Offline: The possible effects of Internet-related behavior on work values,expectations, & behavior among Ultra-Orthodox millennials

ABSTRACT

This work examines differences in the work-related values, expectations, and behaviors between millennials who are significant users of technology and social media, and those who are not. We delineate the development of millennial behavior using a unique group of millennials, those in the Ultra-Orthodox Jewish (known as “Haredi”) community in Israel. Due to religious and community norms, many Haredi millennials were shielded from digital technology, and particularly the Internet and the various technologies associated with it, such as text messaging and social media. Those who were raised and remained in Haredi communities did not encounter the Internet with any regularity as children. Many as adults are still unfamiliar with social media. Thus, this community presents a unique natural experiment, comparing Haredi millennials who are immersed in social media with those who are not.     

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.     

Pure agraphia and Gerstmann's syndrome as a visuospatial-language dissociation: an experimental case study

A right-handed man suffered a left parieto-occipital cerebral infarction, causing agraphia with Gerstmann's syndrome but without major aphasia, alexia, or apraxia. Oral spelling was superior to written spelling. Experiments were performed involving (1) analysis of errors in writing, (2) tasks of visual imagery, and (3) identifying letters drawn without leaving a visual trace. The results suggest that the agraphia and Gerstmann's syndrome are due to a dissociation of language skills and visuospatial skills caused by a dominant parieto-occipital lesion.     

Variations in characteristic perceptual asymmetry: modality specific and modality general components.

The current study investigates sources of between-subjects variation in asymmetry scores on visual half-field and dichotic listening tasks. For each of these presentation modalities, subjects were given multiple laterality tasks. Results indicate that about 50% of the between-subjects variations in asymmetry scores in each modality is attributable to individual differences in perceptual asymmetries that are not stimulus-specific, referred to as "characteristic perceptual asymmetries" in this paper. In addition, the question of whether individual differences in characteristic perceptual asymmetries are modality specific, modality general, or both was investigated by entering subjects' asymmetry scores from visual half-field and dichotic listening tasks into a principal component analysis. The results of this analysis indicate that there are both modality specific and modality general influences on subjects' characteristic perceptual asymmetries.     

Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.