Einstein,his theories,and his aesthetic considerations

This article deals with the question whether aesthetic considerations affected Einstein in formulating both his theories of relativity. The opinions of philosophers and historians alike are divided on this matter. Thus, Gerald Holton supports the view that Einstein employed aesthetic considerations in formulating his theory of special relativity whereas Jim Shelton opposes it, one of his reasons being that Einstein did not mention such considerations. The other theory, namely, that of general relativity, is discussed by John D. Norton. He asserts that the successful completion of this theory was due to Einstein's adherence to mathematical simplicity resulting from experience, as Einstein himself stated, and not from an aesthetic drive, to which he did not refer. The present work attempts to overcome this deficiency indirectly by investigating Einstein's aesthetic awareness and its consequences for his work. It is found that this awareness was imbedded in his perception of nature and is linked to the criteria (such as simplicity) that guided him in formulating his theories. The conclusion thus reached is that aesthetic considerations did play a role in Einstein's endeavour, contrary to the assertions of Shelton and Norton.     

Two ways to be complex and why they matter: implications for attitude strength and lying

Integrative complexity broadly measures the structural complexity of statements. This breadth, although beneficial in multiple ways, can potentially hamper the development of specific theories. In response, the authors developed a model of complex thinking, focusing on 2 different ways that people can be complex within the integrative complexity system and subsequently developed measurements of each of these 2 routes: Dialectical complexity focuses on a dialectical tension between 2 or more competing perspectives, whereas elaborative complexity focuses on complexly elaborating on 1 singular perspective. The authors posit that many variables have different effects on these 2 forms of complexity and subsequently test this idea in 2 different theoretical domains. In Studies 1a, 1b, and 2, the authors demonstrate that variables related to attitude strength (e.g., domain importance, extremism, domain accessibility) decrease dialectical complexity but increase elaborative complexity. In Study 3, the authors show that counterattitudinal lying decreases dialectical complexity but increases elaborative complexity, implicating a strategic (as opposed to a cognitive strain) view of the lying-complexity relationship. The authors argue that this dual demonstration across 2 different theoretical domains helps establish the utility of the new model and measurements as well as offer the potential to reconcile apparent conflicts in the area of cognitive complexity.     

Recognition models of alphanumeric characters

Several methods to study the recognition and similarity of alphanumeric characters are briefly discussed and evaluated. In particular, the application of the choice-model (Luce, 1959, 1963) to recognition of letters is criticized. A feature analytic model for recognition of alphanumeric characters based on Tversky’s (1977) features of similarity is proposed and tested. It is argued that the proposed model: (a) is parsimonious in that it utilizes a relatively small number of parameters, (b) is psychologically more meaningful compared with other approaches in that it is attempting to study underlying processes rather than just reveal a similarity structure, (c) yields predictions that have a high level of fit with the observed data. Possible implications from the use of the model for future research are briefly discussed.     

Automated Integrative Complexity

Integrative complexity is a conceptually unique and very popular measurement of the complexity of human thought. We believe, however, that it is currently being underutilized because it takes quite a bit of time to score. More time‐efficient computer‐based measurements of complexity that are currently available are correlated with integrative complexity at fairly low levels. To help fill in this gap, we developed a novel automated integrative complexity system designed specifically from the integrative complexity theoretical framework. This new automated IC system achieved an alpha of .72 on the standard integrative complexity coding test. In addition, across nine datasets covering over 1,300 paragraphs, this new automated system consistently showed modest relationships with human‐scored integrative complexity (average alpha = .62; average r = .46). Further analyses revealed that this relationship consistently remained significant when controlling for superficial markers of complexity and that the new system accounted for both the differentiation and integration components of integrative complexity. Although the overlap between the automated and human‐scored systems is only modest (and thus suggests the continued usefulness of human scoring), it nonetheless provides the best automated integrative complexity measurement to date.