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dc.contributor.authorSutherland, Edward John
dc.date.accessioned2010-01-28T08:49:13Z
dc.date.available2010-01-28T08:49:13Z
dc.date.issued1999
dc.identifier.urihttp://hdl.handle.net/2436/90773
dc.descriptionA thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy
dc.description.abstractResearch by Manktelow and Over (1991,1992) suggested that utility, a construct usually associated with the separate discipline of decision-making research, played a role in mediating deontic reasoning. This research added to a growing feeling of links between decision-making and reasoning. In order to further these links an additional construct from decision-making research was applied to reasoning: probability. Initial experiments considered the role of probability in indicative conditionals, and found evidence to support the use of probability by participants on tasks such as this. The task used was Wason's (1966,1968) four-card selection task, although this task was revised in order to facilitate the use of probabilistic information in the task. This resulted in the introduction of the Large Array Selection Task (LAST). Following these initial findings a move was made to the realm of deontic reasoning. Deontic reasoning is a form of practical reasoning about actions, reasoning about what actions one should, ought or may perform. The task used here was a revised version of Cheng and Holyoak's (1985) immigration task employing the LAST. 'Mese results showed a large effect of probability on deontic reasoning. Finally a set of computer experiments were run which presented participants with probabilistic information, and demonstrated that participants could extract probabilistic information from the data presented to them. The interpretation of these results considers current theories of both indicative and deontic reasoning, and the mental models approach of Johnson-Laird and Bytne (1991) is favoured here. This theory can account for the findings presented whereas alternative theories made predictions that were not supported by the data presented in this thesis. Finally there is a discussion of future research including a need to research the role of probability in other related tasks, such as deontic statements involving threats and promises, as well as looking at utility and probability in inductive reasoning.
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dc.language.isoen
dc.publisherUniversity of Wolverhampton
dc.titleThe role of probability in indicative and deontic conditionals
dc.typeThesis or dissertation
dc.type.qualificationnamePhD
dc.type.qualificationlevelDoctoral
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
refterms.dateFOA2020-05-26T10:19:56Z
html.description.abstractResearch by Manktelow and Over (1991,1992) suggested that utility, a construct usually associated with the separate discipline of decision-making research, played a role in mediating deontic reasoning. This research added to a growing feeling of links between decision-making and reasoning. In order to further these links an additional construct from decision-making research was applied to reasoning: probability. Initial experiments considered the role of probability in indicative conditionals, and found evidence to support the use of probability by participants on tasks such as this. The task used was Wason's (1966,1968) four-card selection task, although this task was revised in order to facilitate the use of probabilistic information in the task. This resulted in the introduction of the Large Array Selection Task (LAST). Following these initial findings a move was made to the realm of deontic reasoning. Deontic reasoning is a form of practical reasoning about actions, reasoning about what actions one should, ought or may perform. The task used here was a revised version of Cheng and Holyoak's (1985) immigration task employing the LAST. 'Mese results showed a large effect of probability on deontic reasoning. Finally a set of computer experiments were run which presented participants with probabilistic information, and demonstrated that participants could extract probabilistic information from the data presented to them. The interpretation of these results considers current theories of both indicative and deontic reasoning, and the mental models approach of Johnson-Laird and Bytne (1991) is favoured here. This theory can account for the findings presented whereas alternative theories made predictions that were not supported by the data presented in this thesis. Finally there is a discussion of future research including a need to research the role of probability in other related tasks, such as deontic statements involving threats and promises, as well as looking at utility and probability in inductive reasoning.


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