Cognitive,Behavioral and Goal Adjustment Coping and Depressive Symptoms in Young People with Diabetes: A Search for Intervention Targets for Coping Skills Training

The aim of the present study was to find relevant coping factors for the development of psychological intervention programs for young people with Type 1 (T1) diabetes. A wide range of coping techniques was studied, including cognitive coping, behavioral coping and goal adjustment coping. A total of 78 young people with T1 diabetes participated. They were contacted through a social networking website, several Internet sites, and flyers. A wide range of coping techniques appeared to be related to depressive symptoms. Especially the cognitive coping strategies self-blame, rumination, refocus positive, and other-blame, together with goal adjustment coping, were of importance. A large proportion of the variance of depressive symptoms could be explained (65 %). These findings suggest that these specific coping strategies should be part of coping skills trainings for young people with T1 diabetes.     

Understanding and the Norm of Explanation

I propose and defend the hypothesis that understanding is the norm of (the speech act of) explanation. On this proposal, an explanation should express understanding. I call this the understanding account of explanation. The understanding account is supported by social and introspective observations. It is also supported by the relationship between knowledge and understanding, on the one hand, and assertion and explanation, on the other.     

The Politics of Paradox: Leo Strauss’s Biblical Debt to Spinoza (and Kierkegaard)

The political philosopher Leo Strauss is famous for contending that any synthesis of reason and revelation is impossible, since they are irreconcilable antagonists. Yet he is also famous for praising the secular regime of liberal democracy as the best regime for all human beings, even though he is well aware that modern philosophers such as Spinoza thought this regime must make use of biblical morality to promote good citizenship. Is democracy, then, both religious and secular? Strauss thought that Spinoza was contradictory in teaching that reason and revelation should be separated from each other while also insisting that a secular democratic politics still requires the biblical morality of charity (love thy neighbor as thyself). The paradox that liberal democracy is both religious and secular, which is central to Spinoza, was dismissed by Strauss as a Machiavellian subterfuge or the cynical attempt to use religion for political purposes. In order to adhere to his dualistic separation of reason and revelation, Strauss turned to ancient Greek political philosophy, particularly the ideas of Plato and Aristotle, as the true ground of liberal democracy since this classical tradition was never exposed to biblical revelation. Yet, the illiberal and hierarchical implications of Greek political thought, which clash with Strauss’s modern views on human individuality and dignity, ultimately take him back to the biblically based philosophies of Spinoza and Kierkegaard, who teach the paradox that the Bible is the true foundation of human freedom.     

The puzzle of language evolution

Linguistics must again concentrate on the evolutionary nature of language, so that language models are more realistic with respect to human natural languages and have a greater explanatory force. Multi-agent systems are proposed as a possible route to develop such evolutionary models and an example is given of a concrete experiment in the origins and evolution of word-meaning based on a multi-agent approach.     

Knowledge level learning and the power law: A soar model of skill acquisition in scheduling

Zusammenfassung. Das hier vorgestellte Modell lernt graduell, Planungsaufgaben aus der Klasse der Maschinenbelegungsprobleme (job-shop-scheduling problems) zu lösen. Mit Hilfe des Chunking-Mechanismus von Soar wird episodisches Wissen über die Belegungsreihenfolge von Aufträgen auf Maschinen memoriert. Bei der Entwicklung des Modells wurden zahlreiche qualitative (z. B. Transfereffekte) und quantitative Befunde (z. B. Bearbeitungszeiten) aus einer früheren empirischen Untersuchung berücksichtigt. In einer Validierungsstudie wurden dieselben Aufgaben von 14 Probanden und dem Modell bearbeitet. Die Passung von Simulationsdaten und empirischen Ergebnissen fiel insgesamt gut aus. Allerdings löst das Modell die Aufgaben schneller und zeigt auch einen etwas besseren Lernverlauf als die Probanden. Das Modell liefert eine Erklärung für das Rauschen, das typischerweise bei Bearbeitungszeiten zu beobachten ist: es handelt sich um erworbenes Wissen, das mehr oder weniger gut und auch unterschiedlich häufig auf neue Situationen übertragen wird. Der Lernverlauf der Probanden entspricht nur für aggregierte Daten einer Potenzfunktion (power law). Der vorgestellte Mechanismus zeigt, wie ein symbolisches Modell der Informationsverarbeitung graduelle Verhaltensänderungen generiert und wie der offensichtliche Erwerb allgemeiner Prozeduren ohne explizites Lernen von deklarativen Regeln erfolgen kann. Es wird nahegelegt, daß es sich hier um die Modellierung einer Form impliziten Lernens handelt. Summary. The model presented here gradually learns how to perform a job-shop scheduling task. It uses Soar's chunking mechanism to acquire episodic memories about the order to schedule jobs. The model was based on many qualitative (e.g., transfer effects) and quantitative (e.g., solution time) regularities found in previously collected data. The model was tested with new data where scheduling tasks were given to the model and to 14 subjects. The model generally fit these data with the restrictions that the model performs the task (in simulated time) faster than the subjects, and its performance improves somewhat more quickly than the subjects' performance. The model provides an explanation of the noise typically found in problem solving times - it is the result of learning actual pieces of knowledge that transfer more or less to new situations but rarely by an average amount. Only when the data are averaged (i.e., over subjects) does the smooth power law appear. This mechanism demonstrates how symbolic models can exhibit a gradual change in behavior and how the apparent acquisition of general procedures can be performed without resorting to explicit declarative rule generation. We suggest that this may represent a type of implicit learning.