Three types of conduct‐problem boys in an educational setting

Third grade boys identified as being disruptive to on‐going classroom activities were grouped according to their teacher's ratings of their behaviour characteristics as unco‐operative (Type I), easily flustered (Type II), and unco‐operative and easily flustered (Type III). No significant differences in performance existed between types on individually administered tests of perception and psycholinguistic abilities. On group administered tests of academic achievement and intelligence, the uncooperative boys did significantly better than the other two types. It was also determined that the easily flustered boys did substantially better on individually administered measures of IQ. than they did on group administered measures. These findings suggest that teachers should avoid using group tests to evaluate disruptive boys they perceive as being easily flustered.     

Effectiveness of the PPVT-R for screening gifted students

The PPVT-R and the WISC-R were administered to a sample of 35 students, grades 1 through 8, who were nominated for possible participation in gifted programming. The correlation between the PPVT-R and Full Scale IQ was .27, which probably was affected by the restricted range of ability assessed. The PPVT-R showed modest incremental effectiveness beyond informal referral procedures in predicting toward a WISC-R criterion score.     

Concept learning by pigeons: Matching-to-sample with trial-unique video picture stimuli

Pigeons were trained to match-to-sample with several new methodologies: a large number of stimuli, computer-drawn color picture stimuli, responses monitored by a computer touch screen, stimuli presented horizontally from the floor, and grain reinforcement delivered onto the picture stimuli. Following acquisition, matching-to-sample concept learning was assessed by transfer to novel stimuli on the first exposure to pairs of novel stimuli. One group (trial-unique), trained with 152 different pictures presented once daily, showed excellent transfer (80% correct). Transfer and baseline performances were equivalent, indicating that the matching-to-sample concept had been learned. A second group (2-stimulus), trained with only two different pictures, showed no evidence of transfer. These results are discussed in terms of the effect of numbers of exemplars on previous failures to find concept learning in pigeons, and the implications of the positive finding from this experiment on abstract concept learning and evolutionary cognitive development.     

Creating value in ecosystems: Crossing the chasm between knowledge and business ecosystems

Policy makers take initiatives to stimulate knowledge ecosystems in technology hotspots. It is implicitly assumed that these ecosystems will lead to value networks through which the participating companies can realize a competitive advantage. Value networks refer to business ecosystems where the value proposition is offered by a group of companies which are mutually complementary. The strategy literature suggests that business ecosystems lead to competitive advantages for each of the partners in the ecosystem. Based on a unique hand-collected database of 138 innovative start-ups in the region of Flanders, we analyze the knowledge and business ecosystem and the financial support network. We find that the knowledge ecosystem is well structured and concentrated around a number of central actors while the business ecosystem is almost non-existent at the local level. Further, we find that the financial support network is almost 100% publicly backed and fails to bridge the knowledge and business ecosystem. The implications for policy makers who tend to focus on the development of local ecosystems are discussed.