THE GOLEM LEGEND AND THE ENIGMA OF FACEBOOK

We are easily misguided as to the true nature of Facebook, and tend to treat it simply as a powerful technological instrument in the service of human intentions. We can, however, gain a better picture of it through recourse to the Jewish tradition of the golem, an image of human beings, created by them in a re-enactment of their own creation by God. It turns into a magic servant in modernity with an inherent dynamic running between its human and its subhuman characteristics. This dynamic is the main cause behind its becoming uncontrollable. In like manner, what is subhuman in Facebook serves its masters and functions under their total control, but also empowers Facebook's increasingly human operation, an algorithm-based capability which raises growing doubts about what counts as human. Facebook implies the crisis of humanity which coincides with the “death of God,” that is, the obsolescence of the idea of a divine creator.     

Aggressive behavior inhibition by serotonin and quipazine injected into the amygdala in the rat

The effects on aggressive behavior, open-field activity, and pain threshold of bilateral microinjections of serotonin (20 micrograms) and quipazine (20 micrograms), the direct serotonergic receptor agonist, into the cortico-medial amygdala were investigated in Wistar rats. Both drugs significantly prolonged the attack latency in isolated killer rats (predatory aggression model), and suppressed the incidence of aggressive postures/attacks in shock-induced fighting test (affective aggression). The only difference in the open-field behavior was the lower number of central square entries in drug-treated compared to saline-injected rats. None of the substances produced any significant change in jump threshold. It is concluded that stimulation of serotonin receptors within the amygdala produces inhibition of affective and muricidal behavior in isolated rats. The effect does not seem to be dependent on changes in general activity and pain sensitivity.     

Comparative clinicogenetic study of schizophrenic psychoses

The author diagnoses 350 carefully selected schizophrenic subjects, their parents and their siblings during parallel studies using three different clinical classification systems and analyzes the results by multiple threshold analysis and the multifactorial inheritance model. The results suggest that, of the three classifications the author studied, Leonhard's and Sneshnewski's system yield relatively homogeneous subgroups; this indicates the future significance of these nosological systems for the planning of biopsychiatric research.     

Lay conceptions of personality: Eliciting tiers of a scientific conception of personality

Two studies are reported which examine the availability of scientific propositions of personality in lay conceptions of personality. It is argued from a social constructivist perspective that models of personality must derive from and refer to lay conceptions of persons. Eysenck's trait-type model of introversion-extraversion, containing specific propositions about phenotypic and genotypic differences between extraverts and introverts, was utilized as the scientific model of personality and its availability in lay conceptions of personality was examined in two studies. In the first study, subjects were presented with a genotypic characterization of either an introvert or an extravert target person and asked to infer corresponding phenotypic differences. In the second study, the inference process was reversed with subjects being asked to infer genotypic characteristics of introverts versus extraverts on the basis of phenotypic target person desecrations of the two types. Results from both studies show a high degree of accuracy in subjects' inferences, suggesting that laypersons have well-formed conceptions about personality containing ‘higher-order’ psychogenetic propositions corresponding to Eysenck's trait-type model. The implications of the findings for theory construction are discussed.     

On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.