The Effects of Income and Skill Utilization on the Underemployed's Self‐Esteem,Mental Health,and Life Satisfaction

This longitudinal study examined the effects of underemployment on psychological well‐being (i.e., self‐esteem, mental health, and life satisfaction) using a sample of 99 unemployed and 153 reemployed individuals in South Korea. Underemployment was determined by wage and skill utilization. The results indicated that when underemployment was determined by wage change, the underemployed showed a more favorable mental health level and more life satisfaction than the unemployed. However, when determined by wage difference, the underemployed were similar to the unemployed. For skill utilization‐based underemployment, no difference was observed between the underemployed and the unemployed. The implications for future research are discussed.     

The impact of object carriage on independent locomotion

The current study examined whether carrying objects in one's hands influenced different parameters associated with independent locomotion. Specifically, 14- and 24-month-olds walked in a straight path under four conditions of object carriage – no object (control), one object carried in one hand (one object-one hand), two objects carried in each of the hands (two objects-two hands), and one object carried in both hands simultaneously (one object-two hands). Although carrying objects failed to influence a variety of kinematic parameters of gait, it did affect children's arm postures, with children adopting less mature arm positions when carrying objects. Finally, arm position was related to walking skill, but only for older children when they were not carrying objects. These findings indicate that although a relation does exist between arm positions and gait parameters, this relation is easily disrupted by carrying loads, even small ones.     

Familiar Verbs Are Not Always Easier Than Novel Verbs: How German Pre‐School Children Comprehend Active and Passive Sentences

Many studies show a developmental advantage for transitive sentences with familiar verbs over those with novel verbs. It might be that once familiar verbs become entrenched in particular constructions, they would be more difficult to understand (than would novel verbs) in non‐prototypical constructions. We provide support for this hypothesis investigating German children using a forced‐choice pointing paradigm with reversed agent‐patient roles. We tested active transitive verbs in study 1. The 2‐year olds were better with familiar than novel verbs, while the 2½‐year olds pointed correctly for both. In study 2, we tested passives: 2½‐year olds were significantly below chance for familiar verbs and at chance for novel verbs, supporting the hypothesis that the entrenchment of the familiar verbs in the active transitive voice was interfering with interpreting them in the passive voice construction. The 3½‐year olds were also at chance for novel verbs but above chance with familiar verbs. We interpret this as reflecting a lessening of the verb‐in‐construction entrenchment as the child develops knowledge that particular verbs can occur in a range of constructions. The 4½‐year olds were above chance for both familiar and novel verbs. We discuss our findings in terms of the relative entrenchment of lexical and syntactic information and to interference between them.     

A Computational Model for the Item‐Based Induction of Construction Networks

According to usage‐based approaches to language acquisition, linguistic knowledge is represented in the form of constructions—form‐meaning pairings—at multiple levels of abstraction and complexity. The emergence of syntactic knowledge is assumed to be a result of the gradual abstraction of lexically specific and item‐based linguistic knowledge. In this article, we explore how the gradual emergence of a network consisting of constructions at varying degrees of complexity can be modeled computationally. Linguistic knowledge is learned by observing natural language utterances in an ambiguous context. To determine meanings of constructions starting from ambiguous contexts, we rely on the principle of cross‐situational learning. While this mechanism has been implemented in several computational models, these models typically focus on learning mappings between words and referents. In contrast, in our model, we show how cross‐situational learning can be applied consistently to learn correspondences between form and meaning beyond such simple correspondences.     

Effect of salespeople's acquisition–retention trade-off on performance

This research examines the impact of the acquisition–retention resource allocation at the individual salesperson level – that is, the proportion of their time dedicated to acquisition versus retention activities – on their sales performance. We extend prior research that investigates the acquisition–retention trade-off below (i.e., customer value approach) or above (i.e., firm portfolio approach) the salesperson's perspective by also incorporating many ‘within-firm’ factors that are critical to capturing the contingent nature of the allocation decision. The results suggest that firms can double their sales gains by implementing a trade-off strategy that customizes the acquisition allocation at the salesperson level. Using matched triadic data gathered from 227 salespersons, 106 supervisors and the seller's database, the authors find an inverted U-shaped linkage between the proportion of time allocated to acquisition activities and sales performance. Moderation analyses show that salespeople's optimal acquisition allocation depends on their knowledge breadth and job commitment, their supervisor's experience and job commitment and the quantity and quality of the prospects in their relationship portfolio.     

Task interspersal for individuals with autism and other neurodevelopmental disorders

This paper reviews recent studies on task interspersal (TI) for increasing skill acquisition in children who have been diagnosed with autism spectrum disorders and other neurodevelopmental disorders. We highlight some limitations of these studies and provide specific recommendations for future research on TI procedures.     

A method to improve the hazard perception of young novice drivers based on Bandura’s observational learning theory: Supplement to expert commentary training

Compared with experienced drivers, young novice drivers are more likely to have traffic accidents. The main reasons are that they lack experience, their hazard perception is weak, and their visual search strategy is underdeveloped. Research shows that hazard perception training can improve the visual search strategy of young novice drivers and enhance their hazard perception ability. We propose that a driver's visual search behaviour, like any other action, can be developed by observing the behaviour of a role model. In an experiment based on a driving simulator, we clustered the visual search paths of 20 experienced drivers, selected the drivers with the best visual search behaviour, and obtained visual search path video footage to produce hazard perception training videos. Using these videos, we applied Bandura’s observation learning theory to train 20 young novice drivers. We call this approach “training based on experienced drivers' performance”. To determine the effects of training based on experienced drivers' performance, 20 young novice drivers were given the usual expert commentary training, and 20 young drivers were given no training. The results showed that training based on experienced drivers' performance and expert commentary training had positive effects on the average speed of young novice drivers through hazard sections. Compared with untrained young novice drivers, trained young novice drivers decreased their speed in response to dangerous road sections. Compared with young novice drivers who received expert commentary training and those who did not receive training, young novice drivers who received training based on experienced drivers' performance showed significant improvements in visual search. These results suggest that training based on experienced drivers' performance can help young novice drivers improve their hazard perception, especially in visual aspects. This training method can complement existing training methods for young novice drivers.     

How Many Mechanisms Are Needed to Analyze Speech? A Connectionist Simulation of Structural Rule Learning in Artificial Language Acquisition

Some empirical evidence in the artificial language acquisition literature has been taken to suggest that statistical learning mechanisms are insufficient for extracting structural information from an artificial language. According to the more than one mechanism (MOM) hypothesis, at least two mechanisms are required in order to acquire language from speech: (a) a statistical mechanism for speech segmentation; and (b) an additional rule-following mechanism in order to induce grammatical regularities. In this article, we present a set of neural network studies demonstrating that a single statistical mechanism can mimic the apparent discovery of structural regularities, beyond the segmentation of speech. We argue that our results undermine one argument for the MOM hypothesis.