Can you help me choosing syllogism, that require the same number of MM (Byrne, Johnson-Laird), but have different informational gain (PHM, Oaksford, Chater)? High informational gain has a syllogism with low a priori probability (e.g. "all A are B") as the opposite are conclusions "some a re not b", which are very probable for random objects, and have low informational gain.
This is already quite an old question and still, I am the first to answer. I would say both theories are mistaken, look-alike theories with little explanatory power. I can demonstrate this if you are interested.
Hi Andreas. I'd love tho hear that.
Last years I've worked on other topics, however I'd love to go back to this.
Hi Michal, cool, I am glad you are interested. Let's first see mental models theory. It was actually introduced in the 80's as an alternative to Euler circles, providing a much better explanatory power. Still, mental models are actually only a graphical variant of Euler circles. I attached a picture about the denotation of the four main syllogistic statements with mental models and with Euler circles. You can see that they are exactly the same, except that in mental models, we denote the content of the sets, so no need to denote the boundary of the sets, whereas in Euler circles we denote the boundaries, so no need to separately denote the content of the sets. It is well known that traditional Euler circles are not suitable to describe people's syllogistic inferences, and since mental models are the same notation, obviously, they are not suitable either. Consequently, whatever has been told about the explanatory power of mental models is simply rhetorical. I have collected some fun citations do demonstrate this,I can copy & paste them here is you haven't yet lost your interest.
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