How much self-presentation behavior do applicants from the United Arab Emirates exhibit?

Applicants from different cultures vary in their self-presentation behavior during job interviews. This study investigates self-presentation behavior in the United Arab Emirates (UAE), the second largest economy in the Arab world. Specifically, it examines self-presentation behavior of applicants from the UAE and compares it to the behavior of American, European, and Chinese applicants from previous studies. The randomized response technique was used to gather self-presentation prevalence data of 111 UAE applicants regarding self-presentation behavior in their last job interview. Prevalence rates were lower than those from the United States and from China but higher than those from Iceland and from Switzerland. Results indicate that though UAE culture values modesty, UAE applicants still engage in distinct self-presentation behavior.     

Training Observers to Detect Deception Effects of Self-Monitoring and Rehearsal

It was predicted that trained observers would detect deception more accurately than untrained observers. More specifically, it was predicted that the highest deception detection accuracy would be found among trained observers judging the veracity of low self-monitors and unrehearsed liars, whereas the lowest detection accuracy would be found among untrained observers judging the veracity of high self-monitors and rehearsed deceivers. It also was hypothesized that the discrepancy between observers‘actual ability to detect deception and their certainty in the accuracy of their judgments would be smaller for trained observers than for untrained observers. Observers trained to detect deception used six behavioral cues based on research by deTurck and Miller (1985): (a) message duration, (b) response latency, (c) adaptors, (d) pauses, (e) nonfluencies, and (f) hand gestures. Results confirmed both hypotheses.     

Multiattribute Decision Making in Context: A Dynamic Neural Network Methodology

A theoretical structure for multiattribute decision making is presented, based on a dynamical system for interactions in a neural network incorporating affective and rational variables. This enables modeling of problems that elude two prevailing economic decision theories: subjective expected utility theory and prospect theory. The network is unlike some that fit economic data by choosing optimal weights or coefficients within a predetermined mathematical framework. Rather, the framework itself is based on principles used elsewhere to model many other cognitive and behavioral data, in a manner approximating how humans perform behavioral functions. Different, interconnected modules within the network encode (a) attributes of objects among which choices are made, (b) object categories, (c) and goals of the decision maker. An example is utilized to simulate the actual consumer choice between old and new versions of Coca-Cola. Potential applications are also discussed to market decisions involving negotiations between participants, such as international petroleum traders.     

Religion and the Human Rights Idea

Three recent books focus, in different ways, on the idea of human rights and its relation to religion and religious ethics. All three books discussed here address criticisms of the human rights idea and seek to establish the relationship of religion and human rights with regard to the field of policy. The present discussion begins with an overview that places these three books in the larger context of the development of the human rights idea and its historical relationship with religion. It then turns to Little's book, next to the collection of essays edited by Twiss, Simion, and Petersen, which is described internally as a Festschrift for Little, and then to Hogan's book, and in the final section it explores comparisons among the books.