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Title: Unfamiliar face matching in the applied context
Author: McCaffery, Jennifer
ISNI:       0000 0004 6058 7608
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2016
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Matching unfamiliar faces is a difficult task. Despite this, ID checks are the primary screening method for individuals wishing to access countries, employment and a range of financial and medical services. Those we might consider experts, such as passport officers, are no better at the task than general population. Individuals with superior unfamiliar face matching have been identified, but the range of ability remains large across expert and general populations alike. Even individuals with superior face recognition skills have not been consistently found to have superior unfamiliar face matching abilities. This suggests that unfamiliar face matching ability may be highly specific. It may also suggest that the unfamiliar matching tasks carried out in the lab are different from ID checks in the applied context. It is the aim of this thesis to investigate the nature of unfamiliar face matching in the applied context and identify ways in which performance might be predicted. In Chapters 2 and 3 participants are required to match unfamiliar faces shown with a passport context and to check the validity of the accompanying biographical information. The presence of a passport context biases viewers to identify face pairs as the same and presence of a face pair biases and reduces accuracy when checking biographical information. These findings demonstrate that applied error rates in unfamiliar face matching may well have been underestimated. In Chapter 4, a battery of tasks is used to identify predictors of unfamiliar face matching ability. The results show that unfamiliar face matching is positively associated with other face identity tasks. However, same and different unfamiliar face matching also associate with more general measures of local processing and space perception. These findings are tested in Chapter 5 and the theoretical implications of these results and methods for optimising unfamiliar face matching performance are discussed.
Supervisor: Burton, Mike Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available