Who Belongs to Me? Social Relationship and Personality Characteristics in the Transition to Young Adulthood

Not much is known about how social network characteristics change in the transition out of school and what role Big Five personality plays in this context. The aim of this paper was twofold. First, we explored changes in social network and relationship characteristics across the transition out of secondary school. Second, we examined within‐person and between‐person effects of personality on these social network changes. Results based on a series of multilevel models to a longitudinal sample of 2287 young adults revealed four main findings. First, social networks increased in size, and this increase was mainly due to a larger number of nonkin. Stable social networks during the transition consisted mainly of family ties but were generally characterized by high closeness. Second, extraversion and openness consistently predicted network size, whereas agreeableness predicted network overlap. Third, increases in emotional closeness were found only for kin; closeness was generally lower for unstable relationships. Fourth, changes in emotional closeness were related to personality, particularly neuroticism, agreeableness, and conscientiousness for stable relationships; for unstable relationships, however, closeness was related to extraversion and openness. The article concludes by discussing the role of personality for social relationship development and the active moulding of social networks in young adulthood. Copyright © 2014 European Association of Personality Psychology     

Isolated words enhance statistical language learning in infancy

Infants are adept at tracking statistical regularities to identify word boundaries in pause-free speech. However, researchers have questioned the relevance of statistical learning mechanisms to language acquisition, since previous studies have used simplified artificial languages that ignore the variability of real language input. The experiments reported here embraced a key dimension of variability in infant-directed speech. English-learning infants (8-10 months) listened briefly to natural Italian speech that contained either fluent speech only or a combination of fluent speech and single-word utterances. Listening times revealed successful learning of the statistical properties of target words only when words appeared both in fluent speech and in isolation; brief exposure to fluent speech alone was not sufficient to facilitate detection of the words' statistical properties. This investigation suggests that statistical learning mechanisms actually benefit from variability in utterance length, and provides the first evidence that isolated words and longer utterances act in concert to support infant word segmentation.     

Interactions between statistical and semantic information in infant language development

Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because linking distributional cues vs. phonological information to semantics make different computational demands on learners, we also tested whether their use is related to language proficiency. We found that 22-month-old infants with smaller vocabularies generalized using phonological cues; however, infants with larger vocabularies showed the opposite pattern of results, generalizing based on distributional cues. These findings suggest that both phonological and distributional cues marking word categories promote early word learning. Moreover, while correlations between these cues are important to forming word categories, we found infants' weighting of these cues in subsequent word-learning tasks changes over the course of early language development.