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Appears in Collections:University of Stirling Research Data
Title: Stirling Face Recognition Scale Dataset 2018
Creator(s): Bobak, Anna Katarzyna
Mileva, Viktoria R
Hancock, Peter J B
Contact Email:
Date Available: 23-Mar-2018
Citation: Bobak, AK; Mileva, VR; Hancock, PJB (2018): Stirling Face Recognition Scale Dataset 2018. University of Stirling. Faculty of Natural Sciences. Dataset.
Publisher: University of Stirling. Faculty of Natural Sciences.
Dataset Description (Abstract): A reliable self-report measure to assess the broad spectrum of face recognition ability (FRA) from developmental prosopagnosia (DP) to super-recognition (SR) would make a valuable contribution to initial screening of large populations. We examined performance of 96 naive participants and seven SRs, using a range of face and object processing tasks and a newly developed 20-item questionnaire, the Stirling Face Recognition Scale (SFRS). Overall, our findings suggest that young adults have only moderate insight into their FRA, but those who have been previously informed of their (exceptional) performance, the SRs, estimate their FRA accurately. Principal Component Analysis of SFRS yielded two components. One loads on questions about low ability and correlates with perceptual tasks and one loads on questions about high FRA and correlates with memory for faces. We recommend that self-report measures of FRA should be used in addition to behavioural testing, to allow for cross-study comparisons, until new, more reliable instruments of self-report are developed. However, self-report measures should not be solely relied upon to identify highly skilled individuals. Implications of these results for theory and applied practice are discussed
Dataset Description (TOC): SFRS_dataset_QJEP_2018 - The file contains demographic information (variables 1 -5), scores in individual questions of the Stirling Face Recognition Scale (variables 6 – 25). Further, the file contains raw scores for the Cambridge Face Memory Test Long form (variable 26), Cambridge Car Memory Test (Variable 27), Models Face Matching Test (variable 28), Full SFRS score (variable 29), group (variable 30), Z scores for the above variables (variables 31-34), Experimenter collecting data (variable 35), PCA two factor solution (variable 37-38). Please see readme file for further details.
Type: dataset
Contract/Grant Title: Face Matching for Automatic Identity Retrieval, Recognition, Verification and Management
Funder(s): EPSRC - Engineering and Physical Sciences Research Council
Contract/Grant Number: EP/N007743/1
Rights: Rights covered by the standard CC-BY 4.0 licence:
Affiliation(s) of Dataset Creator(s): University of Stirling (Psychology)

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Data_SFRS_stored.sav16.32 kB.SAV is a file extension used for saved data of SPSS (Statistical Package for the Social Sciences). SPSS is used for statistical analysis. SAV files contain binary data which can only be used on the platform that created the file. If migrating the file to another platform, it would have to be converted into the appropriate format. IBM SPSS Version 23.0 usedView/Open
Data readme.docx11.67 kBMicrosoft Word XMLView/Open

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