Regularizing Unpredictable Variation: The Roles of Adult and Child Learners in Language Formation and Change

By Carla L. Hudson Kam, Elissa L. Newport. 2005

582 citations recorded by the source corpus.

Subfields: Developmental and Educational Psychology, Language and Linguistics

View Paper: https://www.semanticscholar.org/paper/4f322a8a9eee4216be74c512ba6d164fdf01cbc1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Developmental and Educational Psychology

In Language and Linguistics

Citations in the corpus

Age Effects in Second Language Learning: Stepping Stones Toward Better Understanding (2013, unknown): “…of issues, from the nature of inferring structure from input (Goldowsky & Newport, 1993; Monner, Vatz, Morini, Hwang, & DeKeyser, 2012; Newport, 1990; Saffran, Johnson, Aslin, & Newport, 1999; Ullman, 2001) to the mechanisms of historical change (Hudson Kam & Newport, 2005, 2009; Kerswill, 1996).”
The nature of generalization in language (2009, background): “…processes, are taking another look at the question of whether the generalizations can be learned (Childers and Tomasello 2002; Elman et al. 1996; Kam and Newport 2005; Kuhl 2000; Gomez 2002; Sa¤ran et al. 1996; Sa¤ran et al. 1999; Sa¤ran 2001a, 2001b, Sa¤ran and Wilson 2003; Tomasello 2003;…”
Statistical learning: From acquiring specific items to forming general rules (2012, unknown): “For example, Hudson Kam and Newport (2005) (2009) and Austin and Newport (2011) presented adults and children with miniature languages containing inconsistent, probabilistically occurring forms (e.g., nouns were followed by the nonsense word ka 67% of the time and by the nonsense word po the remaini”
Language as shaped by the brain. (2008, background): “In this context, it has been suggested that innovations may primarily be due to adults (Bybee, in press), whereas constraints on children’s acquisition of language may provide the strongest pressure towards regularization (e.g., Hudson Kam & Newport 2005).”
Iterated learning and the evolution of language. (2014, unknown): “The combination of iterated learning and artificial language learning has been used to show that miniature languages exhibiting unpredictable or ‘free’ variation (largely absent from natural languages) become increasingly regular and predictable as a result of their transmission [53,54], demonstrati”
Natural Language Acquisition and Grounding for Embodied Robotic Systems (2017, result): “This idea agrees with the findings of Hudson-Kam and Newport (2005), which shows that children reproduce the most frequent grammatical forms they hear.”
Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift (2010, background): “For example, learners facing unpredictable variation may either reproduce this variability accurately or collapse it towards more deterministic rules—a process referred to as regularization (Hudson & Newport 2005; Reali & Grifﬁths 2009).”