Naturalizing Logic: a case study of the ad hominem and implicit bias

The fallacies, as traditionally conceived, are wrong ways of reasoning that nevertheless appear attractive to us. Recently, however, Woods (2013) has argued that they don’t merit such a title, and that what we take to be fallacies are instead largely virtuous forms of reasoning. This reformation of the fallacies forms part of Woods’ larger project to naturalize logic. In this paper I will look to his analysis of the argumentum ad hominem as a case study for the prospects of this project. I will argue that the empirical literature on implicit bias presents a difficulty for the reformation of the ad hominem as cognitively virtuous. Cases where implicit bias influences our assessment of the truth or claim or argument are instances of ad hominem reasoning, and these qualify as fallacious on Woods’ own definition

How reflective is the academic essay?

The purpose of this study was to examine the extent of reflection in academic essays. Forty essays, all previously deemed to be of merit quality, were analysed in terms of three elements of reflection - how the educational issue is conceptualized; what the issue means for practice; how practice might be changed to resolve the problematic. Each element was then assigned one of four levels of reflection - technical, descriptive, dialogical and critical. The main finding was that most of the elements were either at a descriptive level of reflection (which the literature argues is not difficult to achieve) or at a dialogical level (which recognizes that knowledge is not certain but does not tease out the relative merits of differing views). These different levels of reflection are seen as adevelopmental stages (from naïve to sophisticated) in gaining control over the process of co-ordinating extant understanding and new evidenc

False News On Social Media: A Data-Driven Survey

In the past few years, the research community has dedicated growing interest to the issue of false news circulating on social networks. The widespread attention on detecting and characterizing false news has been motivated by considerable backlashes of this threat against the real world. As a matter of fact, social media platforms exhibit peculiar characteristics, with respect to traditional news outlets, which have been particularly favorable to the proliferation of deceptive information. They also present unique challenges for all kind of potential interventions on the subject. As this issue becomes of global concern, it is also gaining more attention in academia. The aim of this survey is to offer a comprehensive study on the recent advances in terms of detection, characterization and mitigation of false news that propagate on social media, as well as the challenges and the open questions that await future research on the field. We use a data-driven approach, focusing on a classification of the features that are used in each study to characterize false information and on the datasets used for instructing classification methods. At the end of the survey, we highlight emerging approaches that look most promising for addressing false news