularization by boosting the frequency of one particle at the expense of the other, while adults regularized by conditioning particle usage on lexical items. Overall, results demonstrate that children and adults are sensitive to speaker identity cues, an ability which is fundamental to tracking sociolinguistic variation, and that children's well-established tendency to regularize does not prevent them from learning sociolinguistically conditioned variation.

Statistical learning of novel graphotactic constraints in children and adults.

The current study explored statistical learning processes in the acquisition of orthographic knowledge in school-aged children and skilled adults. Learning of novel graphotactic constraints on the position and context of letter distributions was induced by means of a two-phase learning task adapted from Onishi, Chambers, and Fisher (Cognition, 83 (2002) B13-B23). Following incidental exposure to pattern-embedding stimuli in Phase 1, participants' learning generalization was tested in Phase 2 with legality judgments about novel conforming/nonconforming word-like strings. Test phase performance was above chance, suggesting that both types of constraints were reliably learned even after relatively brief exposure. As hypothesized, signal detection theory d' analyses confirmed that learning permissible letter positions (d'=0.97) was easier than permissible neighboring letter contexts (d'=0.19). Adults were more accurate than children in all but a strict analysis of the contextual constraints condition. Consistent with the statistical learning perspective in literacy, our results suggest that statistical learning mechanisms contribute to children's and adults' acquisition of knowledge about graphotactic constraints similar to those existing in their orthography.

Learners restrict their linguistic generalizations using preemption but not entrenchment: Evidence from artificial-language-learning studies with adults and children.

A central goal of research into language acquisition is explaining how, when learners generalize to new cases, they appropriately restrict their generalizations (e.g., to avoid producing ungrammatical utterances such as *the clown laughed the man; "*" indicates an ungrammatical form). The past 30 years have seen an unresolved debate between statistical preemption and entrenchment as explanations. Under preemption, the use of a verb in a particular construction (e.g., *the clown laughed the man) is probabilistically blocked by hearing that other verb constructions with similar meanings only (e.g., the clown made the man laugh). Under entrenchment, such errors (e.g., *the clown laughed the man) are probabilistically blocked by hearing any utterance that includes the relevant verb (e.g., by the clown made the man laugh and the man laughed). Across five artificial-language-learning studies, we designed a training regime such that learners received evidence for the (by the relevant hypothesis) ungrammaticality of a particular unattested verb/noun + particle combination (e.g., *chila + kem; *squeako + kem) via either preemption only or entrenchment only. Across all five studies, participants in the preemption condition (as per our preregistered prediction) rated unattested verb/noun + particle combinations as less acceptable for restricted verbs/nouns, which appeared during training, than for unrestricted, novel-at-test verbs/nouns, which did not appear during training, that is, strong evidence for preemption. Participants in the entrenchment condition showed no evidence for such an effect (and in 3/5 experiments, positive evidence for the null). We conclude that a successful model of learning linguistic restrictions must instantiate competition between different forms only where they express the same (or similar) meanings. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reforms to improve reproducibility and quality must be coordinated across the research ecosystem: the view from the UKRN Local Network Leads.

Many disciplines are facing a "reproducibility crisis", which has precipitated much discussion about how to improve research integrity, reproducibility, and transparency. A unified effort across all sectors, levels, and stages of the research ecosystem is needed to coordinate goals and reforms that focus on open and transparent research practices. Promoting a more positive incentive culture for all ecosystem members is also paramount. In this commentary, we-the Local Network Leads of the UK Reproducibility Network-outline our response to the UK House of Commons Science and Technology Committee's inquiry on research integrity and reproducibility. We argue that coordinated change is needed to create (1) a positive research culture, (2) a unified stance on improving research quality, (3) common foundations for open and transparent research practice, and (4) the routinisation of this practice. For each of these areas, we outline the roles that individuals, institutions, funders, publishers, and Government can play in shaping the research ecosystem. Working together, these constituent members must also partner with sectoral and coordinating organisations to produce effective and long-lasting reforms that are fit-for-purpose and future-proof. These efforts will strengthen research quality and create research capable of generating far-reaching applications with a sustained impact on society.

Statistical learning and spelling: Evidence from an incidental learning experiment with children.

Statistical learning processes-akin to those seen in spoken language acquisition (Saffran et al., 1996)-may be important for the development of literacy, particularly spelling development. One previous study provides direct evidence for this process: Samara and Caravolas (2014) demonstrated that 7-year-olds generalize over permissible letter contexts (graphotactics) in novel word-like stimuli under incidental learning conditions. However, unlike in actual orthography, conditioning contexts in Samara and Caravolas' (2014) stimuli comprised perfectly correlated, redundant cues in both word-initial and word-final positions. The current study explores whether 7-year-olds can extract such constraints in the absence of redundant cues. Since theories of literacy development predict greater sensitivity to restrictions within word-final units, we also contrast learning in word-initial and word-final units. We demonstrate that-for 7-year-old learners in two linguistic contexts (English and Turkish)-there is substantial evidence for the learning of both types of restriction.

Language learning, language use and the evolution of linguistic variation.

Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.