Theories of the syllogism: A meta-analysis

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Project

Description: Syllogisms are arguments about the properties of entities. They consist of 2 premises and a conclusion, which can each be in 1 of 4 “moods”: All A are B, Some A are B, No A are B, and Some A are not B. Their logical analysis began with Aristotle, and their psychological investigation began over 100 years ago. This article outlines the logic of inferences about syllogisms, which includes the evaluation of the consistency of sets of assertions. It also describes the main phenomena of reasoning about properties. There are 12 extant theories of such inferences, and the article outlines each of them and describes their strengths and weaknesses. The theories are of 3 main sorts: heuristic theories that capture principles that could underlie intuitive responses, theories of deliberative reasoning based on formal rules of inference akin to those of logic, and theories of deliberative reasoning based on set-theoretic diagrams or models. The article presents a meta-analysis of these extant theories of syllogisms using data from 6 studies. None of the 12 theories provides an adequate account, and so the article concludes with a guide — based on its qualitative and quantitative analyses — of how best to make progress toward a satisfactory theory.

Wiki

This project concerns the paper by Khemlani and Johnson-Laird (2012), which presents a qualitative and quantitative meta-analysis of syllogistic reasoning. It includes a corrigendum to the Table 6 presented in the paper, which corrects some minor bugs in calculating the columns "Accuracy and rank order" (discovered by Alice Ping Ping Tse).

Files

Loading files...

Citation

Tags

Recent Activity

Loading logs...

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.