No Cover Image

Journal article 418 views

Drawing conclusions: Representing and evaluating competing explanations

Alice Liefgreen, David A. Lagnado

Cognition, Volume: 234, Start page: 105382

Swansea University Author: Alice Liefgreen

Full text not available from this repository: check for access using links below.

Check full text

DOI (Published version): 10.1016/j.cognition.2023.105382

Abstract

Despite the increase in studies investigating people's explanatory preferences in the domains of psychology and philosophy, little is known about their preferences in more applied domains, such as the criminal justice system. We show that when people evaluate competing legal accounts of the sam...

Full description

Published in: Cognition
ISSN: 0010-0277
Published: Elsevier BV 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa63276
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2023-04-28T13:20:18Z
last_indexed 2023-04-28T13:20:18Z
id cronfa63276
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>63276</id><entry>2023-04-28</entry><title>Drawing conclusions: Representing and evaluating competing explanations</title><swanseaauthors><author><sid>5a11aaeb0cd68f36ec54c5534dc541bd</sid><firstname>Alice</firstname><surname>Liefgreen</surname><name>Alice Liefgreen</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2023-04-28</date><deptcode>FGHSS</deptcode><abstract>Despite the increase in studies investigating people's explanatory preferences in the domains of psychology and philosophy, little is known about their preferences in more applied domains, such as the criminal justice system. We show that when people evaluate competing legal accounts of the same evidence, their explanatory preferences are affected by whether they are required to draw causal models of the evidence. In addition, we identify ‘mechanism’ as an explanatory feature that people value when evaluating explanations. Although previous research has shown that people can reason correctly about causality, ours is one of the first studies to show that generating and drawing causal models directly affects people's evaluations of explanations. Our findings have implications for the development of normative models of legal arguments, which have so far adopted a singularly ‘unified’ approach, as well as the development of modelling tools to support people's reasoning and decision-making in applied domains. Finally, they add to the literature on the cognitive basis of evaluating competing explanations in new domains.</abstract><type>Journal Article</type><journal>Cognition</journal><volume>234</volume><journalNumber/><paginationStart>105382</paginationStart><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0010-0277</issnPrint><issnElectronic/><keywords>Explanation, causal models, evidential reasoning, simplicity, mechanism</keywords><publishedDay>7</publishedDay><publishedMonth>5</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-05-07</publishedDate><doi>10.1016/j.cognition.2023.105382</doi><url>http://dx.doi.org/10.1016/j.cognition.2023.105382</url><notes/><college>COLLEGE NANME</college><department>Humanities and Social Sciences - Faculty</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>FGHSS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2023-09-04T18:05:14.6528174</lastEdited><Created>2023-04-28T14:15:04.2070782</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">Hilary Rodham Clinton School of Law</level></path><authors><author><firstname>Alice</firstname><surname>Liefgreen</surname><order>1</order></author><author><firstname>David A.</firstname><surname>Lagnado</surname><order>2</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling v2 63276 2023-04-28 Drawing conclusions: Representing and evaluating competing explanations 5a11aaeb0cd68f36ec54c5534dc541bd Alice Liefgreen Alice Liefgreen true false 2023-04-28 FGHSS Despite the increase in studies investigating people's explanatory preferences in the domains of psychology and philosophy, little is known about their preferences in more applied domains, such as the criminal justice system. We show that when people evaluate competing legal accounts of the same evidence, their explanatory preferences are affected by whether they are required to draw causal models of the evidence. In addition, we identify ‘mechanism’ as an explanatory feature that people value when evaluating explanations. Although previous research has shown that people can reason correctly about causality, ours is one of the first studies to show that generating and drawing causal models directly affects people's evaluations of explanations. Our findings have implications for the development of normative models of legal arguments, which have so far adopted a singularly ‘unified’ approach, as well as the development of modelling tools to support people's reasoning and decision-making in applied domains. Finally, they add to the literature on the cognitive basis of evaluating competing explanations in new domains. Journal Article Cognition 234 105382 Elsevier BV 0010-0277 Explanation, causal models, evidential reasoning, simplicity, mechanism 7 5 2023 2023-05-07 10.1016/j.cognition.2023.105382 http://dx.doi.org/10.1016/j.cognition.2023.105382 COLLEGE NANME Humanities and Social Sciences - Faculty COLLEGE CODE FGHSS Swansea University 2023-09-04T18:05:14.6528174 2023-04-28T14:15:04.2070782 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Alice Liefgreen 1 David A. Lagnado 2
title Drawing conclusions: Representing and evaluating competing explanations
spellingShingle Drawing conclusions: Representing and evaluating competing explanations
Alice Liefgreen
title_short Drawing conclusions: Representing and evaluating competing explanations
title_full Drawing conclusions: Representing and evaluating competing explanations
title_fullStr Drawing conclusions: Representing and evaluating competing explanations
title_full_unstemmed Drawing conclusions: Representing and evaluating competing explanations
title_sort Drawing conclusions: Representing and evaluating competing explanations
author_id_str_mv 5a11aaeb0cd68f36ec54c5534dc541bd
author_id_fullname_str_mv 5a11aaeb0cd68f36ec54c5534dc541bd_***_Alice Liefgreen
author Alice Liefgreen
author2 Alice Liefgreen
David A. Lagnado
format Journal article
container_title Cognition
container_volume 234
container_start_page 105382
publishDate 2023
institution Swansea University
issn 0010-0277
doi_str_mv 10.1016/j.cognition.2023.105382
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url http://dx.doi.org/10.1016/j.cognition.2023.105382
document_store_str 0
active_str 0
description Despite the increase in studies investigating people's explanatory preferences in the domains of psychology and philosophy, little is known about their preferences in more applied domains, such as the criminal justice system. We show that when people evaluate competing legal accounts of the same evidence, their explanatory preferences are affected by whether they are required to draw causal models of the evidence. In addition, we identify ‘mechanism’ as an explanatory feature that people value when evaluating explanations. Although previous research has shown that people can reason correctly about causality, ours is one of the first studies to show that generating and drawing causal models directly affects people's evaluations of explanations. Our findings have implications for the development of normative models of legal arguments, which have so far adopted a singularly ‘unified’ approach, as well as the development of modelling tools to support people's reasoning and decision-making in applied domains. Finally, they add to the literature on the cognitive basis of evaluating competing explanations in new domains.
published_date 2023-05-07T18:05:16Z
_version_ 1776127433876963328
score 11.017797

Similar Items