CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2018-2021) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years
10.5
impact factor
CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2018-2021) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2018 – 21).
10.5
pubmed
CiteScore measures the average citations received per peer-reviewed document published in this title. CiteScore values are based on citation counts in a range of four years (e.g. 2018-2021) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2018 – 21).
1- Department of Science and Technology Studies, Faculty of Management, Science and Technology, Amirkabir University of Technology, Tehran, Iran
* Corresponding Author Address: Unit 303, Alborz Building, Sajjad 9, Sajjad Boulevard, Mashhad, Iran. Postal code: 9187816577 (mohammadreza.hezareh.aut@gmail.com)
Abstract (1420 Views)
Proof paradoxes refer to situations where statistical evidence indicates that a suspect is the perpetrator, yet a conviction based solely on this evidence appears counterintuitive. The prevailing approach to addressing proof paradoxes involves establishing a criterion for distinguishing naked statistical evidence from other types of evidence. Smith introduces normic support as a criterion for the aforementioned distinction. Conversely, Di Bello proposes a modified version of normic support, arguing that the absence of access to undercutting defeaters in naked statistical evidence distinguishes it from other forms of evidence. In this research, we argue, in line with Pollock's perspective, that undercutting defeaters can still be accessed in the context of naked statistical evidence. Furthermore, by focusing on an example of proof paradoxes and drawing on Pollock's arguments - illustrated quantitatively by the base rate fallacy - we demonstrate the effectiveness of undercutting defeaters. Consequently, Di Bello's argument appears to be questionable.