We examined self-reported maternal and paternal harsh parenting (HP) and its effect on the moment-to-moment dynamic coupling of maternal autonomy support and children’s positive, autonomous behavior. This positive behavior coupling was measured via hidden Markov models as the likelihood of transitions into specific positive dyadic states in real time. We also examined whether positive behavior coupling, in turn, predicted later HP and child behavior problems. Children (N=96; age 3½ years at Time 1) and mothers completed structured clean-up and puzzle tasks in the laboratory. Mothers’ and fathers’ HP was associated with children being less likely to respond positively to maternal autonomy support; mothers’ HP was also associated with mothers being less likely to respond positively to children’s autonomous behavior. When mothers responded to children’s autonomous behavior with greater autonomy support, children showed fewer externalizing and internalizing problems over time and mothers showed less HP over time. These results were unique to the dynamic coupling of maternal autonomy support and children’s autonomous behavior: the overall amount of these positive behaviors did not similarly predict reduced problems. Findings suggest that HP in the family system compromises the coregulation of positive behavior between mother and child and that improving mothers’ and children’s abilities to respond optimally to one another’s autonomy-supportive behaviors may reduce HP and child behavior problems over time.
The oftenfi erce competition on crowdfunding markets can significantly affect project success. While various factors have been considered in predicting the success of crowdfunding projects, to the best knowledge of the authors, the phenomenon of competition has not been investigated. In this paper, we study the competition on crowdfunding markets through data analysis, and propose a probabilistic generative model, Dynamic Market Competition (DMC) model, to capture the competitiveness of projects in crowdfunding. Through an empirical evaluation using the pledging history of past crowdfunding projects, our approach has shown to capture the competitiveness of projects very well, and significantly outperforms several baseline approaches in predicting the daily collected funds of crowdfunding projects, reducing errors by 31.73% to 45.14%. In addition, our analyses on the correlations between project competitiveness, project design factors, and project success indicate that highly competitive projects, while being winners under various setting of project design factors, are particularly impressive with high pledging goals and high price rewards, comparing to medium and low competitive projects. Finally, the competitiveness of projects learned by DMC is shown to be very useful in applications of predictingfi nal success and days taken to hit pledging goal, reaching 85% accuracy and error of less than 7 days, respectively, with limited information at early pledging stage.
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