Two approaches to assessing eyewitness accuracy
| dc.contributor.author | Baldassari, Mario J. | |
| dc.contributor.supervisor | Lindsay, D. Stephen | |
| dc.date.accessioned | 2017-12-21T20:41:17Z | |
| dc.date.copyright | 2017 | en_US |
| dc.date.issued | 2017-12-21 | |
| dc.degree.department | Department of Psychology | en_US |
| dc.degree.level | Doctor of Philosophy Ph.D. | en_US |
| dc.description.abstract | This dissertation presents two individual-difference measures that could be used to assess the validity of eyewitness identification decisions. We designed a non-forced two-alternative face recognition task (consisting of mini-lineup test pairs, half of which included a studied face and half of which did not). In three studies involving a total of 583 subjects, proclivity to choose on pairs with two unstudied faces weakly predicted mistaken identifications on culprit-absent lineups, with varying correlation coefficients that failed to reach the value r = 0.4 found in Baldassari, Kantner, and Lindsay (under review). The likelihood of choosing correctly on pairs that included a studied face was only weakly predictive of correct identifications in culprit-present lineups (mean r of .2). We discuss ways of improving standardized measures of both proclivity to choose and likelihood to be correct when choosing. The second measure is based on the Guilty Knowledge Test (GKT), a lie detection method that utilizes an oddball paradigm to evoke the P300 component when a witness sees the culprit. This GKT-based lineup was intended to postdict identification accuracy regardless of witnesses’ overt responses, thus faces are used as stimuli. Half of participants were instructed to respond as if they knew the culprit and wanted to falsely exonerate him. P300 amplitudes evoked by the culprit were indistinguishable from those evoked by a different learned face but were larger than P3s evoked by unfamiliar faces in both the described lying condition and the group of participants who intentionally told the truth. | en_US |
| dc.description.embargo | 2018-12-05 | |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/8909 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | Memory | en_US |
| dc.subject | Eyewitness identification | en_US |
| dc.subject | ERP | en_US |
| dc.subject | Lie detection | en_US |
| dc.subject | Individual differences | en_US |
| dc.subject | Guilty knowledge test | en_US |
| dc.title | Two approaches to assessing eyewitness accuracy | en_US |
| dc.type | Thesis | en_US |