An investigation of children's fears and their mothers' fears

Children (75 female, 52 male) in grades 2 through 8 completed the Fear Survey Schedule for Children (FSS-FC). Their mothers completed the same questionnaire twice: once for themselves and a second time to estimate their children's fears. Spearman's rhos indicated that there was a high degree of correspondence between the mothers' rank-ordered estimates of their children's fears and the children's rank-ordered self-reports (=.86 for males, =.96 for females.However, mothers' overall estimates of their children's general fearfulness were significantly correlated only with their daughters' fearfulness, not with their sons'. Further analyses showed that mothers could generally identify their children's highest-rated fears. All test-retest measures were significant. In summary, these results suggest that mothers may provide useful clinical information about their children's specific fears and that the FSS-FC is a reliable instrument with which to assess children's fears.     

Changing industry to continuous operations: Different strokes for different plants

A survey method was designed to evaluate the effect of shift work on industrial workers and to develop recommendations for 7-day around-the-clock production work systems. A Work-Sleep Survey was then offered to 2,340 hourly and salaried workers at four plants. Each plant was in the rubber and plastic products industry and on 5-day around-the-clock operations using permanent shifts. Of the total workers, 90.38% responded to the survey. The results agree with the findings of a previous survey, offered to workers through their unions, using many of the same survey items. The plants were found to differ in worker demographics, habits, and preferences. This survey method is helpful as an aid for the design and evaluation of shift-work systems tailored to specific worker and plant requirements.     

Gregory of Nyssa and Divine Simplicity: A Conceptualist Reading

Andrew Radde‐Gallwitz probes Gregory of Nyssa on divine simplicity, a topic that Radde‐Gallwitz treated earlier in a book‐length monograph and takes further here in response to critics. As he notes, the Cappadocians and their opponents shared belief in divine simplicity. But for Gregory, simplicity functions as part of affirming the co‐equal divinity of the Father and Son, against his opponents. Radde‐Gallwitz lists six negative claims that Gregory’s understanding of divine simplicity supports: (1) God is immaterial; (2) God is without parts; (3) God does not possess any perfection “by acquisition”; (4) God does not possess any perfection “by participation”; (5) in God, there is no mixture or conflux of qualities, especially opposite qualities; (6) in God, there are no degrees of more or less. Yet with regard to positive statements about God’s perfections—for example the relation of God’s goodness to God’s wisdom—things are more difficult, as Radde‐Gallwitz shows. Interpreters of Gregory have differed sharply on this issue, in part because Gregory does not make his position crystal clear. Radde‐Gallwitz himself earlier held that Gregory considers God to have real but non‐definitive perfections distinct from the divine essence. Indebted to Richard Cross, however, Radde‐Gallwitz here adjusts his view, distinguishing more firmly between the divine essence itself and our limited concepts. He draws upon the Platonic distinction between natural and conventional naming, which differ in their accounts of what makes words meaningful. Arguing that Gregory is a “naturalist,” he reads Gregory’s texts on divine simplicity in this light.     

Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners

The curse of dimensionality, which has been widely studied in statistics and machine learning, occurs when additional features cause the size of the feature space to grow so quickly that learning classification rules becomes increasingly difficult. How do people overcome the curse of dimensionality when acquiring real‐world categories that have many different features? Here we investigate the possibility that the structure of categories can help. We show that when categories follow a family resemblance structure, people are unaffected by the presence of additional features in learning. However, when categories are based on a single feature, they fall prey to the curse, and having additional irrelevant features hurts performance. We compare and contrast these results to three different computational models to show that a model with limited computational capacity best captures human performance across almost all of the conditions in both experiments.