Procedural fairness, outcome favorability, and judgments of an authority's responsibility

Fairness theory (R. Folger & R. Cropanzano, 1998, 2001) postulates that, particularly in the face of unfavorable outcomes, employees judge an organizational authority to be more responsible for their outcomes when the authority exhibits lower procedural fairness. Three studies lent empirical support to this notion. Furthermore, 2 of the studies showed that attributions of responsibility to the authority mediated the relationship between the authority's procedural fairness and employees' reactions to unfavorable outcomes. The findings (a) provide support for a key assumption of fairness theory, (b) help to account for the pervasive interactive effect of procedural fairness and outcome favorability on employees' attitudes and behaviors, and (c) contribute to an emerging trend in justice research concerned with how people use procedural fairness information to make attributions of responsibility for their outcomes. Practical implications, limitations, and suggestions for future research also are discussed.     

What do you mean "drunk"? Convergent validation of multiple methods of mapping alcohol expectancy memory networks

The configuration and activation of memory networks have been theorized as mechanisms that underlie the often observed link between alcohol expectancies and drinking. A key component of this network is the expectancy "drunk." The memory network configuration of "drunk" was mapped by using cluster analysis of data gathered from the paired-similarities task (PST) and the Alcohol Expectancy Multi-Axial Assessment (AEMAX). A third task, the free associates task (FA), assessed participants' strongest alcohol expectancy associates and was used as a validity check for the cluster analyses. Six hundred forty-seven 18-19-year-olds completed these measures and a measure of alcohol consumption at baseline assessment for a 5-year longitudinal study. For both the PST and AEMAX, "drunk" clustered with mainly negative and sedating effects (e.g., "sick," "dizzy," "sleepy") in lighter drinkers and with more positive and arousing effects (e.g., "happy," "horny," "outgoing") in heavier drinkers, showing that the cognitive organization of expectancies reflected drinker type (and might influence the choice to drink). Consistent with the cluster analyses, in participants who gave "drunk" as an FA response, heavier drinkers rated the word as more positive and arousing than lighter drinkers. Additionally, gender did not account for the observed drinker-type differences. These results support the notion that for some emerging adults, drinking may be linked to what they mean by the word "drunk." (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

Assessing the use of multiple sources in student essays

The present study explored different approaches for automatically scoring student essays that were written on the basis of multiple texts. Specifically, these approaches were developed to classify whether or not important elements of the texts were present in the essays. The first was a simple pattern-matching approach called "multi-word" that allowed for flexible matching of words and phrases in the sentences. The second technique was latent semantic analysis (LSA), which was used to compare student sentences to original source sentences using its high-dimensional vector-based representation. Finally, the third was a machine-learning technique, support vector machines, which learned a classification scheme from the corpus. The results of the study suggested that the LSA-based system was superior for detecting the presence of explicit content from the texts, but the multi-word pattern-matching approach was better for detecting inferences outside or across texts. These results suggest that the best approach for analyzing essays of this nature should draw upon multiple natural language processing approaches.