Does g variance change in adulthood? Testing the age de-differentiation hypothesis across sex

In the last decade, changes in the structure of intelligence across the life-span has become a central topic in the research on human intelligence. One of the main hypotheses that has arisen to account for such changes has been the age de-differentiation hypothesis [Balinsky, Genetic Psychology Monographs 23 1941, 191]. It predicts an increase in the importance of g, and a decrease in the number and importance of the lower-order abilities from early maturity to senescence. Despite of the research effort to test this hypothesis, no study has ever been conducted controlling by sex. For that purpose, males and females of the Spanish standardisation sample of the WAIS-III were analysed separately. Results show that the importance of g does not change with age irrespective of sex. Thus, the age de-differentiation hypothesis is rejected for both males and females. The indifferentiation hypothesis is supported as a more appropriate view of the changes in the structure of intelligence across adulthood.     

Learning by Collaborative and Individual‐Based Recommendation Agents

Intelligent recommendation systems can be based on 2 basic principles: collaborative filters and individual‐based agents. In this work we examine the learning function that results from these 2 general types of learning‐smart agents. There has been significant work on the predictive properties of each type, but no work has examined the patterns in their learning from feedback over repeated trials. Using simulations, we create clusters of “consumers” with heterogeneous utility functions and errorful reservation utility thresholds. The consumers go shopping with one of the designated smart agents, receive recommendations from the agents, and purchase products they like and reject ones they do not. Based on the purchase–no purchase behavior of the consumers, agents learn about the consumers and potentially improve the quality of their recommendations. We characterize learning curves by modified exponential functions with an intercept for percentage of recommendations accepted at Trial 0, an asymptotic rate of recommendation acceptance, and a rate at which learning moves from intercept to asymptote. We compare the learning of a baseline random recommendation agent, an individual‐based logistic‐regression agent, and two types of collaborative filters that rely on K‐mean clustering (popular in most commercial applications) and nearest‐neighbor algorithms. Compared to the collaborative filtering agents, the individual agent (a) learns more slowly, initially, but performs better in the long run when the environment is stable; (b) is less negatively affected by permanent changes in the consumer's utility function; and (c) is less adversely affected by error in the reservation threshold to which consumers compare a recommended product's utility. The K‐mean agent reaches a lower asymptote but approaches it faster, reflecting a surprising stickiness of target classifications after feedback from recommendations made under initial (incorrect) hypotheses.     

The number 747 is named faster after seeing Boeing than after seeing Levi's: Associative priming in the processing of multidigit Arabic numerals

Two experiments are reported in which naming multidigit Arabic numerals was shown to depend on the context in which the numbers were presented. Number naming and number decisions were faster after an associative prime (e.g., 747 preceded by the word Boeing) than after an unre- lated prime, both in unmasked and masked priming conditions. On the basis of these findings, we conclude that number naming is not always based on a quantity-based semantically mediated pathway.     

Sequential effects in the lexical decision task: The role of the item frequency of the previous trial

Two lexical decision experiments were conducted to determine whether there is a specific, localized influence of the item frequency of consecutive trials (i.e., first-order sequential effects) when the trials are not related to each other. Both low-frequency words and nonwords were influenced by the frequency of the precursor word (Experiment 1). In contrast, high-frequency words showed little sensitivity to the frequency of the precursor word (Experiment 2), although they showed longer reaction times for word trials preceded by a nonword trial. The presence of sequential effects in the lexical decision task suggests that participants shift their response criteria on a trial-by-trial basis.     

Early vigilance and late avoidance of threat processing: Repressive coping versus low/high anxiety

The time course of a bias in predicting danger as a function of a repressive coping style was examined. The participants belonged to repressor, low - anxious, or high - anxious groups. They read context sentences predictive of threat or nonthreat event outcomes, followed by target words for rapid naming representing the outcomes. The interval between context and target word was 50 ms (Experiment 1), 550 ms (Experiment 2), or 1050 ms (Experiments 3 and 4). There was bias for naming words confirming threatening outcomes: (a) for repressors in the 550-ms delay condition; and (b) for high - anxiety participants in the 1050-ms delay condition. Repressive coping facilitated early processing of threat, but inhibited late processing, whereas high anxiety was characterised by sustained vigilance for threat. There were clear differences in threat processing by repressors and the low - anxious participants