Detecting Fabricated Interviews Using the Hamming Distance

In the research literature on survey methodology, there is considerable discussion of interviewer effects and how to prevent data fabrication; however, there is little discussion on the detection of data fabrication by interviewers in published data, and there are even fewer papers examining the ph...

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Main Authors: Jörg Blasius, Lukas Sausen
Format: Article
Language:English
Published: European Survey Research Association 2023-08-01
Series:Survey Research Methods
Subjects:
Online Access:https://ojs.ub.uni-konstanz.de/srm/article/view/7961
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author Jörg Blasius
Lukas Sausen
author_facet Jörg Blasius
Lukas Sausen
author_sort Jörg Blasius
collection DOAJ
description In the research literature on survey methodology, there is considerable discussion of interviewer effects and how to prevent data fabrication; however, there is little discussion on the detection of data fabrication by interviewers in published data, and there are even fewer papers examining the phenomenon of employees of survey research organizations fabricating data. Among them, Blasius and Thiessen (2015) show for the PISA 2009 principal data that employees of survey research organizations in some countries duplicate cases to generate data. While the authors focus on exact copies, more sophisticated data fabrication techniques might include duplicating whole cases and changing a few entries afterwards. By calculating Hamming distances and applying them to the same data, we show that – in some countries in particular – large parts of the data have been duplicated, and most of them have been retrospectively modified to a small degree.
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spelling doaj.art-0794be5f30984ba8b851ea2378175fd02023-10-13T07:35:20ZengEuropean Survey Research AssociationSurvey Research Methods1864-33612023-08-0117210.18148/srm/2023.v17i2.7961Detecting Fabricated Interviews Using the Hamming DistanceJörg BlasiusLukas Sausen0University of Bonn In the research literature on survey methodology, there is considerable discussion of interviewer effects and how to prevent data fabrication; however, there is little discussion on the detection of data fabrication by interviewers in published data, and there are even fewer papers examining the phenomenon of employees of survey research organizations fabricating data. Among them, Blasius and Thiessen (2015) show for the PISA 2009 principal data that employees of survey research organizations in some countries duplicate cases to generate data. While the authors focus on exact copies, more sophisticated data fabrication techniques might include duplicating whole cases and changing a few entries afterwards. By calculating Hamming distances and applying them to the same data, we show that – in some countries in particular – large parts of the data have been duplicated, and most of them have been retrospectively modified to a small degree. https://ojs.ub.uni-konstanz.de/srm/article/view/7961Fabricated data, string distances, PISA data
spellingShingle Jörg Blasius
Lukas Sausen
Detecting Fabricated Interviews Using the Hamming Distance
Survey Research Methods
Fabricated data, string distances, PISA data
title Detecting Fabricated Interviews Using the Hamming Distance
title_full Detecting Fabricated Interviews Using the Hamming Distance
title_fullStr Detecting Fabricated Interviews Using the Hamming Distance
title_full_unstemmed Detecting Fabricated Interviews Using the Hamming Distance
title_short Detecting Fabricated Interviews Using the Hamming Distance
title_sort detecting fabricated interviews using the hamming distance
topic Fabricated data, string distances, PISA data
url https://ojs.ub.uni-konstanz.de/srm/article/view/7961
work_keys_str_mv AT jorgblasius detectingfabricatedinterviewsusingthehammingdistance
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