Modeling the Development of Children's Use of Optional Infinitives in Dutch and English Using MOSAIC

In this study we use a computational model of language learning called model of syntax acquisition in children (MOSAIC) to investigate the extent to which the optional infinitive (OI) phenomenon in Dutch and English can be explained in terms of a resource-limited distributional analysis of Dutch and English child-directed speech. The results show that the same version of MOSAIC is able to simulate changes in the pattern of finiteness marking in 2 children learning Dutch and 2 children learning English as the average length of their utterances increases. These results suggest that it is possible to explain the key features of the OI phenomenon in both Dutch and English in terms of the interaction between an utterance-final bias in learning and the distributional characteristics of child-directed speech in the 2 languages. They also show how computational modeling techniques can be used to investigate the extent to which cross-linguistic similarities in the developmental data can be explained in terms of common processing constraints as opposed to innate knowledge of universal grammar.     

Why computational models are better than verbal theories: the case of nonword repetition

Tests of nonword repetition (NWR) have often been used to examine children's phonological knowledge and word learning abilities. However, theories of NWR primarily explain performance either in terms of phonological working memory or long‐term knowledge, with little consideration of how these processes interact. One theoretical account that focuses specifically on the interaction between short‐term and long‐term memory is the chunking hypothesis. Chunking occurs because of repeated exposure to meaningful stimulus items, resulting in the items becoming grouped (or chunked); once chunked, the items can be represented in short‐term memory using one chunk rather than one chunk per item. We tested several predictions of the chunking hypothesis by presenting 5–6‐year‐old children with three tests of NWR that were either high, medium, or low in wordlikeness. The results did not show strong support for the chunking hypothesis, suggesting that chunking fails to fully explain children's NWR behavior. However, simulations using a computational implementation of chunking (namely CLASSIC, or Chunking Lexical And Sub‐lexical Sequences In Children) show that, when the linguistic input to 5–6‐year‐old children is estimated in a reasonable way, the children's data are matched across all three NWR tests. These results have three implications for the field: (a) a chunking account can explain key NWR phenomena in 5–6‐year‐old children; (b) tests of chunking accounts require a detailed specification both of the chunking mechanism itself and of the input on which the chunking mechanism operates; and (c) verbal theories emphasizing the role of long‐term knowledge (such as chunking) are not precise enough to make detailed predictions about experimental data, but computational implementations of the theories can bridge the gap.     

Gift Giving at Israeli Weddings as a Function of Genetic Relatedness and Kinship Certainty

This study examines gift giving at Israeli weddings. In accordance with kin selection theory, we hypothesized that wedding guests possessing greater genetic relatedness to the newlyweds would offer greater sums of money as wedding gifts. We also hypothesized that family members stemming from the maternal side (where the genetic lineage has higher kinship certainty) would offer the newlyweds more money than those stemming from the paternal side. Data on the monetary gift sums of the wedding guests from 30 weddings were collapsed according to two criteria: (a) genetic relatedness (0%, 6.25%, 12.5%, 25%, and 50%) and (b) kinship certainty (maternal or paternal lineage). Both hypotheses were supported. We discuss the implications of these data in understanding family dynamics, as well as practical applications associated with the marketing of gifts.