Functional Thought Experiments

The literature on thought experiments has been mainly concernedwith thought experiments that are directed at a theory, be it in aconstructive or a destructive manner. This has led somephilosophers to argue that all thought experiments can beformulated as arguments. The aim of this paper is to drawattention to a type of thought experiment that is not directed ata theory, but fulfills a specific function within a theory. Suchthought experiments are referred to as functional thoughtexperiments, and they are routinely used in applied statistics. An example is given from frequentist statistics, where a thoughtexperiment is required to establish the probability space. It isconcluded that (a) not all thought experiments can be formulated asarguments, and (b) the role of thought experiments is more generaland more important to scientific reasoning than has previouslybeen recognized.     

Group-based Life Design Counseling in an Italian context

This study examined the effectiveness of group-based Life Design Counseling using the Career-Story Interview. Written exercises were used to implement the seven topics in the Career-Story Interview. The present study employed an experimental design that involved two groups of Italian entrepreneurs from the agricultural and trade sectors, namely an experimental group (38 participants) who received Life Design Counseling (Savickas, 2010) and a control group (34 participants). The results showed a decrease in career decision-making difficulties (Lack of Information and Inconsistent Information) and an increase in career decision-making self-efficacy in the experimental group thus suggesting the value of group-based Life Design Counseling.     

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.     

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.